Investigation of a biopsychosocial
perspective of pain in Brazilian chronic
pain patients
Jamir J. Sardá Jr.
B.Sc, M.Sc.
Thesis submitted in fulfilment of the requirements for the
degree of Doctor of Philosophy
The University of Sydney
2007
Supervisor’s Certificate
This is to certify that the thesis entitled ”Investigation of a
biopsychosocial
perspective
of
pain
in
Brazilian
chronic
pain
patients” submitted by Jamir J. Sardá Jr. in fulfilment of the
requirements for the degree of Doctor of Philosophy is in a form
ready for examination.
Associate Professor Michael K. Nicholas
Faculty of Medicine
University of Sydney
February 2007
ii
Candidate’s Certificate
I, Jamir J. Sardá Jr., hereby declare that the work contained within
this thesis is my own and had not been submitted to any other
institution as a part or a whole requirement for any higher degree.
Jamir J. Sardá Jr.
February 2007
iii
Acknowledgments
There are a number of people who collaborated directly and indirectly to the
completion of this thesis, to whom I would like to acknowledge.
First at all, I would like to thanks my supervisor Associate Professor Michael
Nicholas, who shared his experience and knowledge with me, and was
present, kind, patient, wise, and tireless in guiding me through this journey.
However these words are not enough to express my gratitude to a great
mentor.
My co-supervisor Dr. Cibele M. A. Pimenta gave me some motivation to do
this thesis a couple years before it really started, and her support during the
data collection was essential.
Dr. Ali Asghari was a great colleague during these 4 years. He was always
keen to discuss my ideas and to motivate me. He also gave me precious
statistical advises and was a true teacher.
I also would like to thank several professionals who make the Pain Research
and Management Institute a place of excellence and one of the best Pain
Centres in the world. Professor Michael Cousins, Professor Laurie Matter,
Ms. Isobel Taylor, Professor Phillip Siddall, Dr. Fiona Blyth, Dr. Stephen
Loftus, Ms. Lee Beeston, Ms. Lois Tonkin, Dr. Robin Murray, Ms. Sandra
Hives, Ms. Ros Wyllie and Ms. Wendy O’Hanlon. Without them the PMRC
would not be what it is and I would not be able to do my thesis.
iv
I would like to mention a number of people in Brazil who also collaborated to
this research project. Ms. Maria Luisa Lombas – Coordinator of Capes PhD
Scholarship Program. Dr. Pedro Girardi – Coordinator of the course of
Psychology at Univali - Itajaí, Dr. Almir Sais – Coordinator of the course of
Psychology at Univali - Biguaçu, Dr. Marco Modesto, Dr. Ivan Pereira, Dr. Li
Shi Mim,
Dr.
José
Oswaldo
Junior,
Dr.
Claúdio
Corrêa,
Dra.
Lilian
Hennemann, and all the research assistants.
I would like to acknowledge all participants who were keen to give personal
information about their lives aiming to contribute with the progress of
science.
An special thanks must go to my partner, Nelisia Medeiros, who has always
give me great support, motivation, happiness and love and has been very
patient over this period.
Two other unique women were also present during this whole process, my
mother Lurdes S.Tiago Sardá and Isobel Taylor. They are my role model of
strength, courage, knowledge and resilience.
If the University of Sydney permitted candidates to dedicate theses, then this
thesis would be dedicated to these three women.
v
Abstract
This series of studies is based on a biopsychosocial perspective of
chronic
pain.
According
to
this
perspective
there
is
a
dynamic
interrelationship among biological changes, psychological status and social
context playing distinct roles in chronic pain, disability and emotional
adjustment. The specific aim of this thesis was to test the applicability of
predictions based on a biopsychosocial model of chronic pain amongst a large
sample of Brazilian chronic pain patients.
The psychometric properties of a number of measures on cognitive and
affective domains of chronic pain were tested. The relationships between
socio-demographic, clinical and psychological factors within a Brazilian and
an Australian chronic pain population were examined and compared.
In this cross-sectional design study data were collected from 311
participants in each sample using questionnaires. A number of statistical
analyses mainly descriptive statistics, t test, analysis of variance, multiple
correlation, multiple hierarchical regression and logistic regression analyses
were used to test the validity and reliability of the measures and the
relationships between variables. All the analyses were conducted using the
SPSS for Windows version 14.0.
The results suggest that the Brazilian versions of the Roland and
Morris Disability Questionnaire, the Pain Self-Efficacy Questionnaire, the
DASS – Depression Scale, the PRSS – Catastrophising Scale and the Chronic
Pain Acceptance Questionnaire have generally sound psychometric properties
and may be used with other Brazilian chronic pain populations. The findings
vi
also revealed that in these populations, some socio-demographic factors
interact with clinical variables contributing to disability. Cognitions also
contributed to disability, emotional adjustment, pain intensity and work
status. In the Brazilian sample, educational level, pain site, and self-efficacy
contributed
to
disability;
catastrophising
was
the
only
predictor
of
depression; gender and self-efficacy contributed to pain severity; and age,
educational
level,
disability
and
self-efficacy
were
risk
factors
for
unemployment. Whilst in the Australian sample, pain severity, activity
engagement and self-efficacy contributed to disability; catastrophising, selfefficacy and pain willingness were predictors of depression; self-efficacy
contributed to pain severity, and age, educational level, pain site, and
depression were risk factors for unemployment.
These findings indicate that the Australian and the Brazilian sample
presented a number of similarities and only a few differences regarding the
contribution of psychosocial factors to chronic pain, disability and emotional
adjustment. This confirms the hypothesis that the relationship between these
factors would occur in a similar pattern in these two samples and in
accordance with biopsychosocial perspectives.
The results of these studies are in accordance with the pain literature
generally, which reaffirms that chronic pain is a multidimensional experience
mediated and moderated by similar psychosocial factors, even in different
cultures. From a clinical perspective these findings suggest that interventions
based on these concepts should be feasible in different populations.
This series of studies is one of the first to analyse the simultaneous
contribution of self-efficacy, acceptance and catastrophising to physical and
vii
emotional adjustment in different cultures. The findings suggest a number of
lines for future research and have a number of clinical and research
implications.
viii
Publications arising from this thesis
Peer reviewed papers/book chapters
Sardá, J. J Jr. Aceitação da dor crônica: novidade conceitual ou resgate de
um princípio
fundamental no
tratamento
de
doenças crônicas?
“Acceptance of chronic pain: conceptual novelty or returning to an old
concept in the treatment of chronic illness?” In: Gildo Angelotti (Org).
Terapia Cognitivo-Comportamental no Tratamento da Dor. São Paulo:
Casa do Psicólogo. (in press).
Sardá, J. J Jr.; Nicholas, M. K.; Pimenta, C. A. M.; Asghari, A. Pain related
self-efficacy beliefs in a Brazilian chronic pain patient sample: A
psychometric analysis. Stress and Health. (in press).
Sardá, J. J Jr.; Nicholas, M. K.; Pimenta, C. A. M.; Asghari, A. Psychometric
properties
of
the
DASS-
Depression
scale
among
a
Brazilian
population with chronic pain. Journal of Psychosomatic Research. (in
press).
Sardá, J. J. Jr.; Angelotti, G. Avaliação Psicológica da Dor. “Psychological
Assessment of Pain” In:
Joao Augusto
Bertuol Figueiro;
Gildo
Angelotti, Cibele A. Mattos Pimenta. (Org.). Dor e Saúde Mental. São
Paulo: Atheneu, 2004, p. 51-65.
Conference and seminar presentations
Sardá, J. J. Jr.; Nicholas, M. K.; Pimenta, C. A. M.; Asghari, A.; Corrêa, C. F.;
Oswaldo, J. Jr.; Hennmann, L.; Pereira, I.; Min, L. S. Validade e
fidedignidade do questionario Roland Morris de Incapacidade em uma
população de brasileiros com dor crônica. “Validity and reliability of the
RMDQ in a Brazilian population with chronic pain” In: 7º Congresso
Brasileiro de Dor, 2006, Gramado.
ix
Sardá, J. J. Jr.;
Nicholas, M. K.;
Pimenta, C. A. M.;
Asghari, A.
Psychological Assessment of Chronic Pain Patients: Available Measures
in Brazil. In: 11th World Congress on Pain, 2005, Sydney. Abstracts.
Seattle: IASP, 2005. v. 1. p.325.
Sardá, J. J. Jr. Perspectivas clínicas e em pesquisa no tratamento
psicológico de pacientes com dor. “ Research and clinical perspectives
in the treatment of chronic pain patients” In: VII Simposio Brasileiro e
Encontro Internacional sobre Dor, 2005, São Paulo. VII Simbidor,
2005. v. 1. p. 372-77.
x
Table of Contents
Page
Supervisor’s Certificate ...................................................................... ii
Candidate’s Certificate ........................................................................ iii
Acknowledgments .............................................................................. iv
Abstract ........................................................................................... vi
Publications arising from this thesis ..................................................... ix
Table of contents .............................................................................. xi
List of figures .................................................................................... xvi
List of tables ..................................................................................... xvi
Chapter 1: Introduction ................................................................. 1
1.1 Definition of Pain ......................................................................... 1
1.2 Epidemiology of Chronic Pain ................................................... 3
1.2.1 Summary of Findings ........................................................... 8
1.3 Pain Theories and Models .............................................................. 10
1.4. Disability .................................................................................... 18
1.4.1 Disability Measures .............................................................. 20
1.4.2 Comments .......................................................................... 25
Chapter 2: Psychosocial Factors Involved in Chronic Pain .............. 27
2.1 Cognitive Factors ........................................................................ 33
2.1.1 Coping Strategies ................................................................ 34
2.1.1.1 The Contribution of Coping Strategies to Adjustment
to Chronic Pain ................................................................. 37
2.1.2 Beliefs ................................................................................ 41
2.1.2.1 Self-efficacy Beliefs ........................................................... 45
2.1.2.1.1 The Contribution of Self-efficacy to Adjustment
to Chronic Pain .................................................................. 47
xi
2.1.2.1.2 Measures of Pain Self-efficacy Beliefs ................................ 49
2.1.2.1.3 Comments .................................................................... 52
2.1.2.2 Catastrophising ................................................................ 55
2.1.2.2.1 The Contribution of Catastrophising to Adjustment
to Chronic Pain .................................................................. 56
2.1.2.2.2 Catastrophising Measures ................................................ 60
2.1.2.2.3 Comments .................................................................... 64
2.2 Attitudes ..................................................................................... 68
2.2.1 Acceptance of Chronic Pain .................................................. 68
2.2.1.1 The contribution of Acceptance to Adjustment to
Chronic Pain .................................................................. 70
2.2.1.2 Acceptance Measures ....................................................... 75
2.2.1.3 Comments ...................................................................... 77
2.3 Affective Factors ......................................................................... 81
2.3.1 The Contribution of Depression to Disability Associated with
Chronic Pain ..................................................................... 81
2.3.2 Depression Measurement ................................................. 86
2.3.3 Comments ...................................................................... 91
2.4 Cultural Factors and Pain............................................................... 93
2.4.1 Contribution of Cultural Factors to Chronic Pain ...................... 93
2.4.2. Comments ...................................................................... 103
2.5 Psychological Assessment ........................................................... 105
2.5.1 Psychological Assessment Indications and Aims ................... 105
2.5.2 Psychological Assessment Methods ...................................... 107
2.6 Final comments .......................................................................... 112
Chapter 3: Study One: Psychometric Properties of Measures of
Disability, Pain Self-Efficacy Beliefs, Catastrophising, Acceptance and
Depression in a Brazilian Population with Chronic Pain
3.1 Introduction ............................................................................. 113
3.2 Method ..................................................................................... 117
3.2.1 Subjects ........................................................................... 117
3.2.2 Inclusion criteria ............................................................... 117
xii
3.2.3 Exclusion criteria ............................................................... 118
3.2.4 Procedure ......................................................................... 118
3.2.5 Measures ......................................................................... 119
3.3 Aims of study .............................................................................. 122
3.4 Statistical analyses ....................................................................... 122
3.5 Results ................................................................................
123
3.6 Discussion ................................................................................... 146
3.6.1 Psychometric properties of the RMDQ Brazilian version ........... 146
3.6.2 Psychometric properties of the PRSS – Catastrophising
Scale Brazilian version ........................................................ 149
3.6.3 Psychometric properties of the DASS – Depression Scale
Brazilian version ................................................................ 152
3.6.4 Psychometric properties of the Pain Self-Efficacy Questionnaire
PSEQ Brazilian version .............................................................. 155
3.6.5 Psychometric properties of the Chronic Pain
Acceptance Questionnaire - CPAQ Brazilian version .................. 159
3.6.6 Summary of discussion ....................................................... 165
Chapter 4: Study Two: The relative contributions of self-efficacy
beliefs, catastrophising and acceptance to disability and depression
in a Brazilian population with chronic pain
4.1 Introduction ................................................................................ 167
4.2 Method ...................................................................................... 170
4.2.1 Subjects ............................................................................ 170
4.2.2 Inclusion and exclusion criteria ............................................. 170
4.2.3 Procedure .......................................................................... 170
4.2.4 Measures ........................................................................... 170
4.3 Hypothesis ................................................................................. 171
4.4 Aims of study .............................................................................. 171
4.5 Statistical analyses ....................................................................... 172
4.6 Results ....................................................................................... 173
4.6.1 Summary of findings ........................................................... 187
4.7 Discussion ................................................................................... 189
xiii
4.7.1 Contribution of socio-demographic, clinical and psychological
variables to disability ................................................................ 189
4.7.1.1 Contribution of socio-demographic and clinical variables
to disability ............................................................................. 190
4.7.1.2 Contribution of psychological variables to disability .............. 191
4.7.2.1 Contribution of socio-demographic, clinical and psychological
variables to depression ............................................................ 196
4.7.2.2 Contribution of psychological variables to depression ........... 199
4.7.3 Contribution of socio-demographic, clinical and psychological
variables to pain intensity ........................................................ 204
4.7.3.1 Contribution of socio-demographic and clinical variables
to pain intensity ...................................................................... 204
4.7.3.2 Contribution of psychological variables to pain intensity ........ 205
4.7.4 Examining risk factors for work status .................................. 208
4.7.5 Summary of discussion and implications ................................ 215
Chapter
5:
Study
Three:
A
cross-cultural
comparison
of
the
contribution of cognitions to disability and depression: A comparison
between an Australian and a Brazilian sample with chronic pain.
5.1 Introduction ................................................................................ 217
5.2 Socio-demographic characteristics of Brazil and Australia ................. 219
5.2.1 Brazil ................................................................................ 219
5.2.2 Australia ........................................................................... 221
5.3 Method ...................................................................................... 225
5.3.1 Subjects ............................................................................ 225
5.3.2 Inclusion and exclusion criteria ............................................. 225
5.3.3 Procedure .......................................................................... 225
5.3.4 Measures ........................................................................... 226
5.4 Hypothesis ................................................................................. 226
5.5 Aims of study .............................................................................. 227
5.6 Statistical analyses ....................................................................... 227
5.7 Results
..................................................................................... 228
5.8 Discussion ................................................................................... 244
xiv
5.8.1 Variables contributing to disability in the Australian and
in the Brazilian sample ....................................................... 252
5.8.2 Variables contributing to depression in the Australian and
in the Brazilian sample ....................................................... 255
5.8.3 Variables contributing to pain intensity in the Australian and
in the Brazilian sample ....................................................... 256
5.8.4 Examining risk factors for work status in the Australian and
in the Brazilian sample ...................................................... 257
5.8.5 Summary of discussion ...................................................... 259
Chapter 6: General Discussion
6.1 General discussion ....................................................................... 260
6.2 Limitations and strengthens........................................................... 273
6.3 Conclusion................................................................................... 276
6.4 Further directions ......................................................................... 278
References ..................................................................................... 280
Appendices
Appendix I. List of institutions participating in the study ........................ 309
Appendix II. The consent form............................................................. 311
Appendix III. Ethic committee approvals............................................... 313
Appendix IV. Original measures and translations ................................... 323
Appendix V. Publications .................................................................... 338
xv
List of figures
Figure 1. Biopsychosocial Model of Pain ................................................ 13
Figure 2. Psychobiological Model of Chronic Pain .................................... 16
Figure 3. Overview of Problems Associated with Chronic Pain .................. 29
Figure 4. A Multistage model of cognition, disability and affect ............... 85
List of tables
Study One
Table 3.1 Socio-demographic characteristics of the study sample .......... 124
Table 3.2 Clinical characteristics of the study sample ........................... 126
Table 3.3 Descriptive statistics for all the measures ............................. 129
Table 3.4 Comparison between mean scores of the Brazilian sample
and the original questionnaire............................................. 130
Table 3.5 Internal consistency and split-half correlation of the measures . 131
Table 3.6 Item-scale correlation for the CPAQ ..................................... 133
Table 3.7 PCA of the CPAQ factors loading and communalities
for a 5 factor solution ......................................................... 135
Table 3.8 Means (SD) and internal consistency for a 4 factor solution...... 136
Table 3.9 PCA of the PSEQ factors loading and communalities for
a 1 factor solution ............................................................. 137
Table 3.10 PCA of the Catastrophising Scale factors loading
and communalities for a 2 factor solution .............................. 138
Table 3.11 Mean (SD) and internal consistency for a 2 factor solution ..... 139
Table 3.12 PCA of the Depression Scale with factors loading
and communalities for a 1 factor solution ............................. 140
Table 3.13 Comparison of mean score in questionnaires
by educational level .......................................................... 141
Tables 3.14 Comparison of mean scores on questionnaires
by working status .............................................................. 142
Table 3.15 Correlations between questionnaires, scales and CPAQ factors 144
xvi
Study Two
Table 4.1 Pearson correlations among socio-demographic, clinical
and psychological measures ................................................ 175
Table 4.2 Multiple hierarchical regression analysis predicting disability .... 178
Table 4.3 Multiple hierarchical regression analysis predicting depression .. 180
Table 4.3.a MHRA predicting depression from catastrophising factors ...... 182
Table 4.4 Multiple hierarchical regression analysis predicting
pain intensity ................................................................... 183
Table 4.5 Logistic regression analysis for work status (Brazilian sample) . 186
Study Three
Table 5.1 Socio-demographic and clinical characteristics of the
Australian sample ............................................................... 229
Table 5.2 Descriptive statistics for the Australian sample
in all the measures ............................................................... 231
Table 5.3 Comparison of scores on questionnaires by educational level ... 232
Table 5.3 Comparison of scores on questionnaires by educational level ... 233
Table 5.5 Pearson correlations among socio-demographic, clinical
and psychological measures ................................................ 234
Table 5.6 MHRA predicting disability (Australian sample) ....................... 237
Table 5.7 MHRA predicting depression (Australian sample) .................... 238
Table 5.8 MHRA predicting pain intensity (Australian sample) ................. 239
Table 5.9 Logistic regression analysis for work status (Australian sample) 242
Table 5.10 Socio-demographic and clinical characteristics of the Australian
and Brazilian sample .......................................................... 244
Table 5.11 Comparison between questionnaire means of the Brazilian
and Australian samples...................................................... 247
xvii
1. Introduction
The main purpose of this literature review is to: (I) describe the
biopsychosocial model of chronic pain, and (II) to explore some key
cognitive and affective aspects of pain.
This review also provides an assessment of a number of commonly
used psychological measures, which will provide a framework for the
development of a battery of measures to assess different aspects of pain
in a Brazilian and an Australian chronic pain population.
1.1 Definition of Pain
According to the International Association for the Study of Pain
(IASP)
definition,
“pain
is
an
unpleasant
sensory
and
emotional
experience associated with actual or potential tissue damage, or
described in terms of such damage” (Merskey and Bogduk 1994).
Although this definition is not totally satisfactory, there is a general
consensus
that
pain
is
a
multidimensional
phenomenon
and
its
relationship to tissue damage and suffering is variable.
There are several pain taxonomies, usually based on area or site,
as well as mechanism and duration. Time - based classification of pain
includes
acute,
acute
recurrent,
chronic,
chronic
progressive
and
laboratory-induced acute pain. According to Turk and Melzack (2001),
acute pain is typically referred to as pain with a relatively short duration
(hours, days or a few weeks, up to a maximum of 4 weeks). Pain that
persists from 4 to 12 weeks is often described as sub-acute pain. Acute
recurrent pain is characterised by the presence of acute pain interspersed
with periods without any pain. Pain that persists for a period longer than
3 months is described as chronic pain. Chronic progressive pain is
characterised by the evolution of pain intensity associated with a
progressive disease (e.g. Cancer). Laboratory-induced acute pain consists
of experimental induced pain (e.g. cold pressor task).
The IASP Subcommittee on Taxonomy established three time
categories for pain: less than one month, one to six months and over six
months. Although, there are a few differences in pain definition, for nonmalignant pain three months is the most convenient point of division
between acute and chronic pain (Merskey and Bogduk 1994).
This literature review will adopt the classification for chronic pain,
as pain that persists for a period longer than three months. This
definition is consistent with commonly-used epidemiology studies (Blyth
et al. 2001; Eriksen et al. 2003; Von Korff 1999).
Pain is the most common symptom and the leading reason given
for seeking health care (Gureje et al., 1998; Turk and Melzack, 2001). In
most acute disease it is an important warning signal and leads to a
diagnosis and subsequent treatment. However, in a significant number of
people acute pain evolves to chronic pain, which in most cases has no
cure or time limit. Recently, some have argued that it may be thought of
as disease entity in itself (Siddall and Cousins 2004). To illustrate the
magnitude of this problem epidemiological data will be presented.
2
1.2 Epidemiology of Chronic Pain
The prevalence of chronic pain has been found to vary among
different populations. In part, this is due to differences in definition and
research methods.
Using a definition of chronic pain as pain that has lasted longer
than three months, Von Korff et al. (1990) reported a prevalence of 45%
of persisting or recurrent pain in a sample of 1,016 adults randomly
select from a health service in Washington State. In this sample 8% of
the participants reported severe and persistent pain, whilst in 3.7% pain
was associated with disability. A study conducted in New Zealand (James
et al. 1991) in a community sample with 1,498 participants found that
over 80% of the adult population is affected by pain at some stage of
their life. However their definition of pain did not specify the criteria used
to establish the duration of the pain, nor severity and impact. Their
results also suggest heterogeneity of pain complaints, and the association
of some pain syndromes and age.
A survey conducted by Gureje et al. (1998) with 25,916
participants in fifteen countries in Asia, Africa, Americas and Europe,
used the definition of persistent pain as pain that is present most of the
time for a period of six months or more during the prior year. This group
found a persistent pain prevalence of 22% among patients using the
primary care system, with some variation among centres. In this study,
participants suffering from persistent pain were more likely to be female,
to have an anxiety or depression disorder, and to experience significant
3
activity limitation. In a review of published studies Von Korff et al. (1999)
described a prevalence of chronic pain in general populations ranging
from 7% to 40%. However, these authors emphasise that this wide range
is mainly due to the use of different pain definitions. Blyth et al. (2001)
reviewed fifteen studies and found a pain prevalence of 15%, ranging
from 2% to 40%.
A review conducted by Harstall and Ospina (2003) with thirteen
studies published between 1991 and 2002 found a chronic pain
prevalence range from 10.1% to 55.2%, with a higher pain prevalence
among females and a higher incidence of musculoskeletal pain. Among
these studies six used the IASP chronic pain definition (3 months), and
four used the definition of persistent pain (pain lasting longer than 6
months). Three studies adopted the American College of Rheumatology
(ACP) definition of chronic widespread pain, which is similar to the IASP
definition but includes the presence of pain in several different areas.
A recent survey conducted in 15 countries in Europe and Israel
with general population (n=49,394 participants) have found a 19%
prevalence of chronic pain, affecting quality of social and working life
(Breivik et al. 2006).
Using the IASP definition of persisting pain (pain that lasts for at
least 3 months in the last 6 months), in an Australian community sample
of 17,000 selected by a random-digit dialling, Blyth et al., (2001)
reported a chronic pain prevalence of 17.1% among males and 20%
among females. In this study chronic pain was associated with aging,
female gender, lower socioeconomic level and psychological distress. In
4
Denmark (Eriksen et al. 2003) found a similar chronic pain prevalence,
16% for men and 21% for women also associated with aging, lower
education and economic levels. Similar results were found in Spain in a
general population survey, with a 23.4% chronic pain prevalence, also
associated with aging and daily activities interference due to pain (Catala
et al. 2002). A 10.8% prevalence of chronic pain was reported in a
sample of 1.000 of Hong Kong’s Chinese adult population (Ng et al.
2002). A study conducted in Canada with a stratified random sample
(n=2,012),
using
a
definition
of
chronic
pain
as
continuous
or
intermittent pain present for at least six months, reported a prevalence of
29% of non-malignant chronic pain (Moulin et al. 2002).
Other studies with specific chronic pain syndromes or specific
groups (eg. elderly, children and indigenous population) have also
reported a high prevalence. A prospective longitudinal study in France
reported a prevalence of 7.8% of chronic neck and shoulder pain in men
and 14.8% among women, with a close association between psychosocial
factors and chronic pain (Cassou et al. 2002). This study investigated
only the working-age population and defined chronic pain as pain that
lasted longer than six months and considered some specific sites only.
A review on chronic back pain in adults in several countries
described a prevalence between 15-30% (Andersson 1999). A survey
conducted in Germany by Kohlmann (2003) found a prevalence of 16%
of musculoskeletal pain among the adult population. According to
Neumann and Buskila (2003), the prevalence of fibromyalgia in the
general population ranges from 0.5% to 5%. Two English surveys
5
reported variations in prevalence according to pain site. The first study,
(Aggarwal et al. 2003) with 2,504 subjects, found a 26% prevalence of
oro-facial pain, with a higher prevalence rate among those people in
lower socio-economic levels. The second survey, (Webb et al. 2003) had
a sample of 5,752 adults and found a prevalence of 14% of neck and
back chronic pain. Another cross-sectional study in the Dutch general
population found a prevalence of 26.9% for back pain, 20.9% for
shoulder pain and 20.6% for neck pain (Picavet and Schouten 2003).
Honeyman and Jacobs (1996) in a study with an aboriginal
population in Central Australia found a pain prevalence range from 30%
to 50%. They reported a higher pain tolerance among the participants
and no illness or pain behaviours that are commonly described in North
American and European studies were observed (e.g. limping, guarding
and facial expressions). Pain duration was difficult to evaluate due to
cultural aspects and language factors, but low-back pain was the most
common chronic pain reported, followed by neck pain.
Most pain prevalence studies have been done in United States,
Canada, Europe, Australia and New Zealand. It has been thought that
some types of pain would be associated with their Western society
lifestyle (e.g. low-back pain) (Andersson 1999; Honeyman and Jacobs
1996), however recent evidence has not supported this hypothesis.
Epidemiological data on pain prevalence from developing countries
are scarce. Sharma et al. (2003) reported a 23.09% pain prevalence in a
rural population of inpatients and outpatients that were referred to a
rehabilitation institution in India. Wang (2003) reviewed several studies
6
in Asia and found a prevalence of tension-type headache between 8.4%
and 12.7%. This result is in the lower range of headache prevalence
reported by International Headache Society (HIS) in Western countries
(15.6% to 25.7%). Volinn (1997) in an epidemiological study found an
18.5% low back pain prevalence rate in lower income countries (e.g.
India, Brazil, South Africa).
In Brazil, Pimenta (2001) conducted a study with a community
randomly selected sample (n=1,871) and found a 28.7% chronic pain
prevalence among children, 61.4% among adults, and in an elderly group
the prevalence was 51.4%. Overall the relationship between chronic pain
and gender, age, social class and level of education was not clear.
Children and adults complained of daily interference in their activities due
to pain. Among adults headaches were more frequent in women. Younger
women reported a higher incidence of pelvic-pain, and low-back pain was
associated with lower socio-economic classes. Data from a survey
conducted by Gureje et al. (1998) with a stratified random sample in
Brazil, reported a persistent pain prevalence of 31% among participants
using the primary health system. Another study conducted by Sardá et
al. (2003) with a convenience sample of 182 university students, found a
chronic pain prevalence of 53%. Low back pain and headache were the
most common symptoms and levels of anxiety and depression were
higher than in the general population. The results showed a higher
prevalence of chronic pain when compared to findings reported in the
international literature; however this study had several methodological
7
limitations and was not intended to be representative of the general
population.
1.2.1 Summary of Findings
The prevalence of chronic pain varies significantly among different
populations (i.e. countries and subgroups) from 10% to 50%, but a mean
prevalence of 15% is a well-supported estimation. The different findings
are likely to be related to variations in methodologies and definitions. It is
notable that most of these studies were conducted mainly in working-age
populations, thus there is still lack of information regarding chronic pain
in elderly, younger and specific populations (e.g. aborigines).
Several
studies
have
reported
an
association
between
psychological factors, demographic and economic variables and the
prevalence of chronic pain, suggesting that the experience and impact of
chronic pain involve many factors. Among socio-demographic variables,
gender (i.e. female) and lower social classes have been associated with a
higher prevalence of chronic pain. Regarding psychological factors, most
studies have found an association between variables such as depression
and anxiety, and higher levels of disability or unemployment.
Chronic pain has a high direct and indirect cost to the health
system as well as an economic impact for the whole community (i.e.
missing
working
days,
insurance
costs,
costs
of
treatment)
and
psychosocial impact (i.e. disability and emotional comorbidities), not to
8
mention the likely effects on the families of those with chronic pain (Blyth
et al. 2005; Turk 2002a).
There is evidence suggesting that chronic pain is a major health
problem in most societies. However, it is important to recognise that
current theoretical models of pain and most epidemiological findings have
emerged from higher income western societies. Whether these models
and epidemiological findings are applicable in developing (or low income)
countries and other cultures are largely unknown.
Given that psychological, functional and environmental interactions
seem important in understanding the impact of chronic pain, and taking
into
account
that
psychosocial
factors
may
be
responsive
to
interventions, it would seem worthwhile to investigate the applicability of
current models of chronic pain in the Brazilian population. Brazil
represents a country in transition from lower to higher income with wide
disparities. The common language spoken is Portuguese.
This investigation will require the development or adaptation of
English (language) psychological measures to assess the range of
dimensions covered by these models. If the relationship between
psychological variables and pain in the Brazilian chronic pain population is
found to be consistent with evidence from the more developed countries,
it would suggest that treatments found to be effective in these other
countries might also be applicable in Brazil.
In the next section a number of relevant pain theoretical models
will be described.
9
1.3 Pain Theories and Models
In this literature review a number of theoretical models about
chronic pain will be briefly described, but the main focus will be on the
biopsychosocial perspectives.
Current pain theories have evolved from earlier models (e.g. Sensory
and Pattern theories) to the Gate Control Theory (Melzack and Wall
1965) and to the Neuromatrix model (Loeser and Melzack 1999).
Some earlier models focused more on sensory components of pain
and viewed psychological aspects only as responses to pain. These
theoretical models tried to explain pain in terms of a stimulus-response
process. Broadly these uni-dimensional models understood pain as a
specific sensation directly related to specific pathways and the amount of
nociceptive input (Flor et al. 1990).
Although earlier sensory models contributed to the understanding
of pain phenomena, cumulative evidence and clinical observations (e.g.
phantom limb pain) collaborated to diminish the uni-dimensional pain
theories and forced the development of other theoretical models.
The later models attempt to address the limitations of the previous
models, combining new evidence of neurophysiological mechanisms with
psychological processes.
The Gate Control Theory (GCT) (Melzack and Wall 1965) provided
a theoretical basis for expanding the comprehension of pain beyond
merely
the
noxious
physiopathologic
stimuli,
components
the
of
sensorial
pain.
This
dimension
model
and
the
suggested
the
10
existence of ascending and descending processes modulated by the brain
and other elements of the central nervous system (Loeser and Melzack
1999). The GCT emphasised the role of the brain and the dorsal horn of
the spinal cord as active systems participating in the modulation of
noxious stimuli (Melzack 1996).
Probably the major contributions of the GCT have been to highlight
the key role of the central nervous system as an active component in
pain processes and response with excitatory and inhibitory roles, and the
participation
of
affective
and
cognitive
components
in
the
pain
phenomenon (Turk and Monarch, 2002). On the other hand, one of the
limitations of the GCT was that it did not explain how psychological
processes contributed to modulate pain. It is also important to realise
that the GCT intended to provide an account for acute pain where there is
a noxious input from the periphery, rather than chronic pain where no
peripheral input may be involved (Nicholas and Molloy 2002; Turk and
Monarch 2002).
Although subsequently neurophysiological research has revealed far
more about the working of the peripheral and central nervous systems
than was known in 1965 the GCT is regarded as the foundation of the
modern concepts of pain (Zimmermann 2005).
More recently the Neuromatrix model was developed aiming to
address the role of a range of factors on the modulation of inputs through
brain patterns. Loeser and Melzack (1999) proposed that afferent inputs
act on this neuromatrix and produce output patterns that lead to the
report of pain. This pattern generating mechanism (Neuromatrix) is
11
thought to be influenced by cultural factors, past experience and
personality
variables,
attentional
processes,
medullary
descending
inhibition, autonomic, endocrine and immune changes, central-nervous
system plasticity, pathogenic inputs, viscerosensory and somatosensory
inputs.
The Neuromatrix model hypothesises that the output of the
neuromatrix, not the input, is able to generate neurosignature patterns
for pain and even act in the absence of inputs. This may explain some
types of pain that are characterised by the absence of a discernible
stimulus or a lack of relation between pathology and pain intensity
(Melzack, 1996; Loeser and Melzack, 1999). This model proposes a range
of possibilities for pain modulation, but at a more central level.
This model proposes that nociceptive stimulation may produce
neurological structural and functional changes, which explain why some
individuals
experience
a
gradual
pain
increase
after
an
initial
sensitisation.
A number of studies have provided support for the Neuromatrix
model describing neuroplasticity and sensitisation properties of the
peripheral and nervous system (Siddall and Cousins 1998; Siddall and
Cousins 2004). These two processes have a central role in explaining
physiological and psychological changes in chronic pain.
The GCT and Neuromatrix theories have provided a framework for
understanding the role of psychological and physiological factors in pain.
However, both models have limitations regarding how cognitive and
12
emotional
factors
might
mediate/moderate
physiological
changes
associated with chronic pain.
Parallel to the development of these primarily neurophysiological
pain theories other researchers have worked on concepts of illness and
factors
involved
biopsychosocial
in
it
model
(e.g.
Engel
proposed
by
1977,
Mechanic,
1962).
The
Engel
(1977)
suggested
that
symptoms should be conceptualised as a result of dynamic interactions
between psychological, social and pathophysiological variables. Engels’
model was an attempt to overcome the reductionism and limitations of
the
traditional
biomedical
approach,
which
is
centred
on
pathophysiological factors only.
A number of researchers (Flor et al. 1990; Loeser 1980; Turk et al.
1983; Waddell 1998) have adapted the original biopsychosocial model to
chronic pain.
Social Environment
Illness Behaviour
Suffering
Pain Perception
Nociception
Figure 1. Biopsychosocial Model of Pain (Waddell 1998).
13
The premise of this biopsychosocial model is that nociceptive
components
are
one
contributor
to
pain
experience,
interacting
continuously with psychological and social factors. Based on this
assumption, it is proposed that nociception will influence pain perception,
suffering, illness and pain behaviour but these domains will be mediated
and moderated1 by psychological and environmental factors. These
relationships are not uni-directional but multi-determinate and dynamic.
Although Waddell (1998) did not intend to describe all the factors
participating in chronic pain, his model illustrates the overlap and the
dynamic of variables participating in the experience of pain.
The biopsychosocial perspectives propose the existence of a
dynamic
interrelationship
among
biological
changes,
psychological
processes and social context playing distinct roles in pain. According to
this perspective “Biological factors may initiate, maintain, and modulate
physical perturbations; psychological factors influence the appraisal and
perception of internal physiological signs, and social factors shape the
behavioural response of patients to the perception of their physical
perturbations” (Turk, 1996, p.6).
Although conceptually important the early biopsychosocial models
of pain lacked evidence on how psychosocial factors interact with
biological aspects. However evidence regarding these interactions has
built up during the last 20 years.
1
Although the term mediator and moderator are often used interchangeably these terms are distinct
and should be clarified to avoid further misunderstandings. A moderator variable affects the
relationship between two variables in a way that the impact of the independent variable on the
dependent variable varies according to the value of the moderator (i.e. pain intensity - educational
level - disability). On the other hand, with a mediator variable the relationship between a
independent variable and a dependent variable is influenced through the mediator variable (i.e. pain
intensity – self-efficacy – disability) (Holmbeck 1997).
14
It has been found that psychological factors can promote changes
in the endocrine and the autonomic nervous system which may
predispose the onset of a disease (Bandura et al. 1987; Flor et al. 1985).
Other findings suggest that a number of behavioural aspects (i.e. pain
behaviours) may reduce physical activity and consequently muscle
flexibility, muscle tone, strength and physical endurance, contributing to
physical deconditioning (Flor et al. 1990). Bandura’s (1985) findings also
indicated that cognitive factors may have a direct effect on physiological
parameters, associated more directly with the production or exacerbation
of nociception. Cognitive interpretation and affective arousal may directly
affect physiology by increasing sympathetic nervous system arousal,
production of endogenous opioids (i.e. endorphins) (Bandura et al.,
1987), and elevating the levels of muscle tension (Flor et al. 1992).
Research conducted by Turk (1996) and Edwards et al. (2001a;
2001b) has shown that race and ethnicity may also influence pain
perception and response to it. Their findings support the biopsychosocial
perspective and help to explain how pain experience is shaped by
interactions among biological, psychological and social variables.
Other researchers (e.g. Bates, 1987) have included cultural and
social components of the pain experience in their biopsychosocial model.
Bates proposed that "there is evidence that social learning is instrumental
in the development of meanings for and attitudes toward pain. Learned
values and attitudes affect one's attention to painful stimuli and one's
memories of prior pain experiences… Therefore, it is likely that cultural
group experiences influence the physiological processes responsible for
15
pain threshold and perception of pain severity, as well as pain response"
(Bates, 1987, p. 48). This biocultural perspective of pain suggests that
social comparison and social learning processes within ethnic-cultural
group situations influence attitudes toward pain, attention to pain stimuli
or sensation and thus cognitive control. Prior pain experiences also
participate in this process, moderating the descending inhibitory control
(Bates 1987; Edwards et al. 2001a)
Recent formulations of the biopsychosocial model of chronic pain (Flor
and Hermann 2004) have described in more detail, and provided evidence
about, how the factors presented in earlier biopsychosocial models might
work in terms of mechanisms.
Eliciting stimuli
•
Predisposing factors
• Genetic
determination
• Learning
• Occupational factors
Aversive external / internal stimuli
Psychophysiological
response stereotypy
e.g. symptom specific EMG
increase s
Pain responses
Maintaining
processes
• Subjective-verbal
• Behavioural-motor
• Physiological-organic
• Operant
conditioning
• Responden t
conditioning
Eliciting responses
• Lack of coping skills
• Inadequate perception and interpretation of physiological
processes and bodily symptoms
• Anticipation of pain
• Memory of pain
• Lack of self-efficacy
Figure 2. Psychobiological model of chronic pain (Flor and Hermann, 2004).
16
Broadly this model outlines that external or internal eliciting stimuli
could trigger psychophysiological responses, which are influenced by
predispositional
factors
and
eliciting
responses.
These
psychophysiological responses will lead to pain responses, which will
influence and be influenced by maintaining processes. Maintaining
processes also influence eliciting responses.
The biopsychosocial perspective of chronic pain has made a
number of contributions to the comprehension of pain phenomena. First,
these
models
have
provided
a
way
of
integrating
evidence
of
physiological changes and psychosocial processes and the dynamic
interaction of these two aspects. Second, these perspectives have
provided an alternative to more biological and reductionist explanations.
Third, these models also provided the basis for interventions that may
address multiple targets rather than just nociceptive processes.
In the next section, the concept of disability in chronic pain will be
explored.
17
1.4. Disability
Chronic pain can have an enormous impact on ability to function.
However, this is not universal. While some people become severely or
moderately disabled, others seem to adjust reasonably well to chronic
pain. Because chronic pain is not synonymous with disability, and there is
a low association between impairment and disability, it is important to
identify other factors that promote adaptive physical and psychological
functioning (Jensen et al. 1992; Turk and Monarch 2002).
The
term
disability
has
had
varying
definitions.
The
conceptualisation of disability based on a biopsychosocial model is
adopted by the World Health Organisation (World Health Organization
2002), and includes the role of health conditions (disease, disorders and
injuries) and external factors (environmental and personal factors) in
shaping disability.
According to the International Classification of Functioning - ICF
(World Health Organization 2002), disability is defined as the lack
(resulting from an impairment) of ability to perform an activity in the
manner or within the range considered normal for a human being. To
better understand this concept, two other major concepts are central to
understand disability; these are impairment and handicap.
Impairment is conceptualised as problems in body function or
structure such as a significant deviation or loss. Handicap is defined as an
individual disadvantage resulting from impairment or disabilities that limit
a person’s normal roles.
18
Although the WHO’s definition of disability is well accepted, and the
ICF 2002 version emphasises more the role of environmental and
personal factors in disability than the 1980 document, it still relies on a
scheme of causal relations, with physical damage or impairment, leading
to disability and handicap.
Main et al. (2005) have described different types of disability
model. Some focus more on biological features, others on occupational
aspects, or societal perspectives. In the chronic pain context as well as
other chronic diseases, disability seems to be intrinsically related to
psychosocial factors rather than only with the biological (Waddell 2003).
Robinson (2001) defines disability as an inability to carry out tasks in any
important domain of life due to a medical condition; including mental
disorders, such as depression. Robinson’s use of the term disability
implicates inability, incapacity or restricted function not only those
caused by somatic factors.
Pain and disability may be related to each other, but it is clear
there is no one to one relationship between them. Frequently clinical
improvements and decrease in pain may lead to small or unnoticeable
changes in disability and quality of life (Kovacs et al. 2004). Although
pain is influenced by biological factors and there is evidence of a
relationship between pain intensity and disability, disability seems to be
more related to and mediated by psychosocial factors (Asghari and
Nicholas 2001; Kovacs et al. 2004; Main et al. 2005).
Based on these perspectives, this thesis will be guided by the WHO
(2002) concept, which defines disability as the lack (resulting from
19
impairment) of ability to perform an activity in the manner or within the
range considered normal for a human being. However it will be
complemented by Robinson’s (2001) definition of disability, which takes
into account that an inability to carry out tasks due to an impairment
could be occur due to a medical or psychological condition.
This view is in accordance with recent evidence described above,
which examined the role of psychosocial factors in disability. Further
evidence will be described during this thesis.
Altogether there is evidence that a number of psychosocial factors
may contribute to disability. Thus, psychological assessment of the
factors involved in disability is an essential issue in treatment and
research.
In the next section a number of disability measures will be
described.
1.4.1 Disability Measures
Waddell (1998) pointed out that clinical assessment of disability
usually depends on the patient’s own report. Frequently, clinical interview
and a clinical functional capacity evaluation provide a reliable assessment
of daily activities disability, however these assessment methods are often
complemented with self-reports.
Disability questionnaires can be useful tools. They are more
consistent and reliable than interviews, due to the invariability of the
presenting questions and they are also a quick and efficient way to collect
20
information. Data provided by questionnaires also can be compared with
other data, providing a more precise analysis. Furthermore, they are
essential to research. On the other hand, reliability, validity and
responsiveness of disability questionnaires must be demonstrated.
Among several measures, some of the most frequently used
disability questionnaires in the pain field are the Sickness Impact Profile,
the Roland and Morris Disability Questionnaire, the Oswestry Low-Back
Pain Disability Questionnaire, the Medical Outcome Study 36 Short-Form
Health Survey (Battié and May 2001; Robinson 2001).
The Sickness Impact Profile – SIP (Bergner et al. 1981) was one of
the first self-report measures developed to assess the impact of health
problems in physical and psychological disability. It is a behavioural
based measure of health status, has 136 items and assesses 12 areas of
functioning (functional problems in ambulation, mobility, body care and
movement,
social
interaction,
communication,
alertness
emotional
behaviour as well as problems in sleeping, eating, working, home
management and recreation), yielding 3 scales. The SIP is a reliable and
valid measure, with reasonable responsiveness properties, but some
items do not refer to pain problems, which may decrease its validity,
reliability and sensitivity when compared to other chronic pain disability
measures (Jensen et al. 1992; McDowell and Newell 1996). Another main
disadvantage of this questionnaire is its length and complex scoring
procedure; it takes 20 to 30 minutes to administer. These concerns led to
the development of other measures (e.g. RMDQ).
21
The Roland and Morris Disability Questionnaire - RMDQ (Roland
and Morris 1983) was initially developed with items from the SIP to
measure self-rated physical disability in back pain patients. It has 24
items scored 0 or 1 (yes and no) and the total score varies from 0
(suggesting no disability) to 24 (severe disability). The RMDQ is a simple
measure, usually takes 5 minutes and is easy to calculate and analyse.
Several studies have described the strength of the RMDQ’s
psychometric properties compared with other measures, specially its
validity,
reliability
and
responsiveness
as
a
measure
of
physical
dysfunction in chronic pain patients (Lurie 2000; Robinson 2001; Roland
and Fairbank 2000; Stroud et al. 2004). RMDQ correlates well with other
disability measures in physical function, such as the SF 36, SIP and
Oswestry Questionnaire (Donald et al. 1995; Jensen et al. 1992; Turner
et al. 2003).
The RMDQ has been validated in 12 languages and adapted to
other chronic pain populations with good results (Roland and Fairbank
2000). A study conducted by Nusbain et al. (2001) described satisfactory
reliability and validity of a Brazilian translation of this measure. A study
conducted by Donald et al. (1995) with a modified version of the RMDQ
for
sciatica
patients
showed
nearly
equivalent
effect
sizes
and
responsiveness when compared with the SF-36. Asghari and Nicholas
(2001) also reported adequate psychometric properties for the RMDQ for
chronic pain patients in general in an Australian sample. In this study
these authors changed the term “back” to “pain” in all items, and item 13
was changed to “I am in pain almost all the time”. Jensen et al. (1992)
22
have reported the same adaptation with good results in a North American
sample.
When compared with the Oswestry Disability Questionnaire, the
RMDQ seems to be more sensitive to detect changes in disability in
patients with minor or moderate disability, while the Oswestry Disability
Questionnaire appears to be more suitable to patients with severe
disabilities. Turner et al. (2003) reported that in patients involved in
worker’s compensation the RMDQ showed much more responsiveness to
change and a greater ability to discriminate patients who were working
from those who were not than the SF-12 and SF-36. Similar findings
have been reported by Grotle et al. (2005).
The Oswestry Low -Back Pain Disability Questionnaire (Fairbank et
al. 1980) was also developed to assess disability in back pain patients.
This questionnaire has 10 items; responses vary from 0 to 5, which
indicate different levels of disability regarding daily activities. It takes less
than 5 minutes to respond and it is easy to score. Scoring consists of
summing the points in each item, total scores will vary from 0 to 50,
which is multiplied by two and results are in percentage (Battié and May
2001; Fairbank et al. 1980). The Oswestry Questionnaire has shown
moderate
correlation
with
other
measures
(i.e.
the
McGill
Pain
Questionnaire, the RMDQ and the SF-36) and adequate validity and
reliability (Battié and May 2001; Roland and Fairbank 2000). However,
similarly to the RMDQ, the Oswestry Questionnaire only assesses physical
disability.
23
The Medical Outcome Study 36 Short-Form Health Survey (SF-36)
(Ware and Sherbourne 1992) has been developed as a generic measure
to assess health related quality of life. It has eight scales: physical
functioning, role limitations due to physical problems, bodily pain, general
health, social functioning, limitation due to emotional problems, vitality
and mental health perceptions. The first four scales assess physical
health and the last assess mental health. The health concepts from which
the scales were developed were selected from forty concepts included in
the Medical Outcomes Study (Ware and Sherbourne 1992). The SF-36 is
a 5 point rating scale; each domain is scored from 0 to 100, indicating
poor and optimal health respectively. It takes approximately 10 minutes
to be completed and it is available in a paper and in a computer version.
Responsiveness,
internal
consistency,
construct
validity
and
discriminative ability of the SF-36 has been reported by several studies,
and its psychometric properties are equal or better than other health
related quality of life measures (Bronfort and Bouter 1999; McDowell and
Newell 1996; Ware 2000). According to Ware (2000) the physical
functioning and the mental health scales are the best all round measures
in this area. However in some populations this measure has shown some
problems with sensitivity to change (e.g. more disabled patients) (Ruta et
al. 1998; Turner et al. 2003). Another issue is that when compared with
the RMDQ and the Oswestry Questionnaire, the SF-36 scoring procedure
is more complex.
Despite these minor problems, the SF-36 has been successfully
validated in several populations, including Brazil (Ciconelli et al. 1998). It
24
has also been used in other diseases and health conditions including
arthritis and back pain with good results (Ware, 2000).
1.4.2 Comments
As noted, in a number of people chronic pain can lead to disability.
However, disability is not only a function of physiological aspects and
seems to be mediated/moderated by psychosocial factors.
Disability self-reports are reliable methods and have been used
frequently with chronic pain patients.
All
measures
psychometrically
of
sound.
disability
described
Furthermore,
a
in
number
this
of
review
studies
are
have
compared disability measures and reported that in most cases these
measures have a moderate to high correlation, although each measure
has its strengths and weaknesses (Donald et al. 1995; McDowell and
Newell 1996; Turner et al. 2003). Thus, the selection of a measure
depends on its psychometric properties and on the purpose of the
assessment (Battié and May 2001).
In relation to their content, while the Oswestry and the RMDQ are
more specific to some pain conditions, the SIP and the SF-36 are
considered generic measures. The main advantages of generic measures
are the possibility of comparing disability scores among different groups
of patients and being able to assess different spheres of disability.
However, there are also a number of studies reporting good results with
25
the adaptation of specific measures to more generic pain conditions
(Asghari and Nicholas 2001).
Regarding scoring, the RMDQ and the Oswestry Questionnaire are
less time consuming and easier to score than the others.
Based on a number of findings, the Roland Morris Disability
Questionnaire
appears
to
have some advantages
over the
other
measures of disability. It is a specific back pain disability measure
successfully adapted to general chronic pain; it has been found to be
more sensitive to detect changes in patients with all levels of disability
when compared to other disability measures. It is less time consuming
and easier to score than all the other measures, except for the Oswestry,
and it has a prior validation to the Brazilian population. Furthermore, the
concept of disability as measured by the RMDQ is in accordance with
WHO concept, focusing on the ability to perform an activity in the manner
or within the range considered normal for a human being.
The RMDQ modified version (Asghari and Nicholas 2001) has also
been used in the Pain Management and Research Centre – RNSH, which
will permit comparisons between the studied populations, thus it is the
chosen measure to assess disability in this study.
In the next chapter evidence about the role of psychological,
social and cultural factors
participating in physical disability and
emotional adjustment associated with chronic pain will be presented.
26
2. Psychosocial Factors Involved in Chronic Pain
It has been recognised that psychosocial factors may shape the
individual’s pain experience, influencing the degree to which pain is
experienced, responses to it, and the degree of interference caused by
pain (Linton 2000; Pincus et al. 2002; Skevington 1995; Turk and Okifuji
2002). On the other hand, most evidence is against psychological factors
causing chronic pain (Gamsa 1994; Turk and Monarch 2002).
Keefe et al. (1990), among others (e.g. Linton, 2000), described a
number of factors likely to be involved in the transition from acute to
chronic pain. Specifically, Keefe et al. proposed that the acute pain phase
is characterised by a focus on somatic symptoms, often a decrease in
activities, reliance on medication and beliefs that pain is controllable
through medication, seeking professional help, use of passive coping
strategies, presence of anxiety and autonomic arousal symptoms. This
phase is followed by a pre-chronic phase lasting from 2 to 6 months,
which may be characterised by alternating increasing and decreasing
activity, withdrawal from reliance on medication, reduced contact with
health professionals, working or trying to work, recognising that
medication is not always effective, alternating active and passive coping,
denying of depression, focus on physical symptoms, pain with varying
intensity, and physiological responses similar to the acute pain phase. In
Keefe et al.’s model, a chronic pain stage begins after about 6 months,
when there is less likelihood of finding an easy solution to organic
pathology, or when pathology is diagnosed but may not be possible to
27
treat. At this stage activities usually decrease, a tendency to go from one
doctor to another increases, dependence on narcotics may occur, working
difficulties and insurance compensation factors may arise. Pain may now
be believed to be uncontrollable, depression may be present, passive
coping is a common pattern, usually there is a strong preoccupation with
bodily complaints, pain is often constant and may be associated with
muscular spasm, and in general muscle strength and endurance have
decreased.
There is increasing evidence supporting much of what Keefe et al.
(1990) outlined. In particular, there is evidence that as pain becomes
chronic a number of cognitive, psychological and behavioural symptoms
and changes become more apparent. Negative mood may arise, passive
coping strategies (e.g. resting, avoiding activities that might aggravate
pain) are usually predominant, low self-efficacy beliefs and high levels of
catastrophising may be present, among other signs of psychosocial
maladjustment (e.g. Linton, 2000; Keefe et al., 2004). It has become
clear that psychosocial factors can be a consequence of chronic pain or
play a role as maintenance or mediating factors (Linton and Skevington
1999; Turk 2002b; Williams 2001).
Turk (1996) described that psychological and social factors may act
indirectly on pain and disability by reducing physical activity, and
consequently muscle flexibility, muscle tone, strength and physical
endurance.
Cognitive
factors
may
also
have
a
direct
effect
on
physiological parameters, associated more directly with the production or
exacerbation of nociception. Cognitive interpretation and affective arousal
28
may directly affect physiology by increasing sympathetic nervous system
arousal, production of endogenous opioids (i.e. endorphins) and elevating
levels of muscle tension. Altogether, these psychosocial factors seem to
contribute to disability.
Nicholas (1996) outlined a number of possible interrelationships
among biopsychosocial factors, especially in those presenting to pain
clinics.
R EDUC ED
AC TIVIT Y
PH YSIC AL
DET ER IO RAT IO N
(e g. m usc le w asting,
jo int s tiffne ss)
UN H EL PFU L
BEL IEFS &
THO U GH TS
C HR ON IC
PA IN
R EPEA TE D
TREA TM E NT
FAIL U R ES
LO N G-T ER M
US E OF m ultiple DR UG S
FEEL IN GS O F
DEP RES SIO N ,
H ELP LES SN ESS,
IR RITA BILITY
EXC ESS IVE
SU FFER IN G
SIDE EFFE CT S
(e g. s tom ach pro blem s
lethargy, co nstipa tion )
LO SS O F J OB , FIN AN C IAL
DIFFIC UL TIE S, FA M ILY
ST RE SS
Figure 3. Overview of problems associated with chronic pain (Nicholas 1996).
This clinical model describes in a very comprehensive way the
dynamic interaction among several physiological aspects of pain and
emotional, cognitive and behavioural factors. According to this model,
reduction of activities and physical deterioration may affect mood (e.g.
29
depression) and cognitions may mediate the relationship between
behavioural
and
emotional
variables
and
vice-versa.
Feelings
of
depression and irritability among other factors may also contribute to
reducing activity, treatment failures and social difficulties. Emotions
related to stress and social aspects, and physical deterioration may
enhance suffering. On the other hand, chronic pain per se may cause or
lead
to
behavioural,
cognitive
and
psychosocial
changes.
Other
interactions as illustrated by the single and double arrows also occur, not
only the ones described above (Nicholas 1996).
However, while many of those people referred to pain clinics
present with this picture, it is also clear that not everyone in the
community with chronic pain will present these features. For example,
Blyth et al. (2001) found that at least 40% of those with chronic pain
reported almost no interference in their daily lives.
In an attempt to explain why some become disabled but not
others, Turk (2002b) proposed a diathesis-stress model to explain the
relationship between trauma and disability. According to this model the
impact of a trauma or physical event may depend on predispositional
characteristics or traits (e.g. neuroticism). These predispositions are
likely to contribute to disability in people that interpret their symptoms in
unhelpful ways and that tend to have patterns of response that include
anxiety, depression, catastrophic thoughts, fear-avoidance, low-self
efficacy
and
neuroticism.
These
factors
appear
to
participate
as
vulnerability factors, which mediate disability.
30
There is also substantial evidence that psychosocial factors play an
important role in transition from acute to chronic pain, in the onset and
maintenance of chronic pain, in maladjustment to chronic pain, in
disability and in psychological dysfunction.
Linton’s (2000) review found that psychological factors are linked
to the transition from acute to chronic pain and generally have more
impact than clinical factors (e.g. pain intensity, pain site). Linton found
that the main psychological factors were: attitudes, cognitive style,
catastrophising, fear-avoidance, depression, anxiety, distress, passive
coping, and self-perceived poor health. Altogether Linton’s findings
suggest that psychological factors are important predictors of the risk for
developing chronic pain and disability.
Pincus et al., (2002) found that among several psychological
factors distress and depression are implicated in the transition to chronic
pain. This finding confirmed some of Linton’s findings, reinforcing the role
of some psychological factors as risk factors for pain chronicity and
disability. Although these findings are related to back and neck pain, as
they are psychological and social factors there is no obvious reason why
the can not be generalised to other chronic pain syndromes and sites.
A more recent review (Keefe et al. 2004) highlighted that among
several
psychological
factors
recent
research
suggests
that
catastrophising, pain related anxiety and fear and helplessness may
increase pain, distress and physical disability, while self-efficacy, coping
strategies, readiness to change and acceptance may decrease pain,
distress and disability.
31
In summary, these reviews of studies examining the possible role
of psychological factors in the transition from acute to chronic pain have
highlighted a number of contributors
to
disability and emotional
maladjustment associated with chronic pain.
As part of this literature review, the specific role of a number of
psychosocial factors in physical disability and adjustment to chronic pain
will be examined. The role of some cognitive factors (i.e. beliefs and
attitudes) will be described, especially self-efficacy, catastrophising and
acceptance. The role of depression will also be examined. Finally, this
section will examine the role of cultural factors in chronic pain and the
issues related to the assessment of psychosocial factors.
32
2.1 Cognitive Factors
Biopsychosocial perspectives suggest that a person's cognition
about the consequences of an event and ability to respond to it, may
have direct and indirect effects on functioning (Flor et al. 1990; Hunt and
Ellis 1999).
Cognitive processes may be defined as mental processes such as
perception, memory, language, concept and representation formation,
thoughts, appraisal, beliefs, problem solving. But there are other
definitions according to experimental cognitive psychology and cognitive
social psychology (Brewin 1988; Hunt and Ellis 1999).
Flor et al. (1992) argued that “independent of a medical diagnosis
or extent of physical damage, personal evaluations of pain and one’s
ability to cope with it are pivotal in determining how disabled a person
becomes or remains” (p. 63). Several studies have suggested that
changes in maladaptive coping, beliefs and appraisals can contribute to
decreased suffering, disability and improved functioning (Flor et al. 1990;
Nicholas 1996; Turk and Monarch 2002).
In this section some cognitive processes relevant to chronic pain
will be described: namely coping, beliefs and attitudes.
33
2.1.1 Coping Strategies
Chronic pain and disability can be considered stressors, which in
turn mobilise coping strategies. It is generally accepted that coping
strategies may act as vulnerability factors and as a mediator of
adjustment in a wide range of physical and psychological disorders and
events (Brewin 1988; Elliott and Eisdorfer 1982; Flor et al. 1990).
Coping may be defined as the use of behavioural and cognitive
efforts or purposeful strategies to manage stressful demands that are
appraised as taxing or exceeding the resources of a person (Lazarus and
Folkman 1984). Coping with chronic pain, can be described as efforts to
tolerate, minimise or reduce pain (Robinson et al. 1997).
Lazarus and Folkman (1984) conceptualised coping as a process
composed of appraisals, responses and reappraisals. Cognitive appraisal
and coping are critical processes that mediate the person-environment
relationship. Cognitive appraisal may be defined as, “an evaluative
process that determines why and to what extent a particular transaction
or series of transactions between the person and the environment is
stressful. Coping is the process through which the individual manages the
demands of a person-environment relationship, that is appraised as
stressful and the emotions they generate” (Lazarus and Folkman, 1984,
p.19).
Lazarus and Folkman (1984) classify cognitive appraisals into
primary and secondary appraisals. Primary appraisal consists mainly of
giving a meaning to a situation that could be classified in three types:
34
irrelevant, benign-positive and stressful. Secondary appraisal regards the
evaluation of what needs to be done, which coping resources are
available and possible consequences. A third type of appraisal is
reappraisal, and consists of changes in appraisal based on new
information acquired.
Since the early seventies the role of appraisal in coping and stress
has been widely studied. Lazarus and Folkman (1984) and Bennett and
Holmes
(1975)
among
others,
have
demonstrated
that
cognitive
appraisal processes affect stress responses and that appraisal is a strong
predictor of chosen coping responses and how people react emotionally.
There are a number of different constructs of coping (e.g. emotion
and problem focused, active and passive, behavioural and cognitive) and
consequently several different measures of coping.
Problem-focused and emotion-focused consist of strategies that
focus on solving the situation itself or the emotion associated with it,
respectively (Lazarus and Folkman 1984). Research based on this
conceptual framework
has
shown
that problem-focused
coping
is
associated with lower levels of psychological distress, while emotionfocused strategies are more commonly related to poor adjustment
(Lazarus 1993; Robinson et al. 1997).
Active coping may be defined as strategies used to attempt to
control
or
function
despite
pain.
Passive
coping
strategies
are
characterised by relinquishing control of pain to others (Brown and
Nicassio 1987). One of the key issues in this model is whether the patient
is relying on internal or external resources to control pain.
35
Behavioural coping strategies consist of actions, behaviours or
statements in an effort to deal with chronic pain. Cognitive strategies
generally consist of thoughts and emotional oriented strategies (Jensen
et al. 1995). Although behavioural strategies appear to be important,
Jensen et al. (2003) suggested that cognitive strategies play a more
important role in adjustment than behavioural strategies.
Illness-focused strategies may be described as efforts to minimise
or control the illness effects (e.g. resting), wellness-focused coping
strategies consist of activities that supposedly will promote well being
(e.g. exercise) (Jensen et al. 1995).
Attentional and avoidance pain strategies could be described as
another coping conceptual framework. Attentional strategies may include
ways of distracting attention from a given situation or object, while
avoidance involves diverting the focus from the problem (Holmes and
Stevenson 1990). These authors’ findings suggest that chronic pain
patients who use attentional coping strategies appear to be less
depressed and anxious than patients who use avoidance strategies.
Catastrophising is another cognitive construct that has initially
been defined as a coping strategy by some authors (Keefe et al., 1989).
However, more recently it has been thought of as a maladaptive
cognitive response (Turner et al., 2003). The different views on
catastrophising have generated some controversy (Jensen et al. 1991b)
and will be addressed later.
Although the role of coping seems to be important in adjustment to
chronic pain, the overlap of constructs makes it difficult to establish a
36
consensus on which types of coping strategies are more efficient and for
what type of patient they work (DeGood and Tait 2001).
2.1.1.1 The Contribution of Coping Strategies to Adjustment to
Chronic Pain
Coping strategies are hypothesised to alter perception of pain,
ability to manage it and to continue daily activities. There is evidence
that coping strategies can have an impact on function and adjustment to
chronic pain and that certain types of coping are related to different
outcomes (Jensen et al. 2003; Jensen et al. 1991b; Nicholas et al. 1991;
Romano et al. 2003).
Although coping is recognised as an important factor in patients’
adjustment to chronic pain several studies have reported varying results.
Strategies such as positive self-statements, ignoring pain and increased
physical activities have been associated with better psychological status
(Jensen and Karoly 1991; Jensen et al. 1991b; Keefe and Williams 1990).
Patients who use relaxation techniques also show decreases in pain
intensity, psychological distress and functional disability when compared
to
controls
reinterpreting
(Flor
pain
and
Turk
1988).
and
reinterpreting
Coping
pain
self-statements
sensations
have
and
been
associated with greater perceived control over pain than other strategies
(Haythornthwaite et al. 1998). On the other hand, ignoring pain,
diverting attention, praying and hoping, resting and guarding have been
associated with worse functioning and outcomes (Haythornthwaite et al.
37
1998; Jensen and Karoly 1991; Jensen et al. 1991b; McCracken and
Eccleston 2003; Romano et al. 2003).
DeGood and Tait (2001) reported that reinterpreting pain has been
found to be efficacious to manage chronic pain, but in addition the results
or benefits of other coping strategies such as diverting attention, coping
self-statements, ignoring pain, praying and increasing activity have not
been established and need further research. Furthermore, these authors
have argued that different coping strategies may produce different
outcomes depending on other moderating variables (e.g. pain intensity,
age), under different groups, cultures and conditions, depending on the
studyies’ methodologies and on measurement.
In general, studies have reported that active coping has been
associated with enhanced activity level and better psychological and
physical functioning, while passive coping has been associated with
maladaptive outcomes (Blyth et al. 2005; Brown and Nicassio 1987;
Keefe and Williams 1990; Snow-Turek et al. 1996). Jensen et al. (1995)
found that illness-focused coping strategies are related to poorer
adjustment to pain and that some wellness-focused strategies were
associated with better adjustment to pain. Passive coping strategies and
catastrophising appear to be the most relevant coping factors leading to
poor outcomes and maladjustment (Boothby et al. 1999; DeGood 2000;
Jensen et al. 1995; McCracken and Eccleston 2003; Romano et al. 2003).
Only a few studies have failed to find a strong association between
catastrophising and disability (Jensen et al., 1992; Jensen et al., 1994).
38
From a clinical perspective, coping strategies appear to be an
important factor in adjustment and are frequently addressed through
teaching
coping
skills
in
cognitive-behavioural
therapy.
These
interventions intend to improve patients’ adjustment towards the
development of several coping abilities (Bradley 1996; DeGood and Tait
2001; Williams 2001). This perspective is also supported by DeGood
(2000) and Haythornthwaite et al. (1998b) who suggest that high
numbers of coping strategies possessed by patients are related with
perceived control over pain, suggesting that flexibility contributes to
effective coping.
Altogether,
the
majority
of
the
evidence
suggests
that
catastrophising and some passive coping strategies are associated with
maladjustment. The literature reviewed also indicates that there is a
complex
relationship
among
coping,
appraisals
and
beliefs
and
adjustment to chronic pain (Boothby et al. 1999; DeGood and Tait 2001;
Geisser et al. 1999; Jensen et al. 1991b).
To date, as suggested by Lazarus and Folkman (1984) and Lazarus
(1993) it seems that effective coping strategy is a function of several
factors, such as values, commitments, appraisals, beliefs, personality,
and other aspects. A mismatch between coping and some of these factors
may reduce the effectiveness of a coping strategy.
In the chronic pain field, the role of factors that influence the
development of maladaptive coping strategies has been a focus of recent
research. This research has suggested that personality traits, specifically
39
neuroticism, seem to predispose some people to engage in catastrophic
response to pain.
The findings reported by DeGood and Tait (2001), McCracken et al.
(2004), Nicholas and Asghari (2006) and Geisser (1999), describe
growing evidence for the role of attitudes and beliefs that moderate or
mediate coping efficacy, such as readiness for change, flexibility in goal
setting, acceptance and self-efficacy. However, much of this work is still
relatively preliminary and longitudinal studies, particularly, are needed to
clarify the role of these dimensions.
As
no
specific
coping
strategies
have
been
identified
as
consistently useful in adapting to chronic pain, this series of studies will
focus on the role of catastrophising as a maladaptive response to pain
that often mediate adjustment and disability in patients with chronic pain.
The concept of catastrophising will be further explored in the next
section.
40
2.1.2 Beliefs
Beliefs can be defined as pre-existing notions about reality and
thus determine how people perceive, evaluate and understand what is
happening around them (Wrubel et al. 1981).
Fishbein and Ajzen (1975) considered that beliefs consist of
information a person has about an object, specifically a belief links an
object to some attribute. It implies a person's understanding about
him/her and the environment. According to these authors, observation
(which will produce descriptive beliefs), information received from outside
(that may produce informational beliefs) and inferential processes
(responsible for inferential beliefs and based on past experience) will
contribute to the formation of beliefs about an object. “The totality of a
person’s beliefs serves as the informational base that ultimately
determines his/her attitudes, intentions and behaviours“ (Fishbein and
Ajzen, 1975, p.14). These authors proposed that only the salient beliefs
(the most important beliefs in a certainty moment regarding an object)
serve as a determinant of an attitude in a given situation.
It is important to differentiate attitudes, beliefs and coping
strategies. An attitude may be defined as “a learned predisposition to
respond in a consistently favourable or unfavourable manner with respect
to a given object” (Fishbein and Ajzen, 1975, p.6). Coping strategies
differ significantly from beliefs (which are always mental) in that coping
strategies are implicated in efforts and can be overt behaviour.
41
Lazarus (1993) argued that beliefs, along with environmental
conditions, influence thoughts, emotions, actions and decisions. In the
appraisal processes, beliefs determine what will be considered important,
or how people perceive things in the environment and consequently how
they might respond.
Different types of beliefs have been linked to appraisal. Lazarus
and Folkman (1984) suggested that beliefs about personal control (locus
of control) and existential beliefs are central in dealing with stressful
demands regarding chronic illness. Beliefs about personal control, (i.e.
the controllability of a given situation) will also influence emotion and
coping.
In general it appears that situational factors (e.g. predictability,
duration) influence appraisal of an event, but also it seems that the
perceived characteristics of the event and personal beliefs play a more
important role in the appraisal and coping process (Lazarus and Folkman,
1984).
There are a number of types of pain-related beliefs. DeGood and
Tait (2001) categorised pain related beliefs into three groups: 1. basic
philosophical and ethical assumptions about the nature of the self and the
world (e.g. justice, suffering, personal responsibility); 2. generalised
beliefs, (e.g. sense of rejection), and 3. specific beliefs regarding the pain
experience (e.g. aetiology of pain, self-efficacy beliefs).
The third category of belief has been investigated more than the
others in chronic pain patients. Several measures have been developed
to assess beliefs regarding control, disability, harm, emotion, use of
42
medication, medical cure, self-blame, catastrophising, pain permanence
and constancy and self-efficacy (DeGood and Tait 2001; Jensen et al.
1999).
This literature review will investigate the role of two of these
specific beliefs, namely pain self-efficacy and catastrophising.
From a cognitive-behavioural perspective, beliefs are considered
important mediators of emotional and behavioural responses to chronic
pain (e.g. Turk 2002). There is evidence that changes in beliefs may lead
to changes in attitudes, coping and behaviours (Boothby et al. 1999;
DeGood and Tait 2001), and that maladaptive beliefs are strongly related
to poor adjustment (DeGood 2000; Jensen et al. 1994).
To Williams et al. (1994) beliefs have a major role in adjustment to
chronic pain. These authors outlined that, pain beliefs “are probably best
judged not by how true or false they are, but how adaptive they are in
enabling the believer to function in the world he/she experiences” (p.
71.).
It has been found that pain-related beliefs play an important role in
the transition from acute to disabling chronic pain. Some beliefs may be
considered a risk-factor for the development of disability, maladjustment,
and poor treatment outcomes (DeGood and Tait 2001; Jensen et al.
1994; Kendall et al. 1997; Linton 2000; Nicholas 1996). For example,
beliefs that pain is mysterious, permanent and that the person is to
blame have been found to be associated with greater psychological
distress. Specifically, pain beliefs regarding mystery appeared to be
related to the use of catastrophising and depressive symptoms, while
43
self-blame beliefs have been associated with depressive symptoms.
Beliefs about pain constancy have been associated with greater pain
severity, and beliefs in pain constancy have been associated with higher
anxiety (Turner et al. 2000; Williams et al. 1994). Harm beliefs (beliefs
that pain indicates damage and that activity should be avoided) have
been associated with poor functioning and pain behaviour (Vlaeyen and
Linton 2000).
On the other hand, there is evidence that the belief that pain is
understandable is associated with higher treatment adherence (Williams
et al. 1994). Stronger pain self-efficacy beliefs also have been found to
be associated with better adjustment to chronic pain and reduced
disability (Asghari and Nicholas 2001; Nicholas and Asghari 2006).
Based on these findings it is widely accepted that research and
clinical interventions should focus on identifying important dysfunctional
and maladaptive beliefs (Jensen et al. 2003).
To date one of the key pain beliefs is self-efficacy. It seems to be
one of the most relevant to pain adjustment and pain-related disability
(DeGood and Tait 2001; Jensen et al. 1991a; Turk and Okifuji 2002).
44
2.1.2.1 Self-efficacy Beliefs
Bandura (1977) proposed that efficacy expectancies determine a
person’s choice of activities; they affect the person’s willingness to
continue in the face of difficulties and adverse situations. Anderson et al.
(1995) and Turk (1999) reported that a person’s self-efficacy beliefs
regarding a behavioural coping strategy are strongly related to the actual
use of a coping behaviour.
Bandura (1977) defined self-efficacy as the degree of conviction
held by a person that she/he can successfully perform a specific
behaviour required to produce a given outcome. Bandura has also
described two types of self-efficacy beliefs: outcome expectancy consists
of a person’s evaluation that a given behaviour will lead to certain
outcomes and efficacy expectations is a person’s conviction that he/she
can successfully execute the required behaviour to produce a given
outcome.
Lazarus and Folkman (1984) and Lazarus (1993) suggested that
efficacy expectancies are a secondary appraisal. According to these
authors, efficacy expectancies and incentives are inter-related and part of
the total evaluation of a situation. They may play a role in evaluating the
antecedents and consequences of particular coping strategies. These
authors emphasised that “the important point is whether general or
specific, illusory or realistic, one’s belief in one’s ability to control an
event influences how that event is appraised and, through appraisal,
45
subsequent coping activity” (p.77). Thus, it could be hypothesised that
certain beliefs are essential to adaptive coping.
Linton and Skevington (1999) proposed that self-efficacy has 3
dimensions rather than the two proposed by Bandura. The first regards
expectations about how difficult a task will be; people are more likely to
avoid difficult tasks than easy ones. The second and third are more
similar to those proposed by Bandura: namely, people may have different
expectations about their ability to carry out specific tasks, and how
confident a person feels about being able to succeed.
Cioffi (2000) described four psychological ways in which selfefficacy beliefs may operate. First, higher self-efficacy levels may
decrease
anxiety
and
distress
which
can
be
responsible
for
misinterpretation of physical symptoms; second, an efficacious person
may distract attention from unpleasant sensations, third, people with
high levels of self-efficacy may also learn other skills to deal with pain
and disability and thus persist despite difficulties; and fourth, other
meanings can be given to a stimulus previously interpreted as noxious.
Linton and Skevington’s (1999) and Cioffi’s (2000) description of
the dimensions and psychological mechanisms involved in self-efficacy,
emphasise the importance of considering the task and it’s content
environment involved (i.e. appraisal of the situation) and perceived selfresources, as aspects considered in relation to the contribution of beliefs
to adjustment to chronic pain.
46
2.1.2.1.1 The Contribution of Self-efficacy to Adjustment to
Chronic
Pain
A number of studies have confirmed the relationship between selfefficacy beliefs, disability and adjustment to chronic pain (Arnstein 2000;
Jensen et al. 1991a; Nicholas and Asghari 2006; Turk and Okifuji 2002).
Anderson et al. (1995) found that self-efficacy beliefs were
associated with levels of functioning and response to treatment in a
sample of chronic pain patients. Their findings also suggested that
patients with higher levels of self-efficacy reported less pain, less
interference in daily activities and greater perceived control over pain.
Altmaier et al. (1993) reported that increments in self-efficacy predict
better functioning and less pain report. Geisser et al. (2003) also found
that self-efficacy is related to functional performance.
Arnstein et al. (1999) and Arnstein (2000) found that although
pain intensity is the most important predictor of disability, self-efficacy
mediates
the
relationship
between
pain
intensity,
disability
and
depression. Their results suggested that lack of self-efficacy beliefs to
manage pain, cope and function despite pain, is a significant predictor of
disability and depression.
Asghari and Nicholas (2001) in a longitudinal study (9 month
follow-up)
also
Questionnaire
found
similar
(Nicholas,
results
1989).
Their
using
the
results
Pain
Self-Efficacy
showed
correlations
between low self-efficacy scores, pain, and complaint and avoidance
behaviours. They also found that self-efficacy is a stronger predictor of
47
disability than pain and distress. Nicholas and Asghari (2006) findings
also suggest that self-efficacy was a significant predictor of disability over
and above the effects of age, pain intensity, depression, fear of
movement, catastrophising and acceptance of pain. This study also
reported that pain severity was significantly predicted by self-efficacy,
and also suggested that changes in self-efficacy could be achieved
despite no change in pain severity. Nicholas and Asghari (2006) have
also reported that self-efficacy is a significant predictor of depression.
Anderson et al. (1995) and Rahman et al. (2005) using different
measures of self-efficacy (CPSS and PSEQ respectively) found that
patients with higher levels of self-efficacy reported a more positive mood
and fewer symptoms of depression. Rahman et al. (2005) and Adams
and Williams (2003) have also reported that self-efficacy is an important
predictor of occupational status.
Jensen et al. (1991a)
suggested that self-efficacy plays
a
significant role in the use of different coping strategies among chronic
pain patients. This finding is similar to those reported by Turner et al.
(2005) with an outpatient community sample with Rheumatoid Arthritis.
In this sample, after controlling for age, gender and pain intensity, selfefficacy was associated negatively with disability and depression, and
positively with active coping strategies.
It has also been recognised that changing beliefs is important in
attempts to change behaviour and to re-establish adaptive functioning.
Altmaier et al. (1993) and Turner et al. (2007) reported that self-efficacy
48
is an important predictor of adjustment in patients who participate in a
CBT intervention program.
Turk (2002b) suggested that patients who believe that they can
alleviate their suffering are more likely to mobilise resources and skills
and to persevere in their efforts to cope with their pain, disability and
suffering. On the other hand, a lack of self-efficacy or the belief that
there are few possibilities to control pain or functioning despite pain, may
lead to a minimal effort to try anything. In turn, this may generate
several negative affects, such as depression (Turk and Okifuji 2002).
Altogether, the available evidence supports the role of self-efficacy
as an important contributor to disability and emotional adjustment to
chronic pain.
2.1.2.1.2 Measures of Pain Self-efficacy Beliefs
Among several measures that assess self-efficacy beliefs the most
commonly used are the Survey of Pain Attitudes - SOPA (Jensen et al.
1987), the Pain Beliefs and Perception Inventory - PBPI (Williams and
Thorn 1989), the Chronic Pain Self-Efficacy Scale - CPSS (Anderson et al.
1995) and the Pain Self-Efficacy Questionnaire - PSEQ (Nicholas 1989).
However, only the last two measures specifically assess pain self-efficacy
beliefs.
The Chronic Pain Self-Efficacy Scale – CPSS was developed by
Anderson et al. (1995) to measure perceived self-efficacy to cope with
the consequences of chronic pain. This measure was based on the
49
Arthritis Self-Efficacy Scale (Lorig et al. 1989). CPSS has 22 items, each
rated on a 10-point Likert scale. Factor analyses identified a three factor
solution accounting for 64% of the variance. Alpha coefficients for
internal reliability of these scales are higher than 0.86 (Anderson et al.
1995). Altogether, data from the initial validation of this measure
reported adequate validity and reliability.
Anderson et al. (1995) found that three factors comprise the CPSS
(i.e. self-efficacy for pain management, self-efficacy for coping with
symptoms and self-efficacy for physical function). The three factors were
significantly correlated with each other, with other measures such as the
Beck Depression Inventory (Beck et al. 1961) and with several scales of
the Multidimensional Pain Inventory (Kerns et al. 1985). Anderson et al.
(1995) also reported that higher scores on the self-efficacy scales were
associated with behavioural coping, less overt pain behaviour, level of
functioning, response to treatment, emotional distress and depression.
Recently this measure has been validated in Brazil, confirming its
psychometric properties and usefulness (Salvetti and Pimenta 2004).
The Pain Self-Efficacy Questionnaire – PSEQ (Nicholas 1989) was
developed specifically to assess a person’s belief in their ability to
function despite pain. It is conceptually based on Bandura’s self-efficacy
theory, in the recognition in the reality that in chronic pain, pain relief is
rarely possible, and that functioning despite pain is one of the main goals
in pain management (Nicholas et al. 1991).
The PSEQ has 10 items, reflecting tasks frequently reported as
problematic according to patients with chronic pain. Each item is rated in
50
a Likert scale varying from 0 to 6, scaled from not confident at all to
completely confident. Scores vary from 0 to 60 and higher scores reflect
stronger self-efficacy beliefs.
The PSEQ validity was assessed through comparison with other
measures with good results. Factor analysis has yielded only one factor
and a strong negative correlation between the PSEQ and the RolandMorris Disability Questionnaire (Asghari and Nicholas 1991; Nicholas
2007). The catastrophising scale of CSQ also correlated negatively with
PSEQ, as well as other measures, such as Sickness Impact Profile (Deyo
1986), BDI (Beck et al. 1961) and the Pain Beliefs Questionnaire
(Gottlieb 1984) (Nicholas, 2007). Ignoring pain, coping self-statement
and pain control, measured by CSQ were positively correlated with the
PSEQ (Asghari and Nicholas, 1991; Nicholas, 2007). Internal consistency
of the PSEQ has been assessed in two studies (both reporting an alpha
coefficient of 0.92) (Asghari and Nicholas 1991; Nicholas 2007) and 0.94
(Gibson and Strong 1996). Test re-test correlation coefficients higher
than 0.71 (over three months) have been reported in the same studies,
which also confirm the stability of this measure.
Williams et al. (1993) have also reported that the PSEQ is sensitive
to detect changes after pain management interventions, and that its
scores are not simply a reflection of pain intensity.
Taking all together, these findings provide strong psychometric and
theoretical support for the PSEQ, and its ability to assess beliefs relevant
to pain management, as well as evaluation of outcomes. Its advantages
51
over the CPSS are that it takes the presence of pain into account and its
items are probably more generally applicable across countries.
2.1.2.1.3 Comments
Despite the importance of self-efficacy beliefs, there are a few
problems in its assessment. These include measurement variability,
variability of findings and construct divergences among other problems,
that are not within the scope of this review (DeGood and Tait, 2001;
Nicholas, 2007).
Differences in results reported may be related to the use of
different measures with the different dimensions (DeGood and Tait,
2001; Turner et al., 2003; Nicholas, 2007). Most recent findings and
studies appear to describe or at least mention the self-efficacy beliefs or
pain-related belief concepts that have been investigated, making the
scope of the study clearer and clarifying the established relationships
among factors.
In reference to construct divergences, although there are some
conceptual divergences regarding the assessment of self-efficacy beliefs,
in general self-efficacy measures assess two domains of this construct:
confidence in personal ability to perform specific tasks and confidence to
cope with chronic pain (Nicholas, 2007).
It is important to note that Bandura’s self-efficacy concept
emphasises that the context must be considered when investigating a
person’s self-efficacy. Reflection on clinical experience might also suggest
52
that it is one thing to ask a person in pain if they can do something and
another thing to ask them if they can do it when they are in pain. Thus,
taking the presence of pain into account would seem important when
assessing the self-efficacy beliefs of a person in chronic pain. This is
consistent with Bandura’s construct. To date only the CPSQ and the PSEQ
seem to consider this issue.
Problems
regarding
construct
definition
measurement variability. Self-efficacy scales
may
may be
also
lead
to
divided into
generalised and specific measures. The generalised ones usually assess
several domains of beliefs but pay little attention to specific tasks. They
may include attitudes, beliefs and coping in the same instrument (i.e.
Survey of Pain Attitudes – SOPA, Jensen et al, 1987); they also could
assess some pain-related beliefs regarding a specific pathology (e.g.
arthritis). On the other hand, specific measures may tend to focus on a
construct or on a few tasks hypothesised to be important, such as
walking a certain distance. While this is thought to be relevant to that
task, it may be difficult to generalise to other tasks or areas of daily life.
To date, the literature reviewed suggests that the Pain Self-Efficacy
Questionnaire – PSEQ (Nicholas, 1989, 2007) is one of the most relevant
measures of this construct. The PSEQ has several advantages over other
measures described here. It is a specific measure that focuses on one of
the most relevant pain-related beliefs; it is based on a strong theoretical
model; its construct is clear and well defined; it takes pain into account
when asking patients about their ability to perform a specific task; it has
53
sound psychometric properties and it has been widely used for over a
decade in several countries with good results.
In addition, the PSEQ is also used at the Pain Management and
Research Centre - RNSH, which will permit comparison of the results
obtained in a Brazilian population with the population at this pain centre.
Based on these considerations, the PSEQ (Nicholas, 1989) is the chosen
measure to assess self-efficacy to be used in this research.
54
2.1.2.2 Catastrophising
The concept of catastrophising has long been used in relation to
depression (Beck 1976; Ellis 1962). Generally, catastrophising has been
described in terms of the expectation of the worst possible outcome in a
given situation (Beck 1976).
Catastrophising was described by Beck (1976) as a cognitive error.
Other authors conceptualise it as automatic, unpleasant, magnificatory,
and unrealistic interpretation of feared future events (McCracken and
Eccleston 2003). Sullivan et al. (1995) stated: “catastrophising involves
an exaggerated negative orientation toward a noxious stimulus” (p.2).
This conceptual framework views catastrophising as a mental set and
that it has at least three dimensions: rumination, magnification and
helplessness. Turk (2002b) defines catastrophising as a cognitive coping
strategy
characterised
by
negative
self-statements
and
excessive
negative future thoughts.
There is some conceptual overlap, as well as divergence on
conceptual
definitions
of
catastrophising.
Some
authors
define
catastrophising as a cognitive coping strategy (Keefe and Williams 1990),
others, such as Jensen et al. (1991) and Turner et al. (2000), conceive
catastrophising as a cognitive process; an automatic thought, an
appraisal. Flor et al. (1992) conceived catastrophising as an automatic
thought that may emerge as a self-statement, which is indeed based in
cognitive schemata and thus could be defined as a belief.
55
According to Sullivan et al. (1995) the three dimensions of
catastrophising; rumination, magnification and helplessness share some
features with the concepts of primary and secondary appraisal. However
they are also very distinct from effort; which is a central issue in the
concept of coping as proposed by Lazarus and Folkman (1984).
The conceptual definitions proposed by Sullivan et al. (1995),
Jensen et al. (1991) and Flor et al. (1992) are becoming better accepted
as many studies are providing evidence regarding the differences among
the constructs and relationship with coping strategies (Turner et al.
2000). Most recently catastrophising has been considered by most
authors as an appraisal process or a belief rather than a coping strategy
(DeGood and Tait 2001; Romano et al. 2003; Stewart et al. 2001).
Furthermore, there is evidence suggesting catastrophising is also distinct
from depression (Keefe et al. 2004; Stroud et al. 2000; Sullivan et al.
2001a).
2.1.2.2.1 The Contribution of Catastrophising to Adjustment to
Chronic Pain
In the chronic pain field, catastrophising has been found to be a
strong predictor of maladjustment, disability, psychological distress, pain
intensity and poor treatment outcomes (Burton et al. 1995; Jensen et al.
2001b; Keefe et al. 2004; Sullivan et al. 2005; Turk and Okifuji 2002).
Sullivan et al. (1995) and Sullivan et al. (2004) in experimental
studies with students using a cold pressor task to induce pain and
56
assessing catastrophising through the Pain Catastrophising Scale found
that high scores on this measure predict intensity, physical and emotional
distress.
Sullivan et al. (2001a) and Buer and Linton (2002) reported that
the relationship between catastrophising and reported pain has been
observed in experimental and clinical studies with different pain patients
and other specific populations. Asghari and Nicholas (2001) found a
relationship between catastrophising and pain intensity in a study with
patients having mammography, suggesting that catastrophising is a
strong predictor of reported pain severity, with those who respond with
catastrophic thoughts reporting higher pain severity. However most of
these studies are cross-sectional in design and the direction of influence
is unclear.
Michael and Burns’ (2004) findings also indicate a relationship
between pain intensity and catastrophising and they suggested that
catastrophising may affect pain intensity and distress through a bias
toward processing the most disturbing aspects of a painful experience.
On the other hand, others have reported that pain intensity may
influence catastrophising (Jones et al., 2003; Sullivan et al., 2001). In
the case of chronic pain at least, as the time course is potentially years, it
is likely that the relationship between catastrophising and pain is bidirectional.
Several studies have reported that catastrophising is a better
predictor of adjustment to pain than coping strategies and medical status
variables (Flor and Turk 1988; Keefe and Williams 1990; Lester et al.
57
1996; Rosenstiel and Keefe 1983). Among several psychological variables
catastrophising has been found to be a better predictor of disability
(Adams and Williams 2003; Sullivan and D'Eon 1990; Sullivan et al.
2005) and quality of life (Lame et al. 2005) than pain intensity. Adams
and Williams (2003) have also found that catastrophising is an important
predictor of return to work. Keefe et al. (2004) pointed out that
catastrophising has emerged as one of the most important predictors of
pain, accounting for 7% to 31% of the variance in pain ratings.
A number of studies have suggested that catastrophising is more
related to the affective dimension of pain. Geisser et al. (1999)
suggested that catastrophising may contribute to the evaluative and
affective dimensions of pain, which is supported by a number of studies.
A study conducted by Turner et al. (2000) found that catastrophising
independently predicted depression, but not physical disability. Sullivan
et al. (2005) reported that catastrophising was significantly correlated
with the affective sub-scale of the MPI. Nicholas and Asghari (2006) also
have found that catastrophising was a stronger predictor of depression
severity than fear-avoidance, self-efficacy and acceptance of pain.
Catastrophising and depression appear to be strongly associated;
however the degree of overlap between these constructs is not high
enough to consider them redundant (D'eon et al. 2004; Jensen et al.
2001b; Jones et al. 2003; Keefe et al. 2004; Sullivan et al. 2001a).
There is also evidence that catastrophising may promote fear of
movement which may lead to avoidance behaviour and consequently
disuse, physical deconditioning and disability (Vlaeyen and Linton 2000).
58
Sullivan
et
al.
(2001)
reported
a
positive
association
between
catastrophising and illness behaviour, even when controlling mood,
neuroticism, pain and disease severity. Catastrophising has also been
found to be associated with solicitousness and pain reports (Giardino et
al. 2003). These relationships may suggest that catastrophising could
contribute to disability and maladjustment by its interactions with other
variables.
It is expected that other pain beliefs, catastrophising and coping
interact dynamically. Turner et al. (2000) suggested that pain beliefs and
catastrophising may influence coping, but also that coping in turn will
influence
beliefs
catastrophising
and
catastrophising.
may
influence
there
is
These
disability
finding
indirectly
suggest
through
that
other
appraisals.
Although
enough
evidence
of
the
contribution
of
catastrophising to disability and adjustment to chronic pain, theoretical
refinements of this concept are still in progress. As noted, there is
evidence that catastrophising is not a coping strategy, it is also distinct
from depression, and may be better defined as a belief or an appraisal
process.
Sullivan et al. (2001b) described a number of theoretical models
(i.e. schema activation, appraisal, attentional and communal coping) that
provide a conceptual framework to understand the role of catastrophising
in pain. Their review suggests that these models are not incompatible
and may offer different contributions to define catastrophising and its
59
dimensions, however do not offer a final solution for the theoretical
debate.
To Sullivan et al. (2001b), the schema activation and appraisal
models offer explanations to understand processes and mechanisms that
underlie
the
relationship
attentional processes),
between
but
do
not
catastrophising
explain
the
and
pain
development
(i.e.
and
maintenance of catastrophising. The communal coping model emphasises
more the contribution of social-behavioural aspects to catastrophising.
2.1.2.2.2 Catastrophising Measures
This literature review has found that the most used measures to
assess catastrophising are the Catastrophising Scale of Coping Strategies
Questionnaire
Catastrophising
–
CSQ
Scale
(Rosenstiel
-
PCS
and
(Sullivan
Keefe
et
al.
1983),
1995)
the
and
Pain
the
Catastrophising Scale of the Pain-Related Self-Statements - PRSS (Flor et
al. 1993).
The Coping Strategies Questionnaire (Rosenstiel and Keefe, 1983)
is a 44-item self-report questionnaire which consists of 8 subscales:
reinterpreting pain sensations, positive coping self-statements, ignoring
pain sensations, increase activity level, diverting attention, increasing
pain behaviours, praying and hoping, catastrophising scale and two selfefficacy items. The catastrophising scale has 6 items that reflect elements
of helplessness and pessimism in relation to pain experience.
60
There are several studies reporting the psychometric properties of
this measure, however, the subscale structure of the CSQ as a whole has
been found to be inconsistent or at least problematic. Nevertheless, the
psychometric properties of the catastrophising scale have been found to
be stronger than the other scales of the CSQ. It has been reported this
scale has good construct validity, reliability and stability (DeGood and
Tait 2001; Geisser et al. 1994; Jensen et al. 1991b; Stewart et al. 2001).
Stewart et al. (2001) reported an inadequate internal consistency,
and
low
test-retest
reliability
(0.7)
on
all
scales,
except
for
catastrophising. On the other hand, the catastrophising scale has shown
a significant correlation with other catastrophising measures (r=0.74),
such as the Cognitive Coping Strategy Inventory (Stewart et al., 2001).
Studies using the CSQ have found that catastrophising is one of
the strongest predictors of several outcomes of maladjustment (DeGood
and Tait 2001; Geisser et al. 1994; Jensen et al. 1991b; Stewart et al.
2001).
There
are
several
criticisms
regarding
the
definition
of
catastrophising as a coping strategy and a sub-scale of CSQ. As noted
before, due to conceptual divergence several authors dispute the idea
that catastrophising is not a coping strategy (Jensen et al., 1991a;
Turner et al., 2000).
Beside this divergence, CSQ also seems to have construct
problems. Several findings do not agree with the number of CSQ factors,
suggesting the existence of three, five or six factors, as well as the fact
that the catastrophising scale is the only CSQ value scale. Furthermore,
61
there is also divergence on CSQ scoring procedures (Hadjistavroupolos et
al. 1999; Jensen et al. 1995; Robinson et al. 1997; Romano et al. 2003).
Despite these concerns, the CSQ is one of the most widely used
measures,
and
several
findings
about
the
role
of
coping
and
catastrophising in adjustment were produced using the CSQ.
The PCS - Pain Catastrophising Scale is a thirteen-item scale
developed by Sullivan et al. (1995) to assess catastrophising thoughts
related to chronic pain. PCS items were derived from catastrophising
ideation symptoms and from the CSQ (Rosenstiel and Keefe 1983). The
items are rated in a 5-point scale, varying from 0 to 4, and ranging from
the words “not at all” to “all the time”.
On the validation of the PCS, Sullivan et al. (1995) found three
scales (rumination, magnification and helplessness) with moderate intercorrelations and high internal consistency suggesting that there are
different dimensions of this construct. Other studies have confirmed the
existence of three factors, reliability and validity of the PCS (Osman et al.
2000; Sullivan et al. 2004), as well as high test-retest correlations (0.70
– 0.80) (Sullivan et al., 2001).
The authors also found differences in
scores associated with gender; females tend to score higher on the
rumination and helplessness scales than males, but these differences
were not confirmed in later studies (Sullivan et al. 2001). Other studies,
have
found
a
two-factor
model
of
the
PCS
(rumination
and
powerlessness, which is a combination of magnification and helplessness)
(Chibnall and Tait 2005).
62
Another measure used to assess catastrophising is one of the
scales of the Pain-Related Self-Statements (Flor et al., 1993). This
measure was developed based on the concepts of cognitive schemata and
automatic thoughts. Cognitive schemata may be defined as “cognitive
structures that contain the individual’s stored knowledge about the world,
and they guide the organisation of incoming information” (Flor et al.,
1993, p. 64). Automatic thoughts are a product of cognitive schemata
and may emerge in the form of self-statements regarding a specific
situation. Cognitive schemata are formed based on past experience as
well as beliefs and thus will mediate a person’s pain perception and
response to it. Indeed, the concept of cognitive schemata is similar to the
concept of cognitive configurations, a central concept in the definition of
belief.
Cognitive schemata are cognitive processes that occur prior to
cognitive appraisal, thus influencing appraisal. This assumption is in
accordance with Lazarus and Folkman’s (1983) concept of coping, which
recognised the influence of beliefs and other factors in coping strategies.
The development of the PRSS is based on the assumption that
these cognitions play a role in promoting or undermining attempts to
cope with pain, and that coping measures such as the VPMI and CSQ did
not properly assess these constructs.
PRSS items were derived from a clinical setting and were factor
analysed, and yielded a 9-item scale for catastrophising rated on a 6point scale (0 to 5). Construct validity, reliability, stability and sensitivity
properties were reported by Flor et al. (1993). Factor analysis of the two
63
scales of the PRSS (catastrophising and coping) reported a lower
correlation between them, suggesting that they are distinct constructs
and should be analysed separately. The authors also suggested that the
more negative scales, helplessness and catastrophising are more crucial
to understand other pain variables. Meanwhile passive coping selfstatements and resourcefulness seem not to be crucial factors (Flor et al.,
1993).
This scale has been used at the Pain Management and Research
Centre for over 10 years and its psychometric properties have been found
to be good (Nicholas 2007; Nicholas and Asghari 2006).
2.1.2.2.3 Comments
Catastrophising
has
emerged
as
one
of
the
most
robust
psychological predictors of pain outcomes (Sullivan et al. 2001a; Thorn et
al. 2003). As noted, catastrophising is associated positively with
measures of physical disability and psychological adjustment, as well as
pain severity in patients with different pain conditions.
Despite the demonstrated importance of this construct as a
mediator factor in adjustment to chronic pain, Turner and Leslie (2001)
and Sullivan et al. (2001) identified a number of key issues still to be
explored regarding the assessment of catastrophising: construct validity,
stability, relationship with other factors and establishing causal relations.
Most catastrophising measures appear to be related but Turner and
Leslie (2001) questioned whether they capture the original construct
64
proposed by Ellis (1962) and Beck (1976). In their study, Turner and
Leslie (1994) reported that these measures seem to have good face,
content and construct validity and are distinct from the concept of
anxiety and depression, but the measures may be improved if they
explored a wider range of items. They suggested that the CSQ and the
PCS would increase their validity if more items were added.
To date, there are no studies comparing these three measures, but
it appears that approximately half of the PRSS items share the same
content as the PCS items. Furthermore the PRSS catastrophising scale
explores a few broader contents and is more pain-specific than the CSQ,
one of the most used catastrophising measures.
The second aspect proposed by Turner and Leslie (2001) regards
the definition of catastrophising as a state or a trait, a dispositional factor
or
a
situational
response.
Studies
using
different
measures
of
catastrophising have reported a high test-retest correlation. CSQ showed
a (0.81) test-retest correlation (Brown et al. 1989), PCS had a (0.75)
correlation across a 6-week period (Sullivan et al. 1995), while the PRSS
had a (0.87) correlation coefficient (Flor et al. 1993). These findings
somehow support the evidence that catastrophising is stable; and could
be defined as a personality trait. On the other hand, Sullivan et al.
(1995) reported that catastrophising scores have changed after some
interventions and certain conditions (e.g. affective states), which support
the evidence that catastrophising may be determined by situational
factors. However, a third and
intermediate
alternative
has
been
proposed. This suggests that, catastrophising may be considered a stable
65
tendency, which may vary as a function of certain conditions (Sullivan et
al., 2001; Turner and Leslie; 2001). This issue may be extremely
important from a clinical point of view, as interventions intend to change
patterns aiming to increase adjustment.
The relationship between catastrophising and other factors (i.e.
beliefs, depression) is becoming better understood. Although there is
some evidence that catastrophising predicts depression (Jensen et al.,
1991; Nicholas and Asghari, 2006)), further research needs to be done to
understand the role of catastrophising as a mediator of adjustment to
chronic pain and the interaction between catastrophising and other
variables. Improvement of catastrophising measures, longitudinal studies
and cross-cultural research may collaborate to increase the knowledge in
this field.
The evidence collected in this literature review has provided
theoretical support to choose the Catastrophising scale of the PainRelated Self-Statements (Flor et al., 1993) as a measure to assess
catastrophising. The PRSS has equal or superior psychometric properties
when compared to the CSQ and the PCS. There is not an overlap of other
constructs in this instrument. Its items are more pain-specific than the
CSQ and the PCS, which may provide important information. Furthermore
the content of the PCS items seems to be assessed by the PRSS
catastrophising scale.
The PRSS catastrophising scale is also the measure used at the
Pain Management and Research Centre – PMRC to assess catastrophising,
which would allow a comparison between data collection from a Brazilian
66
population and the population at this centre. Therefore, the PRSS
catastrophising scale is the chosen measure of this series of studies.
67
2.2 Attitudes
Attitude has been defined as “a learned predisposition to respond
in a consistently favourable or unfavourable manner with respect to a
given object” (Fishbein and Ajzen, 1975, p.6). Attitudes may also be
conceptualised as a tendency to react in a certain manner to a given
situation. They are tightly related to beliefs and appraisals, and also
share some conceptual bases. One of the key differences between beliefs
and attitudes is that the latter are always associated with a response or
orientation towards an object. Although there are several categories of
attitudes, this series of studies will focus only on acceptance.
2.2.1 Acceptance of Chronic Pain
Acceptance may be described as an active and aware attitude,
which implies a willingness to remain in contact and experience pleasant
or unpleasant thoughts, emotions, feelings and sensations without trying
to change or avoid them (Hayes et al. 1994). This concept is not a novel
concept in some fields of Psychology. In Gestalt therapy acceptance and
awareness are central processes in psychotherapy and the bases for any
change (Perls 1969). Kübler-Ross (1982) described acceptance as one of
the stages of loss, indeed an important stage in dealing with any grief
and loss. Hayes et al. (1999) suggested that acceptance may be
considered the opposite of avoidance and different from tolerance.
68
In
western
societies,
this
concept
might
be
frequently
misunderstood and confounded with passivity, and not considered an
important feature of adjustment. However, recently a number of studies
have described the importance of acceptance to adjustment to several
chronic illnesses including chronic pain (Hayes et al. 2006; McCracken
and Eccleston 2003; McCracken and Eccleston 2006; Viane et al. 2004).
The concept of acceptance is quite recent in the chronic pain
literature, but it may make an important contribution to this field,
especially because, for most chronic pain patients, there is no medical
procedure to permanently relieve pain (Turk 2002a). In this context,
there may be adaptive advantages in not persisting with efforts to avoid
what is not possible to be avoided, as it could lead to excessive distress,
anxiety, depression and other negative affects (Hayes et al. 2006).
Acceptance of chronic pain implies living with pain without useless
reactions and attempts to control or avoid it. According to Hayes et al.
(1999) and McCracken and Eccleston (2003), acceptance involves
acknowledging pain, giving-up unproductive attempts, or disengagement
from struggling with pain, acting as if pain does not necessarily imply
disability, developing a realistic approach to pain and pain-related
circumstances, and engagement in positive everyday activities despite
pain. Acceptance also involves a neutral acknowledgment frame and
willingness to live with pain, which is not tolerance and also different
from passive coping strategies which usually lie in external resources to
manage pain. Acceptance also implies not avoiding activities that may
69
cause pain, and it can be differentiated from self-efficacy, because it does
not consider managing pain (McCracken et al. 2004a).
Acceptance seems to have a few dimensions. Risdon et al. (2003)
found 8 different accounts of acceptance, but reported that all the
features could be grouped in three major dimensions: 1. focus away from
pain to no-pain aspects of life, 2. recognition that cure would be unlikely
to happen, and 3. the rejection that acceptance is equal to failure.
McCracken and colleagues analysing the Chronic Pain Acceptance
Questionnaire (McCracken, 1998) and the Illness Cognition Questionnaire
(Evers et al. 2001) reported that these measures have a moderate
correlation
and
therefore
may
measure
distinct
components
of
acceptance. Furthermore, analyses of the CPAQ suggest the existence of
four factors: activity engagement, pain willingness, thought control and
chronicity. But only the first two seem to have adequate psychometric
properties and correlate well with relevant outcomes (McCracken et al,
1999; McCracken et al, 2004b; Viane et al, 2003), therefore two major
dimensions seem to better describe this construct.
2.2.1.1 The Contribution of Acceptance to Adjustment to Chronic
Pain
Several studies
have
found
significant
associations
between
acceptance and adjustment to chronic pain. This section will cover the
main features regarding this relationship.
Experimental studies have found that participants with higher
levels of acceptance report higher tolerance to induced pain and less pain
70
intensity than the placebo and control group (Hayes et al. 1999). Other
studies found that perceived control over pain had a smaller correlation
with better functioning and suggested that the adoption of an accepting
attitude to pain may promote a higher sense of self-control (Jacob et al.
1993; Tan et al. 2002).
Clinical studies have found that greater acceptance of pain is
associated with lower pain intensity, less pain related anxiety, avoidance,
less depression, disability, up time and better work status. After
controlling for demographic variables and pain intensity, acceptance
predicted better adjustment than all the other variables described above
(McCracken, 1998). McCracken and Eccleston (1999) and McCracken et
al. (1999) reported that dysfunctional patients (e.g. not well adapted to
chronic pain) have greater pain-related anxiety and less acceptance of
pain than adaptive patients, and that anxiety and acceptance contributed
uniquely to adjustment independent of depression and pain intensity.
Based on these findings, they suggested that decreasing anxiety and
increasing acceptance might help patients to become more adaptive and
adjusted to chronic pain. Furthermore, results from these studies have
also shown relatively low correlations between acceptance and pain
intensity, suggesting that acceptance is not simply a function of having
low pain intensity.
Other studies done by McCracken and Eccleston (2003a, 2006)
found that greater acceptance of chronic pain was associated with less
pain intensity, lower levels of disability, depression and pain-related
anxiety,
uptime
and
working
status.
When
compared
to
coping,
71
acceptance accounted for more variance in adjustment than coping
strategies. In their second study, they also reported that acceptance is a
more reliable predictor of stress and disability than coping.
Acceptance also has been found to be associated with mental wellbeing, and seems to be a more important predictor of it than pain
intensity and catastrophising (Viane et al. 2003). Viane et al. (2004) also
reported that acceptance seems to be associated with less attention to
pain and engagement in meaningful life activities.
Nicholas
and
Asghari
(2006)
also
investigated
the
role
of
acceptance considering the CPAQ scales and found that only the activity
engagement scale predicts depression, but neither of the subscales
predict pain intensity and disability. Also when compared to self-efficacy
and catastrophising, acceptance appears to be a less important predictor
of disability than self-efficacy. Results from this study found that
acceptance
was
catastrophising,
a
and
less
also
important
less
predictor
important
of
than
depression
than
self-efficacy
and
catastrophising in predicting pain intensity. When analysing the predictive
properties of the four factors, these authors found that only the first
factor (i.e. activity engagement) contributes to depression.
Other studies have shown that activity engagement and pain
willingness have singular roles. McCracken and Eccleston (2003) reported
that activity engagement is a stronger predictor than pain willingness on
several outcomes (i.e. physical and psychosocial disability, uptime, work
status and depression). In another study McCracken and colleagues
(2004a) reported that only the pain willingness factor accounted for a
72
significant variance in pain intensity, medical visits, physical disability
and depression, while the activity engagement factor accounted only for
work status. However when applied as distinct scales, they both
predicted depression, pain-related anxiety and psychosocial adjustment,
but only pain willingness accounted for a significant variance in physical
disability. Viane et al. (2003) also failed to find an association between
acceptance and physical disability.
Taken together, these results suggest that acceptance seems to be
an
important
predictor
of
physical and
psychological adjustment.
However, studies have yielded different results which suggest that
findings with the CPAQ are not robust. So far, it seems that the activity
engagement scale is more relevant than pain willingness, especially on
psychological outcome (i.e. depression).
From a clinical perspective, CBT based programs for chronic pain
often incorporate the concept of avoidance as one of their main
principles. This aspect may be somehow considered the opposite of the
concept of acceptance which implies acknowledging the pain, and
carrying on with daily activities aiming to avoid disability. This modality of
interventions frequently emphasise the importance of not denying pain,
improving physical and psychosocial functioning and not focusing solely
on pain intensity reduction.
Geisser et al. (1994) found that greater acceptance of pain at the
end of a behavioural treatment predicted less interference in daily activity
and higher levels of activity. More recently a few studies have tested the
importance of acceptance based interventions and found that patients
73
that have greater acceptance scores showed significant improvements in
emotional, social and physical outcome (McCracken et al, 2005).
Recent studies of catastrophising and avoidance also suggest some
relationship among these features and hypothesise that enhancing
acceptance may reduce catastrophic thoughts and avoidance (McCracken
and Eccleston 2003; Vlaeyen and Linton 2000).
Nicholas (2007) hypothesised that there is a possible relationship
between acceptance and self-efficacy, suggesting that if a person has
accepted their chronic pain, the chances of engaging in activities would
be greater but still influenced by his/her pain self-efficacy beliefs.
Viane et al. (2003) point out that although it is recognised that it is
important to develop coping strategies to deal with pain, it appears that
strategies to control pain did not reduce depression, and were not related
with better social functioning in patients with high-intensity pain. Actually
according to this perspective, attempts to control chronic pain may be
maladaptive. This finding is in accordance with McCracken et al. (2003),
who found that adaptive copers showed greater acceptance than
dysfunctional patients, and McCracken and Eccleston (2006) who found
that acceptance is a better predictor of adjustment than coping.
Altogether, these findings indicate that exploring the role of
acceptance may contribute to improve the understanding of adjustment
to chronic pain. Furthermore, these results may suggest that acceptance
of pain might be an important mediator of adjustment for some chronic
pain patients.
74
2.2.1.2 Acceptance Measures
Consistent with the
limited evidence regarding the role
of
acceptance in chronic pain is the scarcity of its measures. The only
measures found on this literature review were the Chronic Pain
Acceptance Questionnaire (Geiser 1992) and the Illness Cognition
Questionnaire (Evers et al. 2001).
The Chronic Pain Acceptance Questionnaire – CPAQ (Geiser 1992)
was developed to assess acceptance of pain based on an early version of
the Acceptance and Action Questionnaire (Hayes, 2006). It has 34 items
rated in a Likert scale from 0 to 6 ranging from "never true" to "always
true". The initial study described medium to moderate correlations of this
measure with measures of depression, anxiety and disability, supporting
CPAQ’s validity.
McCracken (1998) proposed a 24-item version, using only the
items found to be relevant. This version has been reported to have a
positive item-correlation and internal consistency (0.84). Initially a four
structure factor was proposed: engaging in normal life activities;
believing that controlling thoughts controls pain; recognising pain
chronicity and needing to avoid or control pain (McCracken et al. 1999).
However, further studies have analysed the factor structure of the CPAQ,
proposing an elimination of some irrelevant items, confirming its face
validity and suggesting minor variations on the existent four factors
(McCracken et al. 2004b). The four factors proposed were: activity
engagement (attitudes that reflect the need to engage in or pursue in
75
normal life activities while pain is being experienced); pain willingness
(recognition that avoidance and control often do not work to adapt to
chronic pain); thought control and chronicity (recognising that pain may
not change). These findings suggest that only the activity engagement
and pain willingness were significant predictors of pain-related disability
and distress (McCracken et al. 2004b).
This latest study confirmed the psychometric properties of the
Chronic Pain Acceptance Questionnaire for a 20-item structure and
confirmed the existence of two major components. The first scale named
activity engagement consists of items that reflect the need to engage in
or pursue activities despite pain, and the second scale concerns the
recognition that avoiding or controlling pain may be of a little use and an
ineffective strategy.
The Chronic Pain Acceptance Questionnaire – CPAQ (20-item
version) proposed by McCracken et al. (McCracken et al. 2004b) appears
to be an adequate measure with good psychometric properties to assess
chronic pain acceptance.
The Illness Cognition Questionnaire - ICQ (Evers et al. 2001) was
developed to assess cognition reflecting meanings of chronic diseases. It
has 18-items, which yield three general illness cognitions: helplessness,
acceptance and disease benefits. The validity of the ICQ has been
supported by its correlations with measures of physical and psychological
health status (Evers et al., 2001; Viane et al., 2003). Although the ICQ
was not developed to assess acceptance regarding chronic pain, it has a
76
moderate correlation with the CPAQ, which suggests that they may
measure different aspects of acceptance (Viane et al. 2003).
2.2.1.3 Comments
The concept of acceptance is novel and promising in relation to
adjustment to chronic pain. Although there is some evidence of the role
of acceptance in chronic pain, further research is needed to clarify its role
and relationships with other factors, such as beliefs, coping strategies,
disability and adjustment to chronic pain, and to assess the contribution
of acceptance to physical disability and emotional adjustment (McCracken
and Eccleston 2006; Nicholas and Asghari 2006; Sullivan et al. 2005;
Viane et al. 2003).
Recent findings from these authors enhanced the importance of
clarifying the definition of acceptance, improved acceptance measures
and providing evidence about the role of acceptance in disability and
adjustment.
In relation to conceptual definitions, generally, acceptance could be
conceived as either an attitude or a belief. According to Fishbein and
Aizen (1975), an attitude is a learned predisposition to respond in a
consistently favourable or unfavourable way to a given object, while
beliefs are defined as pre-existing notions about reality which serve as a
perceptual lens and thus determine how a person evaluates and
understands what is happening (Wrubel et al. 1981). To Fishbein and
Ajzen (1975), beliefs consist of information a person has about an object,
77
and links an object to some attribute. It implies a person' understanding
about himself/herself and the environment. Although attitudes may be
based on beliefs, they imply an orientation towards an object, thus it
seems more appropriate to define acceptance as an attitude.
Recent studies (McCracken et al. 2004a; Risdon et al. 2003;
Viane et al. 2003) have applied the concept of acceptance initially
proposed by Hayes et al. (1994) by considering the context of chronic
pain sufferers. This novel conceptualisation regarding acceptance in
chronic pain emphasises the attitude to shift from pain to no-pain aspects
of life and the need to acknowledge that there might not be a total cure
for pain (Risdon et al. 2003).
It may also be important to differentiate acceptance from other
constructs, especially self-efficacy. Self-efficacy concerns beliefs related
to the ability to manage pain, while acceptance is more related to facing
chronic pain without judging it or coping with it.
Another important aspect regarding the concept of acceptance is
related to its dimensions. As noted previously, studies have reported a
moderate correlation between two measures of acceptance. Furthermore,
studies have reported different findings about the contribution of
acceptance to pain intensity, disability and emotional adjustment, as well
as the unique contribution of its factors. These findings suggest that
acceptance is composed of more than one dimension, and these
dimensions probably play different roles in physical disability and
emotional adjustment.
78
The relationship between acceptance and pain-related beliefs
(e.g. self-efficacy and catastrophising), and acceptance and mood, and
what are their unique roles in disability and adjustment is not well
understood yet, and further research should address these questions.
Altogether,
the
evidence
gathered
suggests
that
although
acceptance seems to predict physical and psychological adjustment,
studies have yielded different results, which suggest that those findings
are not robust. So far, it seems that the activity engagement scale is
more
relevant
than
pain
willingness,
especially
when
evaluating
psychological outcome (e.g. depression). Therefore, further studies might
be necessary to support the psychometric properties of this measure, as
well as providing more evidence about the contribution of acceptance and
its dimensions to adjustment.
In this series of studies the psychometric properties of the CPAQ
will be examined in a non-English speaking population, which may help to
improve our understating of the use of the CPAQ. Furthermore, the
contribution of acceptance to physical and emotional adjustment will be
evaluated in a Latin American population with chronic pain, which may
shed some light on the role of acceptance in other non English speaking
populations with chronic pain. Beside these features, this series of studies
will also compare the contribution of acceptance to disability including
measures of self-efficacy, depression and catastrophising.
Supported by these assumptions, and aiming to understand the
role of acceptance in disability and its relationship with other factors, this
series of studies choose the Chronic Pain Acceptance Questionnaire –
79
CPAQ (20-item version) (McCracken et al., 2004b) as the measure to
assess acceptance in chronic pain patients. The CPAQ (McCracken et al.,
2004) has stronger psychometric properties than the Illness Cognition
Questionnaire (Evers et al. 2001); it was specifically developed for
chronic pain patients, its factors appear to be more in consonance with
relevant findings reported by the literature and it is widely used.
As a part of this research project, the CPAQ was added to the
battery of measures used in the Pain Management and Research Centre –
RNSH, making it possible to compare the samples investigated in this
series of studies.
80
2.3 Affective Factors
Among all affective factors associated with chronic pain, depression
appears to be one of the most relevant, as well as the most studied.
Depression is more common among chronic pain patients than in the
general population and healthy controls (Pincus and Williams 1999;
Romano and Turner 1985; Turk and Okifuji 2003). Although the
prevalence of depression varies among different chronic pain populations,
rate of depression in this population is considered high. Reviews have
reported a depression prevalence range from 1.5% to 57% (Fishbain et
al. 1997; Worz 2003). McWillians et al. (2003) have found a depression
prevalence of 20% in a chronic pain non-clinical representative sample in
the United States. The large variance in results may be due to different
diagnostic criteria, measures and setting. Despite different results, from a
clinical perspective the association of depression and chronic pain is
considered very important.
2.3.1 The Contribution of Depression to Disability Associated with
Chronic Pain
Worz (2003) suggest that depressed chronic pain patients are less
active than non-depressive patients, that depression reduces the likelihood
of responding to treatment and worsens the effect of chronic pain on
physical and psychological functioning.
81
A literature review by Pincus et al. (2002) found that depression,
anxiety and somatization are implicated in transition from acute to
chronic low-back pain. According to Pincus and Williams (1999) selfreports of depression predict disability better than pain intensity and pain
duration. Keefe et al. (2001) and Pincus and Williams (1999) have
suggested that depression may not be only associated with chronic pain,
indeed it is a risk factor to pain onset and development, as well as
disability.
Haythornthwaite et al. (1991) reported that chronic pain patients
with depression reported greater pain intensity, greater pain interference,
and more pain behaviours. They also found that depressed patients are
more likely to drop out of a rehabilitation program. Keefe et al. (2001)
findings suggest that emotional distress (i.e. depression) has being
associated with higher numbers of treatment seeking behaviour.
Breslau et al. (2003) found that higher disability levels related to
headache were associated with depression. Nicholas (1996) pointed out
that depression contributes to suffering, disability, as well as impaired
coping abilities (Von Korff et al. 1993). Banks and Kerns (1996) have
found that depression may mediate the relationship between chronic pain
and disability.
On the other hand, other studies have reported that physical
disability, self-efficacy and catastrophising could also mediate depression
(Asghari 1996). Arnstein et al. (1999) have also reported that selfefficacy and pain intensity contributed to the development of depression
and disability.
82
The influence of depression on chronic pain has also been
associated with pain intensity, gender and age. Jensen et al. (1994)
found that pain intensity was a significant predictor of depression. Turk et
al. (1995)
found that in older patients there is a strong association
between pain severity and depression, not observed in younger patients.
Other findings suggest that although gender does not predict disability, it
moderates the relationship between depression and disability (Campbell
et al. 2003; Keogh et al. 2006).
Evidence of the relationship between pain intensity, disability and
depression has been well reported in the literature, however with a large
variance (McCracken and Eccleston 2005; Turk et al. 1995). Gender and
age have also often been reported as moderators of depression, again
with a large variance in results (Harris et al. 2003).
A few theoretical models have described the contribution of
depression to chronic pain and disability (e.g. Pincus and Willians, 1999;
Turk, 2002b). According to these models depression may contribute to
disability due to interaction with other factors (e.g. anxiety, catastrophic
thoughts, fear-avoidance, low self-efficacy and neuroticism). These
factors appear to participate as vulnerability factors to disability.
Although the role of depression in chronic pain is recognised, the
nature of this relationship remains unclear. Robinson and Riley (1999)
described the existence of four models regarding the relationship of
negative affect and pain. The first perspective suggests that negative
emotions increase pain report through the sensory dimension (e.g.
increasing sensitivity to noxious stimuli). Another model posits that pain
83
is caused by negative emotions (e.g. an underlying depressive disorder).
A third hypothesis suggests that negative emotion is a common response
to pain, while a fourth hypothesis proposes that chronic pain and
depression
occur
simultaneously,
due
to
similar
physiological
mechanisms. Broadly these models could be described as antecedent,
consequence and bidirectional hypotheses respectively (Worz 2003).
A review by Fishbain et al. (1997) reported that 9 of 13 studies
that endorsed the pain as a consequence hypothesis failed to support it
with evidence, while another 15 studies supported the hypothesis that
depression may follow chronic pain.
Evidence gathered by Gamsa (1994) suggests that depression may
often be a consequence of chronic pain that is also mediated by other
factors (e.g. self-efficacy), but which in turn mediates other factors such
as coping, physical and psychological functioning.
To Worz (2003) the third hypothesis (i.e. negative emotion is a
common response to pain) needs further evidence, and it seems more
appealing that the relationship of depression and chronic pain is dynamic
and bidirectional.
A model proposed by Pincus and Williams (1999) illustrates the
multi-directional relationship between depression and other factors in
chronic pain.
84
Stressor
Stressor
Pain
Injury
Trauma
DIATHESIS
Negative
Affect
(Depression)
Disability
Cognitive
Vulnerability
Stressful
Life
Events
Figure 4. A Multistage model of cognition, disability and affect (Pincus and
Williams 1999).
To date it seems that no single model that has been widely
accepted to explain the relationship between chronic pain and depression.
As
proposed
by
Worz
(2003),
a
multifactorial
and
bidirectional
comprehension of this relationship seems to be better supported by
evidence and is more adequate from a clinical perspective as well.
Taken together, these findings suggest that depression may
mediate the perception of noxious stimuli, as well as responses to chronic
pain, which in turn may increase disability and maladjustment to chronic
pain. On the other hand, depression does not appear to be an important
predictor of physical disability, especially when compared to other factors
such as catastrophising, self-efficacy and acceptance.
85
2.3.2 Depression Measurement
Despite the prevalence and contribution of depression to chronic
illness and specifically to chronic pain there is criticism regarding the
construct validity of a number of measures of depression.
Debate has emerged over the actual nature of depression in
chronic pain populations, especially in relation to symptoms that may be
shared between chronic illnesses, pain, side-effects of treatment and
depression (e.g. Pincus and Williams, 1999). A number of researchers
(e.g. Lovibond and Lovibond, 1995; Morley et al., 1995; Novy et a.,
1995; Pincus and Williams, 1999) have explored cognitive models of
depression, in contrast to the more traditional DSM-IV (American
Psychiatric Association 1994) which describes depression in terms of
somatic, affective and cognitive symptoms. These different models of
depression have implications for the assessment of depression, especially
when assessment is based on older psychometric scales (e.g. Beck (Beck
et al. 1961), Zung (Zung and Durham 1965) and Hamilton (Hamilton
1960). These older scales are derived from the traditional DSM approach
and, accordingly, include somatic symptoms, such as: insomnia, appetite
changes, weight loss, loss of libido, and motor retardation (Aylard et al.
2005; Beck et al. 1961; Hamilton 1960; Heretik and Molcan 1984; Zung
and Durham 1965).
The somatic items inflates depression scores in chronic pain
populations, making its diagnosis and assessment biased (Pincus and
Williams 1999; Robinson and Riley III 1999; Taylor et al. 2005).
86
Pincus and Williams (2004) found that chronic pain patients tend to
endorse the somatic items of depression more often than depressed
people without chronic pain. In this population, it seems that somatic
items may be relatively poor markers of depression; chronic pain patients
may experience somatic symptoms for other reasons than depression;
and that the presence of somatic items may inflate test scores in this
population (Pincus et al. 2004; Taylor et al. 2005).
To date, the most widely used measures to assess depression in
chronic pain patients are the Beck Depression Inventory – BDI (Beck et
al. 1961), the Center of Epidemiological Study-Depression Scale – CES-D
(Radloff 1977) and the Zung Self-rating Depression Scale (Zung and
Durham 1965). However, to overcome the problem of bias caused by
somatic items in the assessment of depression, especially in medical
populations, a number of alternative depression measures have been
used. These include the Hospital Anxiety and Depression Scale (HADS)
(Zigmond and Snaith 1983), the DASS - Depression, Anxiety and Stress
Scales (Lovibond and Lovibond 1993), the Depression, Anxiety, and
Positive Outcome Scale (DAPOS) (Pincus et al. 2004).
Below the most used measures of depression will be briefly
described.
The Center of Epidemiological Study-Depression Scale - CES-D
(Radloff
1977)
was
developed
to
measure
levels
of
depressive
symptomatology, with a focus on affective, somatic and interpersonal
aspects of depression. The CES-D has 20 items; rated in a four point
scale, and a cut-off of 16 points for general population while a cut-off of
87
19 has been suggested for chronic pain patients (Turk et al. 1995).
Radloff (1977) has described adequate validity and reliability properties
for the CES-D. Other studies have confirmed the psychometric properties
of this measure and pointed out that it has fewer somatic items than the
BDI (Bradley and McKendree-Smith 2001; Turk et al. 1995).
The Beck Depression Inventory – BDI (Beck et al., 1961) was
based on Beck’s depression theory and its items were selected partially
from DSM-III. Originally the BDI was developed to evaluate cognitive
components of depression; however, it has several somatic items (e.g.
sleep disturbance). A 3 factor structure has been reported (i.e. negative
attitudes/suicide, performance difficulty and physiological manifestation)
(Novy et al. 1995; Turk et al. 1995) which is not discrepant with BDI
theoretical bases .
The BDI has 21 items, rated on a 0 to 3 scale, with wellestablished means for a number of groups, including chronic pain
patients. The BDI psychometric properties have been supported by many
studies, and this is probably the most widely used measure to assess
depression (Bradley and McKendree-Smith 2001; Robinson and Riley III
1999). There is also a Brazilian validation of this measure for general
population and for chronic pain patients (Cunha 2001).
Studies comparing the BDI and CES-D suggest that both measures
have adequate sensitivity and specificity properties. The CES-D seems to
be more sensitive to detect change than the BDI, while the BDI seems to
be more specific to detect depression (Bradley and McKendree-Smith
2001).
88
The Zung Self-rating Depression Scale – SDS (Zung and Durham
1965), is another common self-report measure. This scale was originally
developed to assess depression in people with a primary diagnosis of
depressive disorders. The SDS has 20-items, including somatic and
organic symptoms of depression. The items are ranked from 1 to 4
associated with the words ’little or none of the time”, “some of the time”,
“a good part of the time” and “most of the time”.
Turner and Romano (1984) reported that in a sample of chronic
pain patients the SDS has shown good concurrent validity, sensitivity and
specificity when compared to BDI. Recent findings suggest that in a
sample of chronic pain patients, the Zung’s somatic items were
preferentially endorsed when compared to non-somatic items (Taylor et
al. 2005). This feature may cause an inflated score on depression in this
population when measured by SDS. In the same study, the SDS showed
poor sensitivity and specificity to discriminate somatic symptoms of
depression from anxiety/stress items in chronic pain patients, as well as
in another clinical population and in a sample of general population.
More recently, the Depression, Anxiety and Stress Scale – DASS
(Lovibond and Lovibond 1993) was developed aiming to provide a more
specific measure of depression, anxiety and stress with a lower intercorrelation between these factors, and without including somatic items.
The DASS has 3 scales (depression, anxiety and stress) and 42-items
ranging from 0 to 3. The Depression scale has 14 items; none of them
reflect somatic symptoms. This scale is characterised mainly by loss of
self-esteem and incentive, indeed some symptoms of depression that
89
traditionally appear in other scales are not part of DASS – Depression
scale, because they do not seem to be specific to depression (Lovibond
and Lovibond 1995).
It has been reported that the DASS has good psychometric
properties and high to moderate correlation with other similar measures.
The DASS-depression scale has a moderately high correlation (0.74) with
the BDI (Lovibond and Lovibond 1995). Although the BDI has a number
of somatic symptoms of depression among its 21 items, 13 reflect
cognitive symptoms of depression, thus a moderate-high rather than a
high correlation between these two measures is to be expected. The
DASS has a high internal consistency, as well as the depression scale
(0.91). Furthermore, there is a minimal construct overlap in this measure
(Lovibond and Lovibond 1995).
Results from Taylor et al. (2005) have also reported a high internal
consistency for all the scales (0.96 for the depression scale) with a
chronic pain sample, as well as sensitivity and specificity properties of the
DASS scales among different groups (clinical patients, chronic pain
patients and general population).
Recently a short version of the DASS has been developed reporting
adequate psychometric properties for this version as well, which confirms
the validity and reliability of the original version (Henry and Crawford
2005).
90
2.3.3 Comments
As described previously, depression is frequently associated with
chronic pain, and it is recognised that depression plays an important role
in disability and adjustment to chronic pain, thus its
diagnosis,
assessment and treatment are important. Although findings are not
robust and consistent about the contribution of depression to disability,
there is evidence suggesting that depression contribute to suffering and
poor outcomes.
However, as noted, there is concern that in addition to questions
about the models of depression on which these older scales are based,
the assessment of depression in medical populations using scales that
contain somatic items of depression may lead to bias in their findings.
It has also been recognised that the three general depression
measures described previously have strong psychometric properties, as
well as disadvantages and advantages among them (Bradley and
McKendree-Smith 2001). However their use may not be appropriated to
chronic pain patients. Among the no-somatic measures of depression,
each of these measures have been well-supported (Bejlland et al. 2002;
Henry and Crawford 2005; Pincus et al. 2004), as has their use in chronic
pain populations (Pincus et al. 2004; Taylor et al. 2005). Of these scales
only the HADS has been validated in a Brazilian (non-pain) population
(Botega et al. 1995), but none have been validated in a Brazilian chronic
pain patient population.
91
Although there is no consensus in the literature about this matter,
using a measure to assess depression that does not have somatic items
as a part of its construct has been widely encouraged.
Based on the literature reviewed, not having somatic items as a
part of it appears to be the greatest advantage of the DASS – depression
scale among the other measures. Furthermore, the psychometric
properties of the depression scale of DASS are as psychometrically sound
as the other measures, indeed with stronger psychometric properties in a
few aspects. Considering these aspects, its brevity and the fact that the
DASS is one of the measures used in the Pain Management and Research
Centre – PMRC to assess depression, the DASS- Depression scale is the
chosen measure for this series of studies. This will also permit a
comparison of the results obtained in a Brazilian population with chronic
pain with the population at the PMRC.
92
2.4 Cultural Factors and Pain
It has long been thought that ethnicity has an impact on the
course of illness and treatment (Dimsdale 2000). These assumptions may
be extended to chronic pain to some degree.
In the early 1950s Zborowski (1952) suggested that sociocultural
factors may affect the psychophysiological processes of pain perception
and response to it in different ways. He pointed out that every culture has
attitudes towards pain, but their meanings and manifestations differ
significantly. Zborowski’s work provided an important early stimulus to
studies of cultural factors in pain; subsequent research has broadened
understanding of the topic.
This section will describe the main models of culture and pain, as
well as relevant evidence in this area.
2.4.1 Contribution of Cultural Factors to Chronic Pain
Despite Zborowski’s (1952) earlier contribution, Bates (1987),
Edwards and Fillingim (1999) pointed out that there were several
methodological weaknesses in these early findings. Recent investigation
has lead to a better comprehension of the role and interaction of physical
factors and learning processes with cultural, ethnic and racial factors in
illness and chronic pain.
Human beings have basically similar neurophysiological systems,
thus differences in pain perception and response cannot be explained
93
only by neurophysiological differences among races (Bates 1987). Rey
(1998) also shared this assumption suggesting that nociception reflects
anatomy and physiology, but cultural and social factors are the
foundation for the expression and treatment of pain.
The concept of race, ethnicity and acculturation are central to this
discussion, and will be briefly defined. Race may be defined as a group of
people united or classified together on the basis of common history,
common descent and ancestry or hereditary and genetic features. The
concept of ethnicity focuses on the distinction between groups of people
based on behaviour and culture, group membership, as well as biology
and physical characteristics (Edwards et al. 2001a). Acculturation refers
to the process to which migrants go through involving a change of
knowledge, cultural beliefs, values, and practices towards those of the
host society (Helman 1996).
Frequently, people that belong to a specific ethnicity are from the
same race, but beside this, they may also share similar habits, norms,
characteristics, behaviours, culture, social and psychological nature
unless they have been through an acculturation process. According to
Fallo (1998), the level of acculturation may be an important intervenient
variable between ethnicity and variables such as response to pain,
attitudes and beliefs. However, this discussion is not the scope of this
review.
In the last two decades at least three models have attempted to
describe the role of culture in chronic pain. Bates (1987) proposed a
biocultural model to explain some issues regarding pain and ethnicity
94
which integrates aspects of the Gate Control Theory, social learning
theories and social comparison processes. According to this model, the
degree
to
which
sensory
transmission
increases
or
decreases
is
determined by A beta, A delta and C fibres and also by descending
influences from the brain. These descending influences are mediated by
cognitive or higher brain processes, which can have an important
influence on the pain process.
Bates suggested "There is evidence that social learning is
instrumental in the development of meanings and attitudes toward pain.
Learned values and attitudes affect one's attention to painful stimuli and
one's memories of prior pain experiences. Therefore, it is likely that
cultural
group
experiences
influence
the
physiological
processes
responsible for pain threshold and perception of pain severity, as well as
pain response" (1987, p. 48).
Skevington (1995) proposed a four-stage model to explain the
influence of social factors implicated in the generation and maintenance
of chronic pain and illness, which shares some features with Bates’
model.
The first level regards the individual behaviours and includes
perceived bodily sensations, perceived severity of symptoms, lifetime
personal and social schemata, lifetime personal and social emotions,
lifetime personal representations and personal motivation, which are all
in some degree influenced by social processes (e.g. beliefs and social
representations). In the second level are interpersonal behaviours, which
include thoughts, emotions, motives and behaviours resulting from
95
relationships among those suffering and family members, friends and
health professionals.
The third level consists of group and inter-group
behaviour, “where the identity of the pain sufferer is formed and
maintained
through
social
categorisation,
social
comparisons
and
identification process” (1995, p. 294). The fourth level concerns higher
order factors affecting social-psychological processing, and includes
health culture, health history and health ideologies among other macrocomponents. Although there is a dynamic relationship between all levels,
Skevington (1995) suggested that there is a descending influence from
the fourth and superior stages on all the processes on the lower levels.
Wade et al. (1996) also proposed a four-stage model of pain
processing,
which
can
contribute
to
understanding
racial/ethnic
differences in chronic pain. According to this model, there is an initial
sensory-discriminative stage related to the perceived intensity of pain
sensation, the second stage is related to the individual immediate
affective response to stimuli and involves some cognitive processes. The
third
stage
involves
long
term
cognitive
processes
related
with
individual's meaning implications, and the final stage is the behavioural
expression of pain. According to this model race/ethnicity has little
impact on pain sensation the initial sensory-discriminative stage, but a
larger impact on the next two cognitive stages and on the fourth stage,
which involves behavioural expressions of pain. According to this model,
social and cultural factors might act as moderators of the noxious stimuli
in all the pain stages.
96
In general, all these models propose that social comparison and
social learning processes within ethno-cultural group situations influence
attitudes toward pain, attention to pain stimuli or sensation and cognitive
control. Prior pain experiences also participate in this process.
Based on these models it could be assumed that attitudes, beliefs,
attribution, expectations and assumptions are shaped socially and that
culture has an important role in pain perception and response to pain.
Several findings support the influence of social and cultural factors
in response to pain, although with a variety of results.
Zatzick and Dimsdale (1990) reviewed thirteen studies related to
response to laboratory and induced pain. They found a great diversity of
ethnic groups, pain induced methods and outcomes, and suggested that
there appears to be no racial/ethnic differences in the ability to
discriminate noxious stimuli. Woodrow et al. (1972) studied 4000
subjects and found that White Americans showed higher pain tolerance
than African Americans, and Asian Americans showed lower tolerance
than African Americans. Their results also suggest that this difference is
more marked in men than in women. Chapman and Jones (1994)
reported that White Americans descended from Northern Europeans
reported higher thermal pain thresholds and tolerance than African
Americans. Wash et al. (1989) also suggest that Saxons have a greater
pain tolerance (measured by a cold pressor test) than non Anglo-Saxons
(Hispanic and African Americans) across sexes and age. Sheffield et al.
(2000) reported that African Americans rated a noxious stimuli as more
unpleasant and showed a tendency to rate it as more intense than White
97
Americans, women showed a tendency to rate stimuli as more unpleasant
and more intense than men. In addition, systolic blood pressure was
inversely related to pain intensity. After statistically adjusting for systolic
blood pressure, sex differences in pain unpleasantness were reduced, sex
differences in pain intensity were abolished but race differences were
unaltered.
Although these findings are not robust, yielding mixed evidence,
there is no evidence about how precise was the racial grouping and
acculturation in the studies involved. Taken together, these studies
suggest that ethnic membership (e.g. African Americans) and female
gender are associated with greater reported pain and greater pain
behaviour display when compared to other groups.
Other studies (Sheffield et al., 2000; Edwards et al, 2001a) have
found different disease distribution among specific chronic pain diseases
related to race, including angina and ischaemic pain among others. These
results suggest that there is some specificity involving disease prevalence
and race, which is important to note but which may not be important to
the discussion regarding the influence of ethnicity on chronic pain.
It seems that one of the main issues in this area regards the
mechanisms that mediate or moderate these differences and how they
may affect response to chronic pain.
Results of a study conducted by Honeyman and Jacobs (1996) with
a group of aboriginal people in Central Australia reported a pain
prevalence range varying from 30 to 50% which is higher than most
studies, but not all studies in other countries. However, no illness and
98
pain behaviours were observed as defined in western models (e.g.
guarding). These authors also described that the community experience
with pain starts in early childhood through spiritual practices, and that
they have some beliefs and laws about displaying or complaining about
pain. Displaying pain behaviour is not encouraged and there is a strong
community expectation about tolerating pain. Thus, pain behaviour and
illness are not reinforced and people appear to learn to cope with or
accept pain.
Lofvander and Furhoff (1996) compared Swedish and Greek
patients with back pain and found several differences between these two
groups. The Greeks in that study displayed more pain behaviours, use
more passive coping strategies and catastrophise more when compared
to the Swedish sample. Fallo (1998) also found significant differences in
coping strategies among different cultures in South Australia. His findings
suggest that Iraq and Central American subjects seemed to use more
passive coping strategies than Italians and Chinese subjects. The Iraq
group reported more use of praying and displayed more pain behaviours
than other groups. Italians and Chinese appeared to attempt to ignore
pain. The Italians also used more active coping strategies than the
Central American group. Attitudes towards pain among groups were also
related to different preferences for coping strategies (e.g. Chinese
preferred massage when compared to other groups). How well these
findings are generalisable to people of similar ethnicities and other similar
situations remains to be shown.
99
Tan et al. (2005) found that Black American patients reported
lower perceived control over pain, more external pain-coping strategies,
more solicitous beliefs about pain, higher levels of depression and
disability, even after controlling for pain intensity. Edwards et al. (2005)
compared African, Hispanic and White Americans and found no significant
differences in measures of pain, depression, psychopathology and
disability, but some differences in coping strategies, with Black and
Hispanic Americans reporting higher scores on hoping and praying than
White Americans. Hastie et al. (2004) also found significant main effects
of ethnicity on four out of seven CSQ-R scales.
Results from Bates et al. (1993) study illustrate these differences
well. Their findings suggest that pain intensity variations may be affected
by differences in attitudes, beliefs and emotional and psychological states
associated with different ethnic groups. These authors also found that
different ethnic groups have different beliefs about appropriate emotional
expression responses to pain. Furthermore the locus of control also
appears to differ among groups and play an important role in pain
intensity perception. Bates and colleagues (1993) pointed out that
culturally acquired patterns might lead to different pain perception but
also to different styles of reporting pain.
Differences in pain perception can be explained partially taking into
account physiological, psychological and ethno cultural factors. Indeed,
some research has suggested that anxiety, personality, education level,
family history, attentional variables and peripheral mechanisms of
nociception do not account for differences between different ethnic
100
groups (Edwards and Fillingim 1999; Lasch 2002; Zatzick and Dimsdale
1990). Other important variables such as beliefs, attitudes, coping
strategies, social learning and affect may influence stimuli response, and
it appears that these variables vary widely across cultures (Moore and
Brodsgaard 1999).
It seems that there is also an affective component in cultural bias
in pain perception. These differences seem to be smaller in pain threshold
measurement, which is a sensory-discriminative dimension of pain
(Moore and Brodsgaard 1999). On the other hand, pain tolerance may be
related strongly with the affective-motivational dimension (Edwards et al.
1999). It can be hypothesised that different ethnicities may differ more in
the affective dimension (e.g. overt pain behaviour) rather than in the
sensory processing of noxious stimuli.
There is evidence suggesting an association between emotions and
pain behaviour. Edwards et al. (2001b) examined responses among
different ethnic groups related to pain intensity (how strong the pain
feels) and pain unpleasantness reports (how unpleasant the pain is). No
differences were found on thermal threshold but differences were found
in pain tolerance, with White Americans demonstrating a greater pain
tolerance over African Americans. Another study conducted by Riley et al.
(2002) found higher levels of pain unpleasantness, emotional responses
to pain, and pain behaviour among African Americans when compared to
White Americans, but no difference in the degree of pain intensity. Other
research also suggested higher levels of depression, post-traumatic
stress disorder and sleep disturbance in Black Americans with chronic
101
pain than White Americans (Green et al. 2003). Studies using the MPQ
found no ethnic differences in measuring pain sensation but found
differences in the affective scales of this instrument. (Lipton and Marbach
1984) These findings reinforce the role of affect on cultural differences
and its contribution to responses to pain.
More recently, differences in the use of the health system and
other outcomes among ethnic groups have been investigated. Lasch
(2002) reviewed several studies and found that
ethnicity membership
may affect provision of medication. Ethnic minority groups also appear to
have less access to health services (Nguyen et al. 2005).
In general, there is a degree of consensus about the importance of
ethnicity in pain perception and response to it. As noted earlier, the
models proposed by Bates (1987), Skevington (1995) and Wade et al.
(1996) share several features in common and provide support to
understand the role of social and cultural factors in shaping perception and
response to pain. Evidence on ethnic differences in pain perception and
responses to it, have confirmed these theoretical models.
However, Edwards et al. (2001a), Edwards et al. (2005) and Riley et
al. (2002) have suggested that methodological aspects should be taken
into
account
and
recommended
caution
in
the
interpretation
and
generalisation of these findings. Problems such as interference of the
experimenter’s ethnicity on results, and controlling for a number of
confounding variables (e.g. acculturation, sampling) could affect results
significantly.
102
Skevington (1995) pointed that some types of social research have
led to patient labelling and categorising instead of understanding the
process by which these differences arise. Broadly, the bulk of available
findings support the evidence that there are different responses to pain
among various ethnic groups. As mentioned by Zatzick and Dimsdale
(1990) it seems that it is easier to identify ethnic differences than to
explain those differences.
2.4.2. Comments
Despite methodological problems and lack of conclusive evidence,
it seems that different ethnic groups have only a small variance in pain
perception, but more important than this, they seem to respond
differently to pain. Mechanisms involved in the relationship between
culture and pain are evidently complex and caution is needed in
interpreting findings, especially in avoiding confusing description with
explanation.
Nevertheless, findings described previously have potential clinical
importance. Ethnicity has been considered an important variable to be
taken into account in the process of diagnosis and treatment, as well as
in the development of more specific measures for different ethnicities.
From a clinical perspective, ethnicity seems to affect perception
and responses to pain, and seems to moderate coping strategies,
relationship with health professionals and even seeking health care.
103
However, it should be considered that evidence for this is scarce in this
field.
To shed more light on the possible role of ethnic differences, ethnic
features should be taken into account when considering chronic pain
models or treatments developed in different cultures.
104
2.5 Psychological Assessment
In the previous sections the role of psychosocial factors in chronic
pain has been described. Due to the role of psychosocial factors in
chronic pain, psychological assessment of chronic pain patients has been
recognised as an essential part of the diagnostic process. Turner and
Romano (1999) have argued that defining and assessing these factors is
critical to designing effective treatment for people with chronic pain.
2.5.1 Psychological Assessment: Indications and Aims
In most instances, a psychological evaluation of people with
chronic pain does not intend to establish a diagnosis of the cause of pain.
Indeed, psychological evaluation is usually a part of a multidimensional
assessment, which aims to understand the role of several factors in the
development, modulation and maintenance of chronic pain.
According to Tollison and Hinnant (1996), although an assessment
is frequently requested when symptoms are greater than would be
expected
from
the
physical
examination,
there
are
other
better
indications to request a psychological assessment. A psychological
assessment is indicated when pain interferes significantly with the
patients’ ability to perform normal activities in many spheres (e.g. social
life, work), when there are signs of psychological distress, excessive use
of medications or alcohol, and repeated/extensive use of the health care
105
system (Tollison and Hinnant, 1996). A psychological evaluation may also
be indicated when patients are moderately or severely disabled.
To Turner and Romano (1999), a psychological assessment is
useful to identify specific psychological and behavioural factors involved
in pain, suffering and disability and poor response to treatment.
According to Gamsa (1994) the aims of a psychological assessment are
to determine: whether psychological factors play a role in precipitating,
exacerbating or perpetuating pain, to assess whether psychological
disturbance is a cause or an effect of chronic pain, to determine whether,
and which type of intervention is indicated, and to establish rapport with
the patient, offer support and answer questions. To Turk and Okifuji
(2003) a psychological assessment of chronic pain patients intends to
establish a diagnosis, decision making and treatment planning, evaluation
of change in symptoms, impact of treatment, prediction of response to
treatment and program evaluation.
Different
theoretical
approaches
could lead to different aims for a psychological assessment of chronic
pain patients. For example: from a Behavioural perspective it is essential
to evaluate pain behaviour reinforcement, while in a Gestalt approach to
understand how chronic pain is integrated to patients identity may be a
key issue in the assessment.
Despite some divergences, there is a degree of consensus that the
main aim of psychological assessment is to detect cognitive, affective and
behavioural factors that may be contributing to pain, disability and
distress to assist decision-making and guidance in treatment (Gamsa,
106
1994; Tollison and Hinnant, 1996; Turk and Okifuji, 2003; Turner and
Romano, 1999).
2.5.2 Psychological Assessment Methods
Pain is a subjective and multidimensional experience. Therefore, by
its nature, most pain dimensions can only be assessed indirectly (Turk
and Melzack, 2001). The measurement of pain dimensions is fundamental
for the comprehension of pain mechanisms, as well as for the evaluation
of methods to treat it.
The most common methods to assess chronic pain patients'
experience
regarding
psychosocial
interviews,
psychological
testing
aspects
with
are
semi-structured
self-report
questionnaire,
behavioural analysis or observation, and health measures. This literature
review does not intend to explore all types of assessment, but each
method will be briefly described.
Semi-structured interview is the most common method to assess
cognitive and affective aspects of the patient. Broadly, an interview
should cover several dimensions of pain: pain intensity and description,
aggravating
factors,
relevant
medical
history,
past
and
current
treatment, history of drug and alcohol use, history of psychiatric
disturbance or emotional trauma, emotional and cognitive factors,
disability, working and compensation issues, sleep and daily activities,
social aspects and motivational factors (Jamison 2004). There are other
topics that may be included in an assessment of people with chronic pain,
107
according to the setting, patient characteristics, types of intervention and
theoretical models.
Interviews are a useful method of assessing patients’ history and
subjective aspects, as well as to check and integrate information. They
are a rich source of information, are flexible and adaptable to the needs
of the patient and may assess multiple pain domains at the same time
(Newton-John 2003). However, they are time consuming; may have
excessive bias due to interviewer interpretation, lack of objectivity and
difficulty of comparing obtained information with other pain patients
(Sardá and Angelotti 2004).
Behavioural analysis and observation is a further step in order not
to rely only on subjective information. In general, behavioural analysis
intends to observe manifestation of how patients respond to pain, which
may include posturing, limping, grimacing and other pain behaviours, as
well as use of medication. One of its main goals is to identify what factors
might be perpetuating pain behaviour (Jamison, 2004). From some
perspectives this method of assessment is essential, as it may provide a
direct
measure
of
functioning
and
a
comprehension
reinforcing
environmental factors, providing important information for targeted
interventions.
However, there is some criticism of behavioural analysis, due to
the excessively artificial nature of this method, which may produce
unreliable information, as well as lack of standardisation (Asghari and
Nicholas, 2001).
108
Assessment of health care use has been a recent measure to
assess chronicity and disability. This is aimed at quantifying the use of
the health care system, number of sick days, use of pain-related
medications, among other aspects (Newton-John, 2003). As health care
use is a direct measure, this form of evaluation is promising, and may
contribute as an outcome measurement of chronicity and disability.
Psychological measures have been widely used in the assessment
of chronic pain. There is a wide range of self-report questionnaires to
evaluate cognitive, affective, personality and environmental factors.
Psychological tests are usually easy to administer and to score. Beside
this, test results allow clinicians and researchers to make comparisons
among different individuals, as well as various populations. Furthermore,
test scores facilitate longitudinal follow-up and research, as well as a
quantitative evaluation of interventions (Jensen, 2003; Turk and Melzack,
2001).
On the other hand, there is some criticism regarding their potential
for response bias and for not being suitable for all patients, specially
people with low educational levels, children, aged and handicapped
(Newton-John, 2003). Another main criticism of psychometric measures
is due to its psychometric properties. Some tests frequently used in the
psychological assessment of chronic pain patients were not developed for
this population, which makes these measures very unreliable and not
valid (Jamison 2004; McDowell and Newell 1996). Beside this, construct
validity, test-retest reliability and sample bias are other problematic
features of several psychological measures (Jensen, 2001). Once it is
109
guaranteed
that
the
chosen
psychological
measures
have
strong
psychometric properties, it can be an important device in the assessment
of patients with chronic pain.
According to Grenn (1985), methods for data collection should
meet a few criteria: i. Provide information about cognitive, behavioural,
emotional and socio-environmental factors of the target problem; ii. Be
quantifiable to be treated statistically; iii. Be sensitive to detect even
small
changes
in
the
target
problem;
and
iv.
Have
adequate
psychometric properties; specially reliability and validity.
These are important criteria to be kept in mind to ensure and
enhance the quality of psychological assessment and thus provide a
better foundation for the comprehension of chronic pain, other aspects
could be observed.
The evidence presented suggests that a few principles should also
be
observed regarding chronic
pain patients’
assessment. Firstly,
psychological assessment of people with chronic pain must always be
multidimensional
due
to
the
characteristics
of
this
phenomenon.
Secondly, assessment methods should be determined by the assessment
goals. Third, assessment methods should be complementary (e.g.
interviews and psychological tests). Fourth, it must be kept in mind that
interventions are largely dependent upon the accuracy and sensitivity of
the evaluation methods. Thus, selecting an appropriate, reliable and valid
method is determinant to achieving an adequate comprehension of the
aspects involved in chronic pain, as well as to design efficacious
interventions.
110
Evidence suggests that psychological factors play an important role
in disability and emotional adjustment; therefore they should be included
in the evaluation of chronic pain patients. Furthermore it is recognised
that psychological testing is a useful method as a part of the
psychological assessment. However, there is a lack of psychological
measures developed for the assessment of chronic pain patients in Brazil
(Sardá et al. 2005).
111
2.6. Final Comments
Based on the evidence gathered this series of studies is based on
the hypothesis that the biopsychosocial perspective of pain is applicable
to a Brazilian chronic pain population.
This series of studies aim to:
1) Validate a number of measures on cognitive and affective
domains of chronic pain.
2) Test whether the relationships between the validated
measures are consistent with current biopsychosocial
models of pain.
3) To compare two chronic pain samples from different
cultures
and
countries
on
the
same
measures,
specifically a Brazilian and an Australian sample.
Providing satisfactory validation for the proposed measures will
collaborate to enhance resources regarding psychological measures
available to the Brazilian chronic pain population. This series of studies
may also help to improve research possibilities, especially the ability to
collaborate with research in other countries. Furthermore, this series of
studies
may
confirm
the
evidence
published
in
the
international
literature.
112
CHAPTER THREE
Study One: Psychometric Properties of Measures of Disability, Pain SelfEfficacy Beliefs,
Catastrophising, Acceptance
and Depression in
a
Brazilian Population with Chronic Pain.
3.1 Introduction
In the previous chapters chronic pain definitions and pain
prevalence were described. Overall, it was concluded that although there
is still some divergence on the definition of chronic pain, there is strong
evidence suggesting that there is a high prevalence of chronic pain
among most of societies and that chronic pain often has a high
psychosocial and economic impact. However, it was also noted that there
is
considerable
variance
in
the
impact
of
chronic
pain
between
individuals.
Biopsychosocial perspectives attempt to account for this variance
by exploring the role of psychosocial factors interacting with biological
factors in the development and maintenance of chronic pain and its
impact on a person’s life. Evidence was found that some psychological
factors, such as catastrophising, self-efficacy, acceptance and depression
may mediate the relationship between chronic pain, disability and
emotional adjustment (e.g. Linton, 2000; Keefe et al., 2004).
113
Based on this evidence, the assessment of psychological factors has
been recognised as an integral part of the assessment of chronic pain
patients.
There are different methods used to conduct a psychological
assessment. Standardised psychological measures are generally widely
recommended for this purpose and are the most commonly used
assessment method. There are literally dozens of different measures
used to assess pain dimensions; however this literature review identified
only sixteen instruments currently being used for this purpose in Brazil
(Sardá et al. 2005).
Among those instruments, only about half have been validated in a
Brazilian chronic pain population. These are: McGill Pain Questionnaire –
MPQ (Pimenta and Teixeira 1997), the Beck Depression Inventory – BDI
(Cunha 2001), the Survey of Pain Attitude – SOPA (Pimenta and Cruz
2006), the Short Form Health Survey (SF-36) (Ciconelli et al. 1998), the
Roland and Morris Disability Questionnaire – RMDQ (Nusbaum et al.
2001), the Coping Strategies Questionnaire – CSQ (Portnoi et al. 2005),
the Chronic Pain Self-Efficacy Scale – CPSS (Salvetti and Pimenta 2005)
and Numeric or Verbal Pain Rating Scales. However, relatively few
studies have been reported with these validated measures in Brazil.
Not surprisingly, a number of other dimensions or constructs that
seem to be important in relation to pain are not assessed by these
instruments. For example, the role of acceptance, which is a novel
concept in the chronic pain field, has become the focus of systematic
research only recently. To date, the only studies examining this construct
114
have been from North America (McCracken 1999), Europe (McCracken et
al. 2004b) and recently in Australia (Nicholas and Asghari 2006). The
extent to which that research is applicable to chronic patients in Brazil is
presently unknown. Furthermore, the construct validity of some of the
above measures to chronic pain patients is questionable (e.g. the
presence of somatic items on the BDI may cause a bias in the
assessment of depression in patients with chronic pain) (Pincus and
Williams 1999).
In addition, while there has been some Brazilian research on the
constructs of catastrophising (Portnoi et al. 2005) and self-efficacy
(Salvetti and Pimenta 2005), this has been limited to a few studies and
clearly requires further exploration. It might also be worthwhile to
investigate
these
constructs
with
different
measures
to
test
the
generalisation of the earlier findings. Different measures of apparently
the same construct could result in different findings, providing different
perspectives. For example, in relation to self-efficacy measurement, the
Chronic Pain Self-Efficacy Scale (Anderson et al., 1995) does not ask or
emphasise that the patient should consider the fact of being in pain when
answering about his/her self-confidence to execute some tasks. This can
be contrasted with another pain self-efficacy measure, the Pain SelfEfficacy Questionnaire – PSEQ (Nicholas 1989; Nicholas 2007), which
does take pain into account when considering the confidence in
performing tasks.
In both cases, comparisons of studies that apparently investigate
the same construct will clarify the importance of these constructs for
115
disability, as well as, the validity and reliability of these measures to a
Brazilian population.
In general, due to the lack of studies with psychological measures
for the Brazilian population suffering from chronic pain, further studies
are needed to test hypotheses generated by previous research. To
confirm theoretical psychological models of chronic pain generated in
other countries, and to provide a wider range of validated measures. This
study should contribute to improve the assessment and treatment of
Brazilian chronic pain patients.
Accordingly, the purpose of this study is to examine the validity
and reliability of a range of psychological instruments internationally used
on a Brazilian population with chronic pain.
Where no Portuguese translation of the instruments was available,
the first task was to develop acceptable translated versions.
116
3.2 Method
3.2.1 Subjects
Over a period of four months (from March to June 2005), data
were collected from 348 subjects with chronic pain attending pain clinics
or similar facilities in the public and private sector. The subjects should
be considered to represent a convenience sample of patients attending
pain clinics, selected on the basis of specified criteria.
Thirty seven subjects (11%) were excluded after applying inclusion
and exclusion criteria. Data presented on Results are from 311 subjects,
which was the final sample.
3.2.2 Inclusion criteria
•
Patients having chronic pain for a period of more than 3 months over
the past 6 months on most of the days;
•
Age superior to 18 and inferior to 80;
•
Having four or more years of formal education;
•
Willing to participate in the study and spend 40 minutes completing
questionnaires.
117
3.2.3 Exclusion criteria
•
Having cancer pain2;
•
Having a diagnosis of a major psychiatric disorder, such as psychoses
or dementia;
•
Questionnaires with more than 10% of missing items.
3.2.4 Procedure
In general our procedure consisted of two parts, (i) translation
(into Portuguese) and adaptation of measures and (ii) data collection.
The procedure for data collection is described below, while the procedure
regarding the translation of the measures is described in the measure
section.
Brazilian chronic pain patients attending pain institutions willing to
participate in this study were referred by the main physician to the
researcher who provided necessary explanation for the patients, a written
consent form and the measures to be completed. Questionnaires took
approximately 40 minutes to be completed, after that they were checked
by the researcher to ensure there were no missing items. Medical/clinical
data then were collected from the patients’ medical files.
2
In comparison to those with chronic non-cancer pain, there are often other issues involved
with cancer pain (e.g. survival, aversive treatments, beliefs) which may influence the
assessment of variables like depression. To avoid these issues these patients were
excluded from the studied sample.
118
Data were collected in nine different institutions in the South and
South-East regions of Brazil (listed in Appendix I).
All the ethical procedures were observed, including information
about the purpose of the research and patients’ rights3. No change in
treatment occurred.
3.2.5 Measures
In previous sections a number of measures of disability, selfefficacy, depression, acceptance and catastrophising have been described
and examined. Since the psychometric properties of these measures
were good, other criteria influenced scale selection.
The data collected in a Brazilian population in this study will be
compared with a chronic pain patient sample attending the Pain
Management and Research Centre (PMRC) - Royal North Shore Hospital
(Study 3). Thus, since psychometric properties were adequate, being
used at the Pain Management and Research Centre was an important
consideration in scale selection.
All the measures used in this studies have not been previously
validated to the Brazilian population, except the back pain version of the
Roland and Morris Disability Questionnaire (Nusbaum et al. 2001).
The translations of the measures were based on a back-translation
method (Guillemin et al. 1993) which involved reviewing, translating and
3
The consent form is in appendix II, and the ethic committee approval on appendix III.
119
adapting the measures from English into Portuguese (and back to English
again).
A preliminary cross-cultural adaptation was necessary because
some of the words used to express feelings or situations would not make
sense or would lose their meaning if they were translated literally to
Portuguese (e.g. “I can’t go on any more” was translated as “Eu não
consigo mais continuar”).
After the measures were translated and adapted to Portuguese by
the researcher, they were given to three Brazilian examiners who are
involved with health psychology and who speak English as their second
language to be translated independently back to English.
After that, the three translations were compared and no important
divergence was found except for a few minor semantic differences (i.e.
85% of the items were translated in the same way by the reviewers) that
were resolved by discussion between the researcher and reviewers. Once
there was agreement between the researcher and reviewers, that the
initial
translations
were
satisfactory,
a
final
back
translation
to
Portuguese was carried out. Overall, the main problems in translation
related to a few semantic issues. For example, in some sentences instead
of using “my pain” only “pain” was used, in other sentences the order of
words were changed to make the grammar more appropriate in
Portuguese. Apart from these minor changes, the Portuguese versions of
the tests were kept as close as possible to the original English version
without compromising its comprehension and being adequate to a
Portuguese reader.
120
The last back translation was then compared with the original
translation done by the researcher. A high rate of concordance (i.e. in
90% of the items there were no major changes) occurred between the
measures.
All the psychometric properties, characteristics, scoring procedures
and relevant evidence of the chosen measures have already been
described in the literature review section. Thus the following measures
used in this series of studies and listed bellow will not be described again.
The Roland and Morris Disability Questionnaire – RMDQ (Roland and
Morris 1983), the Pain Self-Efficacy Questionnaire - PSEQ (Nicholas
1989), the PRSS - Catastrophising Scale (Flor et al. 1993), the Chronic
Pain Acceptance Questionnaire - CPAQ (McCracken et al. 2004b), and the
DASS - Depression scale (Lovibond and Lovibond 1993), a socio
demographic and a clinical inventory were used to collect data on these
dimensions.
Socio demographic questionnaire
The
socio-demographic
questionnaire
collected
information
regarding: age, gender, marital status, level of education, profession and
working status.
121
Clinical Inventory
The clinical inventory had question regarding: pain site, clinical
diagnosis, pain intensity and duration (assessed by a numerical and
verbal rating scale), medication usage, type of intervention, and other
major health problems.
3.3 Aims of study
The major aim of this study was to assess the psychometric
properties of a pain-related disability, depression, pain-related selfefficacy beliefs, catastrophising and acceptance questionaries, especially
to test the validity and reliability of these measures in a Brazilian chronic
pain population.
3.4 Statistical analyses
A number of statistical procedures were conducted to test the
psychometric properties of these measures, including:
i. Descriptive statistics (means, standard deviations, medians, ranges);
ii. Reliability;
iii. Validity.
Reliability
was
assessed
using
split-half
reliability
(Pearson
correlation) and internal consistency (Cronbach's alpha) calculations.
Validity was assessed by analysis of construct and criterion
validity. Construct validity was examined using convergent validity (item-
122
scale correlations) (Hammond 2000), discriminant validity (correlation
between different scales or measures) and principal components analysis
– PCA (items factors loading, communalities). Criterion validity was
assessed comparing mean differences between groups on education level
and working status (Anastasi and Urbina 1997). The analysis of criterion
validity was based on the hypothesis that some differences between
groups should occur on some scales (e.g. work status and scores on
disability), but not between some other variables (e.g. educational level
and depression).
All the analyses were conducted using the SPSS for Windows
package, version 14.0.
123
3.5 Results
Although initially there were 348 subjects in the sample, 37
subjects did not meet the inclusion and exclusion criteria. Data presented
below is from the final sample of 311 subjects. However to evaluate the
quality of the data and search for any significant differences between the
total sample and the final sample, the two groups were compared with
each other.
There were no significant differences between the two groups
regarding gender, age, level of education, employment status, pain site
and mean scores in all the measures (p≤ 0.05). In the excluded subjects
group the pattern of missing items in the measures were similar to the
final sample. However, most of the excluded questionnaires came from
one pain clinic in southern Brazil where the procedure for data collection
was different than the one used in the other institutions. In this clinic the
questionnaires were given to the subjects to be completed at home and
returned on the patients’ second appointment. In another pain clinic
located in the South East region of Brazil that also treats chronic pain
patients with cancer, questionnaires completed by these patients were
excluded from the final sample.
Due to the fact that the researcher did not collect all the data (i.e.
in 3 pain centres data was collected by research assistant) it is not
possible to specify how many patients were approached, but overall most
of the patients who were approached and met the inclusion criteria were
willing to participate in the study.
124
Table 3.1 Socio-demographic characteristics of the study sample
Socio-Demographic Characteristics
No. (%)
Age group (years)
18 - 30
39 (12.5)
31 - 42
61 (19.6)
43 - 54
105 (33.8)
55 - 66
69 (22.2)
67 - 81
37 (11.9)
Mean (SD)
48.9 (14.06)
Gender
Male
Female
81 (26.0)
230 (74.0)
Marital status
Single
Married
Separated, divorced or widowed
55 (17.7)
200 (64.3)
56 (18.0)
Educational Level
4 to 8 years (primary level)
9 to 11 years (secondary level and/or technical)
Higher level of education (i.e. university)
101 (32.5)
89 (28.6)
121 (38.9)
Employment status (no = 304)
Working
157 (51.6)
Partially working
22
Unemployed due to pain
125 (41.1)
(7.2)
Region
South
164 (52.7)
South-east
147 (47.3)
The age distribution of the sample was normal, with a higher
concentration in the 43 to 54 years group. There were more females than
males (74% to 26%, respectively). Most of the subjects were married,
and in the separated group, 39 (12.5%) subjects were separated or
divorced and 17 (5.5%) were widowed. The sample’s education level was
125
evenly distributed, with a slightly higher proportion of subjects with
tertiary education. Most of the subjects were working, but a substantial
minority (41%) was not working due to pain.
Data
collected
in
the
southern
region
were
gathered
in
Florianopolis - Santa Catarina in the following institutions: Rheumatology
Ward and Acupuncture Ward at the University Hospital - UFSC, IPE-IMTC
(Acupuncture Clinic), Nidi-Neuroscience Pain Clinic and Santa Clara Clinic.
Data collected from the south-eastern region were gathered in São Paulo
city, in the pain clinics of the following institutions: 9 de Julho Hospital,
AC Camargo Hospital, State Public Workers Hospital, and at the Fundão
University Hospital – UFRJ in Rio de Janeiro state. Most of the data were
collected from patients attending public services (n=164, 52.6%).
On Table 2 data related to the clinical characteristics of the sample
are presented.
126
Table 3.2 Clinical characteristics of the study sample
Clinical Characteristics
No. (%)
Pain site
Head, face, neck
36 (11.6)
Cervical, shoulders and upper limbs
48 (15.5)
Thoracic and abdominal
14
(4.5)
Back or spine alone
16
(5.1)
Lower limbs
22
(7.1)
5
(1.6)
Lower back and lower limbs
30
(9.6)
Two or more major sites
140 (45.0)
Pelvic, anal, perineal and genital
Pain duration
From 3 months up to 1 year
28 (12.2)
1 to 3 years
60 (19.3)
3 to 5 years
87 (28.0)
6 to 9 years
39 (12.5)
Up to 10 years
87 (28.0)
Pain intensity (average during past week according a NRS)
1 to 4 (mild)
70 (22.5)
5 to 6 (moderate)
94 (30.2)
7 to 10 (severe)
147 (47.3)
Stress intensity due to pain (average during past week
according a NRS)
0 to 4 (mild)
60 (19.3)
5 to 6 (moderate)
64 (20.6)
7 to 10 (severe)
187 (60.1)
Undergone treatments
Medication
256 (82.4)
Conservative (i.e. physiotherapy, massage)
78 (25.0)
Invasive (i.e. nerve blocks, radiofrequency, surgery)
81 (26.0)
Types of medication
Corticoid-steroids + analgesics
20
(6.5)
Analgesics + anti-depressive, sedative-hypnotics or anti-convulsants
32 (10.3)
Combination of three categories of medication
54 (17.4)
Analgesics
74 (23.8)
Anti-depressive, sedative-hypnotics or anti-convulsants
76 (24.4)
127
In relation to the pain site, a substantial proportion of subjects
(45%) had pain in two or more sites. The next most common pain site
was the cervical region/shoulders/upper-limbs (15.5%), followed by pain
in the back or lower back region associated or not with irradiation to the
lower limbs (14.7%). Pain in the lower limbs (7.1%) was described as a
separated category because it usually consisted of pain in the knees and
joints and was usually associated with osteoarthritis. Mean pain duration
was 4.3 years, but a large number of subjects had pain for over 3 years
(68.5%) and 28% of the subjects had had pain for over 10 years. Pain
intensity was measured on a numerical rating scale (0 to 10 associated
with the words no pain and the most severe pain on the extremities) and
categorized as mild pain (1 to 4), moderate pain (5 to 6), and severe
pain (7 to 10) (Jensen et al. 2001a). There was a small prevalence of
mild pain intensity (22.5) and a large number of subjects (47.3%)
reporting severe pain, mean pain intensity was 6. Furthermore, the
majority of subjects (60.1%) reported severe stress due to pain (using a
0 to 10 numerical scale to rate stress) (i.e. 1-4, 5-6 and 7-10), mean
stress intensity was 6.9 (SD=2.9).
The majority of subjects (82.4%) were taking medications for their
pain and nearly half reported having had conservative procedures (25%)
such as physiotherapy, osteopathy and massage or have done an
invasive procedure (26%) (e.g. radiofrequency lesion, nerve blocks).
In relation to the type of medication, subjects in the corticoidssteroids + analgesic group could be also using immunosuppressors or
quimiotherapics and in general were being treated for arthritis. The
128
second group labelled analgesics + anti-depressive, sedative-hypnotics or
anti-convulsants, could be taking a muscle relaxant, a simple analgesic or
a compound analgesic associated with a psychoactive medication. The
third group was using a combination of three or more medications,
usually of analgesics, opioid and psychoactive drugs. The fourth group
was taking single muscle relaxant, simple analgesic, compound analgesic,
anti-inflammatory or a combination of them, and the fifth group was
taking anti-depressive, sedative-hypnotics or anti-convulsants or a
combination of them. The most used psychoactive medication was
Amitriptyline and Carbamazepine.
Prevalence of co-morbidities was also investigated. The most
common diseases in this population were hypertension (28%), followed
by
psychiatric
disorders
(18%,
mainly
depression),
endocrine
dysfunctions (10%) and diabetes (5%).
Statistical analyses were run to analyse the distribution of the
responses for each measure and a number of other variables (e.g. age,
pain intensity). These indicated normal distributions in each case, with
skewness and kurtosis values not reaching 1.0 (Tabachnick and Fidell
2001). Furthermore no clear outliers were identified either. Thus, no
statistical
transformation
to
normalise
the
data
was
necessary.
129
Table 3.3 Descriptive statistics for all the measures
Questionnaires
Means (SD)
Skewness Kurtosis Floor (%) Ceiling (%) Score range
Roland and Morris Disability Questionnaire
12.03
(6.21)
-0.02
-1.0
1.0
1.9
0-24
Pain Self-Efficacy Questionnaire - PSEQ
34.84 (14.08)
-0.28
-0.63
0.3
1.0
0-60
DASS - Depression Scale
14.03 (12.02)
0.79
-0.56
7.7
1.6
0-42
PRSS - Catastrophising Scale
2.38
(1.38)
0.14
-0.94
2.3
4.5
0-5
Chronic Pain Acceptance Questionnaire
60.20 (18.11)
-0.30
0.13
0.3
0.6
0-120
Activity Engagement Scale
39.89 (14.07)
-0.42
-0.37
0.3
1.0
0-66
Pain Willingness Scale
20.21 (11.08)
0.18
-0.54
2.6
0.3
0-54
Means and standard deviations for the Brazilian versions of each questionnaire were compared with those
obtained in the original standardisation excepted for the RMDQ that was compared with a Brazilian standardisation for
low back pain patients (Nusbaum, 2001).
130
Tables 3.4 Comparison between mean scores of the Brazilian sample and the
original questionnaire
Questionnaires
t-test of
Means (SD)
Means (SD)
Brazilian
Original
sample
sample
12.03 (6.21)
14.30 (7.47)a
1.62
Pain Self-Efficacy Questionnaire
34.84 (14.08)
23.50 (13.1)b
4.68*
DASS - Depression Scale
14.03 (12.02) 15.15 (12.22)c
significance
Roland Morris Disability Questionnaire
Catastrophising Scale
2.38
(1.38)
1.23
2.03 (1.22)d
3.18*
Chronic Pain Acceptance Questionnaire
60.20 (18.11)
56.3 (20.4)e
2.32*
Activity Engagement Scale
39.89 (14.07)
33.3 (13.2)e
4.25*
Pain Willingness Scale
20.21 (11.08)
13.8 (7.9)e
7.91*
* Significant mean differences at a expected t is 1.96, p=0.001
a (Nusbaum et al. 2001), b (Nicholas 2007), c (Taylor et al. 2005), d (Flor et al. 1993),
e (McCracken 1999)
T-tests results indicated a significant difference between the PSEQ
mean score (Nicholas 2007) and the PSEQ mean score on the Brazilian
sample, the CPAQ Brazilian mean score and its sub-scales mean score
were also significantly different when compared to the published
standardisation score (McCracken et al., 1999). Mean score on the PRSS
- Catastrophising scale Brazilian version was also significantly different
when compared to the original version (Flor et al., 1992). In all the
measures described above the Brazilian samples had higher mean score
when compared with the original sample.
131
On the other hand, mean scores of the RMDQ general version
(used in this study) and the preliminary standardisation with back pain
patients done in a Brazilian sample (Nusbaum et al., 2001) did not differ.
However this validation of the RMDQ for low back pain in the
Brazilian population had only 30 subjects. Mean score on the DASS –
Depression scale Brazilian version also did not differ significantly from an
Australian chronic pain patient sample (Taylor et al. 2005).
Reliability
characteristics
of
these
translated
measures
are
presented bellow.
Table 3.5 Internal consistency and split-half correlation of the measures
Questionnaires
Number
of items
Internal
Correlation between
consistency
forms (split-half)
Cronbach’s α
Pearson coefficient
RMDQ
24
0.90
0.82
PSEQ
10
0.90
0.76
DASS - Depression Scale
14
0.96
0.93
9
0.89
0.74
CPAQ
20
0.78
-
Activity Engagement Scale
11
0.85
0.73
9
0.76
0.57
PRSS - Catastrophising Scale
Pain Willingness Scale
All scales had a Cronbach α higher than 0.70, which suggests an
adequate degree of internal consistency for research purposes (Jensen
2003). The RMDQ, PSEQ, Depression scale and the Catastrophising scale
all had a Cronbach α at a superior level (or nearly 0.90), which indicate
132
an excellent internal consistency, which confirm the reliability of these
measures (Nunnaly and Bernstein 1994). According to Jensen (2003)
Cronbach α values above 0.90 indicate an adequate degree of internal
consistency for clinical purposes as well.
Due to the fact that the CPAQ has two scales, split half correlation
was run for each scale independently.
On the depression scale the first half was composed of items 1, 3,
6, 9, 10, 13 and 14, which is consistent with the Depression scale short
form (Henry and Crawford 2005). In both cases when an analysis was
run using other split half methods results were similar. For the other
questionnaires and scales split-half correlation the researcher choose to
use the default mode of the SPSS 14.0 program, which selects the first
half of the scale items and compares them with the second half items.
Pearson correlation coefficients for the split-half forms of all the
questionnaires were in a moderate to high range for most of the
measures, except for the Pain Willingness scale split-half correlation
(0.57) (Anastasi and Urbina 1997).
Although analysis of reliability using internal consistency coefficient
have shown an adequate internal consistency for all the instruments,
split-half correlation coefficients indicate a lack of consistency for the Pain
Willingness scale. To examine this feature and assess the validity of the
measures further analysis including Principal Component Analysis (PCA)
was run.
Construct validity was examined through item-scale correlations,
principal component analysis, and correlation between scales. Criterion
133
validity was assessed comparing mean differences between groups on
education level and working status.
Table 3.6 Item-scale correlation for the CPAQ
Items
Activity Engagement scale
Pain Willingness scale
1
0.69**
0.24
2
0.76**
0.46
3
0.35**
- 0.16**
4
- 0.04
0.60**
5
0.53**
0.08
6
0.76**
0.08
7
- 0.10
0.44**
8
0.63**
0.07
9
0.78**
0.13*
10
0.51**
0.10
11
- 0.10
12
0.67**
13
- 0.00
0.65**
14
0.10
0.70**
15
0.66**
0.48**
0.07
0.04
16
0.03
0.64**
17
0.01
0.53**
18
0.11*
0.66**
19
0.61**
- 0.12*
20
Activity Engagement scale
Pain Willingness scale
0.08
0.51**
1
0.51
0.51
1
Activity Engagement scale: items 1, 2, 3, 5, 6, 8, 9, 10, 12, 15, 19
Pain Willingness scale: items 4, 7, 11, 13, 14, 16, 17, 18, 20
* level of significance:0.05
**level of significance: 0.01
Most correlations between items and the relevant scale were
moderate or nearly in this range (Pearson correlation range 0.44 to 0.78
at a p< 0.01), except for item 3 which had a correlation of 0.35 (items
134
were not adjusted). Also a moderate inter-correlation between the scales
(0.51) suggests adequate convergent validity of the scales.
The next phase of these investigations involved conducting
principal component analysis to explore the factor structure of each
measure (see Table 7 for the CPAQ results).
Factor loadings, communalities (h²), eigenvalue and percentage of
variance indicate the existence of a 5 factor solution for the CPAQ. Since
correlations among some factors were lower than 0.32 they were
submitted to a varimax rotation (Tabachnick and Fidell 2001). This model
accounted for 57% of variance and five main factors were identified using
the eigenvalue greater than 1 criterion. All items had a moderate to high
loading on its factors (range from .50 to .77). The first factor retained
seven of the eleven original items reported by McCracken (1999), the
second factor had six of the original nine items, while the other seven
items loaded to factor 3, 4 and 5, although item three emerged as a
single-item factor. Factors 1 and 2 accounted for the higher percentage
of variance, while factor 5 (item 3) should be reconsidered.
Correlations between factors are presented in the last table.
Internal consistency analysis for a 4 factor solution for the CPAQ is
presented in Table 8.
135
Table 3.7 PCA of the CPAQ factors loading and communalities for a 5 factor solution
Item number and description
Factor 1: Activity Engagement (AC)
(12) Despite the pain, I am now sticking to
a certain course in my life
(15) Even when my pain increases, I can
still take care of my responsibilities
(9) I lead a full life even though I have
chronic pain
(8) There are many activities I do, even
when I fell pain
(1) I am getting on with the business of
living no matter what my level of pain is
(2) My life is going well, even though I
have chronic pain
(6) Although things have changed, I am
living a normal life despite my chronic pain
Factor 2: Pain Willingness (PW)
(17) I avoid putting myself in situations
where my pain might increase
(20) I have to struggle to do things when I
have pain
(13) Keeping my pain level under control
takes first priority whenever I'm doing
something
(4) I would gladly sacrifice important
things in my life to control this pain better
(14) Before I can make any serious plans,
I have to get some control over my pain
(18)My worries and fears about what pain
will do to me are true
Factor 3:Thought Control
(7) I need to concentrate on getting rid of
my pain
(11) My thoughts and feelings about pain
must change before I can take important
steps in my life
(16) I will have better control over my life
if I can control my negative thoughts about
pain
Factor 4:Chronicity
(5) It's not necessary for me to control my
pain in order to handle my life well
(10) Controlling pain is less important than
any other goals in my life
(19) It's a relief to realise that I don't have
to change my pain to get on with my life
Factor 5:Accept suffering
(3) It's OK to experience pain
Eigenvalue
Percentage variance
CPAQ
F1
original
subscales
F2
F3
F4
F5
h²
AC
.76
-.28
.08
.04
.07
.60
AC
.75
.07
-.13
.04
-.15
.62
AC
.73
.05
0.10
.29
.14
.65
AC
.72
-.02
.02
.02
-.14
.54
AC
.70
.05
-.04
.13
.18
.55
AC
.69
.04
.03
.31
.26
.65
AC
.64
.06
.03
.42
.20
.63
PW
.27
.73
-.07
-.06
-.04
.55
PW
-.06
.72
-.02
.19
.24
.62
PW
-.00
.60
.30
.02
-.21
.50
PW
.06
.57
.16
-.12
-.43
.56
PW
.04
.54
.47
.16
-.10
.56
PW
.17
.50
.42
-.05
-.04
.47
PW
-.13
-.03
.67
.05
-.03
.48
PW
.11
.06
.67
-.24
.03
.53
PW
.01
.33
.63
.07
-.03
.51
AC
.16
.08
.03
.75
.13
.62
AC
.28
.10
-.06
.63
-.32
.59
AC
.40
-.17
-.10
.54
-.01
.50
AC
.25
-.09
-.04
-.04
.77
.68
4.72 3.24 1.35
23.61 16.23 6.75
1.08
5.40
1.01
5.09
136
Table 3.8 Means (SD) and internal consistency for a 4 factor solution
Factor description
Factor 1
Mean (SD)
27.40 (10.30)
Internal
Mean inter-
consistency
item
Cronbach’s α
correlation
0.87
0.48
Factor 2
11.36
(8.05)
0.75
0.32
Factor 3
8.94
(4.63)
0.50
0.24
Factor 4
8.06
(4.84)
0.58
0.31
Only factors 1 and 2 had a Cronbach α higher than 0.70, which
suggests an adequate internal consistency. Although Cronbach α for factor
3 and 4 were in the medium range, it suggests a weak correlation among
the items and a low internal consistency (Jensen, 2003). Low mean interitem correlation among the items in all factors, except for factor 1, which
has a moderate correlation (0.48), also confirms the results presented
earlier regarding the internal consistency of the CPAQ and its scales.
In the next tables principal components analysis results from the
PSEQ, Catastrophising and Depression scales are presented.
137
Table 3.9 PCA of the PSEQ factors loading and communalities for a 1 factor
solution
Item number and description
F1
h²
(8) I can still accomplish most of my goals in life, despite the pain.
.83
.69
(1) I can enjoy things, despite the pain.
.81
.66
(9) I can have a normal lifestyle, despite the pain.
.81
.65
(10) I can gradually become more active, despite the pain.
.80
.64
(6) I can still do many of the things I enjoy doing such as hobbies
.77
.60
.76
.58
.73
.54
(4) I can cope with my pain in most situations.
.72
.52
(3) I can socialise with my friends and family members as often as I
.67
.44
.44
.20
or leisure activities, despite the pain.
(5) I can do some form of work, despite the pain (work includes
housework, paid and unpaid work).
(2) I can do most of my household chores (e.g. tiding up, washing
dishes, etc.), despite the pain.
used to do, despite the pain.
(7) I can cope with my pain without medication.
Eigenvalue
5.53
Percentage variance
Principal
components
55.29
analysis
using
oblique
and
orthogonal
rotation and applying the eigenvalue greater than 1 criterion identified
the existence of only one factor. This factor accounts for 55.29% of the
total variance, high loadings (range from .72 to .83) in eight out of ten
items and median communalities on eight items confirms the existence of
only one factor on the Pain Self-Efficacy Questionnaire.
138
Table 3.10 PCA of the Catastrophising Scale factors loading and
communalities for a 2 factor solution
Item number and description
F1
F2
h²
(8) I can’t go on any more.
.98
-.09
.86
(9) This pain is driving me crazy.
.88
-.02
.76
(1) I cannot stand this pain any longer.
.86
-.03
.72
(7) This pan is killing me.
.76
.14
.73
(3) I need to take some pain medication.
.38
.17
.25
(4) This will never end.
-.08
.91
.74
(5) I am a hopeless case.
.00
.86
.75
(2) No matter what I do my pain doesn’t change.
.03
.78
.65
(6) When will it get worse again?
.15
.68
.61
Eigenvalue
4.91
1.17
Percentage variance
54.5
12.9
Factor 1 Rumination
Factor 2 Helplessness
Principal component analysis using oblique and orthogonal rotation
and applying the eigenvalue greater than 1 criterion identified the
existence of two factors, named rumination and helplessness. A two factor
solution accounted for 67.5% of total variance and most loading values
were above 0.70 (range .68 to .98), excepted for item 3 (0.38 and h²=
.25).
Considering
its
loading,
communalities
and
face
value
the
catastrophising scale appears to have more than one dimension, and
139
probably a 2 factor solution may be appropriated to describe the concept
of catastrophising.
Table 3.11 Mean (SD) and internal consistency for a 2 factor solution
Factor description
Mean (SD)
Internal
Mean inter-
consistency
item
Cronbach’s α
correlation
Factor 1: Magnification
2.78 (1.52)
.86
.55
Factor 2: Helplessness
1.87 (1.05)
.85
.58
A Cronbach’s α higher than 0.70 and nearly 0.90 in both factors
suggest an excellent internal consistency for this scale. A moderate interitem correlation (above 0.40) and a correlation of 0.59 between factor 1
and 2 also confirms the validity of this measure.
140
Table 3.12 PCA of the Depression Scale with factors loading and
communalities for a 1 factor solution
Item number and description
F1
h²
5. I felt that I had lost interest in just about everything.
.87
.76
7. I felt that life wasn’t worthwhile.
.87
.75
12. I could see nothing in the future to be hopeful about.
.85
.72
11. I felt I was pretty worthless.
.84
.70
10. I was unable to become enthusiastic about anything.
.83
.69
6. I felt I wasn’t worth much as a person.
.82
.68
9. I felt down hearted and blue.
.82
.67
3. I felt that I had nothing to look forward.
.81
.66
13. I felt that life was meaningless.
.80
.64
4. I felt sad and depressed.
.80
.64
8. I couldn’t seem to get any enjoyment out of things I did.
.79
.62
2. I just couldn’t seem to get going.
.77
.59
14. I found it difficult to work up the initiative to do things.
.73
.53
1. I couldn’t seem to experience any positive feelings at all.
.64
.40
Eigenvalue
9.10
Percentage variance
65.04
Principal component analysis using oblique and orthogonal rotation
and applying the eigenvalue greater than 1 criterion identified the
existence of only one factor for the depression scale of the DASS. This
accounted for 65.05% of total variance. High loadings (range .73 to .87)
141
for all items except for item one (.64) and high communality among
items confirms the existence of only one factor on the depression scale.
The results of comparisons made between different demographic
groups (using 1-way ANOVA) in an attempt to assess the criterion
validity of the measures are presented in the next tables.
Table 3.13 Comparison of mean score in questionnaires by educational
level
Questionnaires
4 to 8 years
9 to 11 years
Higher level
of education
of education
of education significance
mean (SD)
mean (SD)
mean (SD)
F
P
RMDQ
14.55 (6.31)
12.15 (5.62)
9.85 (5.76)
17.46
0.01
PSEQ
32.94 (14.06)
33.51 (14.46)
37.40 (13.53) 3.36
0.04
Depression Scale
15.80 (12.99)
13.80 (12.44)
12.72 (10.70) 1.83
0.16
2.37 (1.45)
2.50 (1.45)
CPAQ
62.17 (16.34)
AE Scale
PW Scale
Catastrophising
2.30 (1.34)
Test of
0.56
0.57
57.69 (18.90)
60.39 (18.83) 1.46
0.23
40.15 (12.78)
29.77 (14.95)
39.76 (14.52) 0.26
0.10
21.92 (10.96)
17.98 (10.69)
20.14 (11.28) 3.05
0.05
No significant differences were found between groups on the
Depression Scale (DASS), Activity Engagement Scale, Pain Willingness
scale, the CPAQ and on the catastrophising Scale. On the Roland Morris
Questionnaire the group with higher education had significant lower
means when compared with the 9 to 11 years of education group
(p=0.001) and with the 4 to 8 years of education (p=0.02). In the Pain
Self-Efficacy Questionnaire although some significant differences were
142
initially found, further analysis (Post Hoc analysis using Scheffe to
analyse significance) did not reveal any significant differences between
groups. Comparison between groups on the basis of work status for each
measure is presented below.
Tables 3.14 Comparison of mean scores on questionnaires by working
status
Questionnaires
Partially
Not working
Test of
Working
due to pain
significance
mean (SD)
Mean (SD)
mean (SD)
F
ρ
RMDQ
9.29 (5.78)
12.61 (6.53)
14.78 (5.21)
29.52
0.001
PSEQ
39.70 (13.22)
34.71 (13.70)
29.84 (13.01
17.17
0.001
Depression Scale 11.05 (10.81)
15.38 (13.58)
17.62 (12.09)
9.84
0.001
2.31 (1.32)
2.14 (1.63)
2.65 (1.36)
2.43
0.09
CPAQ
66.23 (15.03)
54.85 (16.85)
52.67(14.48) 21.98
0.001
AE Scale
43.91 (12.91)
35.80 (13.04)
35.73 (14.03) 12.23
0.001
PW Scale
22.29 (10.56)
18.97 (10.38)
16.67 (10.51)
0.001
Catastrophising
Working
8.59
N= 266 (only subjects with less than 65 years were selected for analysis)
There are significant differences on mean scores between all
groups on all the scales and questionnaires except for catastrophising.
However, further examination revealed that there are only significant
differences (p<0.001 Post Hoc analysis using Scheffe) on mean scores
only between two groups (people working and not working due pain).
143
That is, lower scores on self-efficacy, depression and acceptance, and
higher scores on disability were associated with unemployment.
The ability to detect some differences among groups suggests that
these measures have also concurrent validity and are capable of
identifying distinct outcomes or groups.
The next analysis examined the correlation of the different
measures; including the 5 factors found for the Chronic Pain Acceptance
Questionnaire.
Due to the large number of correlations (66), it was necessary to
adjust the Alpha level and to choose a parameter to avoid the increased
chances of a Type I error. To avoid Type I error, a Bonferroni adjustment
was applied to the level of significance (p=0.05/66). Therefore, only
correlations at a p=0.001 were considered significant.
Low to moderate correlations found among different measures
suggest that these measures have adequate discriminant validity and
measure different dimensions. Moderate correlations may indicate a
relationship between some of these variables (e.g. depression and
catastrophising). The higher correlations found between Chronic Pain
Acceptance Questionnaire and the Activity Engagement Scale suggests
the total score is more influenced by this sub-scale than the Pain
Willingness sub-scale.
144
Table 3.15 Correlations between questionnaires, scales and CPAQ factors
Questionnaires
RMDQ
RMDQ
PSEQ
DASS
CAT
Scale
Scale
CPAQ
AE
PW
Scale
Scale
F1
F2
F3
F4
F5
-
PSEQ
-0.58
-
Depression Scale
0.34
-0.38
-
Catastrophising Scale
0.34
-0.39
0.59
-
CPAQ
-0.39
0.64
-0.44
-0.47
-
Activity Engagement Scale
-0.33
0.67
-0.38
-0.38
0.79
-
Pain Willingness Scale
-0.23
0.22
-0.24
-0.29
0.64
0.05^
-
Factor 1
-0.37
0.69
-0.40
-0.39
0.78
0.95
0.08^
-
Factor 2
-0.25
0.22
-0.19
-0.25
0.61
0.65
0.91
0.09^
-
Factor 3
-0.08^ 0.10
-0.22
-0.24
0.43
-0.34
0.74
0.01^
0.44
Factor 4
-0.12
-0.18
-0.23
0.58
0.75
0.22^
0.54
0.06^
Factor 5
-0.10^ 0.17
0.35
-0.16
0.26
-0.18
0.40
-0.16
-0.09
0.17
-0.09^ -0.08^ -0.09^ -
All correlations were significant at the 0.001 level except for the ones marked with ^ which were above 0.05
145
There is a moderate correlation between factors 1 and 4, and
between factors 2 and 3. But also there is no correlation or a very low and
low correlation between factor 5 and all other factors (range from -0.09 to
0.26). In addition, there were high to very high correlations between
factors 1 and 4 and the acceptance scale (AE) and between factors 2 and
3 and the pain willingness scale (PW), which suggests that these four
factors form two distinct scales.
When examining the correlations between all the factors and the
CAPQ total score, only factor 1 (activity engagement) had a high
correlation with CAPQ, while factors 2, 3 and 4 have only a moderate
correlation, and factor 5 has a low correlation. These results suggest that
factor 1 is the most relevant factor of the CPAQ questionnaire and also
that correlation between factors and scales differ slightly from the results
reported by McCracken (1999, 2004), which will be considered further in
the discussion.
146
3.6 Discussion
This study examined the psychometric properties of a number of
translated measures widely used for assessing psychosocial factors
considered relevant for evaluating chronic pain patients. The summary of
the findings and the discussion are presented separately for each
questionnaire.
3.6.1 Psychometric properties of the RMDQ Brazilian version
The Roland and Morris Disability Questionnaire – Brazilian version
for general chronic pain (abbreviated as RMDQ - BrGCP) had a mean
score of 12.03 (SD=6.21), which does not seem too different from the
mean score reported by Roland and Morris’ original validation for LBP
( X =11.4 but SD was not reported in this study and therefore t test could
not be calculated) (Roland and Morris, 1983). The Brazilian sample’s
mean score was also below the cut-off point expected for high disability
in back pain patients reported by these authors in their original
validation.
When compared to a Brazilian validation for back pain patients
( X =14.30, SD=7.47) (Nusbaun et al, 2001) the mean score in the
present study ( X =12.03, SD=6.21) was lower than the one reported by
these authors, but not significantly different (t=1.62, p<0.05).
147
Reliability was tested using internal consistency coefficients and
correlation between forms (split-half). The RMDQ (BrGCP) had a
Cronbach’s α of 0.90 and a Pearson correlation coefficient between forms
of 0.82, which are similar to the internal consistency values reported by
the literature 0.92 (Asghari and Nicholas 2001; Jensen et al. 1992), 0.90
(Patrick et al. 1995), and 0.89 (Grotle et al. 2003). Furthermore,
according to Jensen (2003) correlation coefficients in this range can be
considered adequate for clinical and research purposes.
Criterion validity was examined through comparisons of means
between different groups regarding working status and level of education.
The mean score on the RMDQ (BrGCP) on the working group, partially
working and not working group was significantly different (p < 0.001).
This finding is similar to those reported in the literature, that support an
association between levels of disability on self-report and work status
(Robinson 2001; Turner et al. 2003).
There were also significant differences on means between the
group with high levels of education and the 4 to 8 years of education
group (means were 12.03 and 14.55 respectively, f=17.4 at a P=0.001).
The discrepancy on education may be reflected by the type of work
these two groups do, with the more educated generally doing less
physical work.
These differences on mean score between groups suggest that this
measure is sensitive to detect differences between distinct groups or
subjects under different conditions. These results support the RMDQ
Brazilian version criterion validity which indicates the efficacy of this
148
measure to predict behaviour (i.e. work status) (Anastasi and Urbina,
1997). These findings are also similar to several studies (Nusbaum et al.
2001; Patrick et al. 1995; Roland and Fairbank 2000), which provided
further support for the validity and sensitivity of the RMDQ.
Correlation coefficients with other tests that measure different
constructs were examined to test the discriminant properties of this
measure. It is expected that a test should not have a high correlation
with measures of different constructs (Anastasi and Urbina, 1997). The
RMDQ (BrGCP) correlation coefficient (Pearson) with PSEQ, DASSdepression scale, PRSS-catastrophising scale, CPAQ and its scale and
factors were in most cases significant (p<0.001), but this level of
significance is partially inflated by the large number of subjects (i.e. it is
easy to achieve a significant correlation when testing the relationships
among a high number of variables with a moderate to high number of
subkects n=311). However, the actual correlations varied from very low
to moderate. These statistics suggest that there is a relation between
some of these constructs, but at the same time there is not a complete
overlap between these measures.
The highest RMDQ (BrGCP) correlation was with the PSEQ (0.58),
which is supported by other findings (Nicholas and Asghari, 2006) that
reported an influence of self-efficacy on disability measure by the PSEQ
and the RMDQ. These findings are also similar to others found in the
literature (Asghari and Nicholas 2001; Kovacs et al. 2004; Stroud et al.
2004). The correlation between the RMDQ (BrGCP) and the average pain
intensity (reported in a VNS varying form 0 to 10) was significant but
149
also low (r=0.38), which suggests that there is a relation between pain
intensity and disability but that they are distinct constructs and also that
disability is not only a function of pain intensity. This finding is also
supported by several studies (Linton 2000; Pincus et al. 2002; SwinklesMeewisse et al. 2006; Williams 2001).
The findings related to the psychometric properties of the RMDQ
(BrGCP) supported by other studies, suggest that this measure is valid
and reliable in the Brazilian sample with chronic pain and may be used in
other Brazilian chronic pain populations.
3.6.2 Psychometric properties of the PRSS–Catastrophising Scale
Brazilian version
Regarding its descriptive statistics, the PRSS – Catastrophising
Scale Brazilian version (Cat-Br) had a mean score 2.38 (SD=1.38), which
differs significantly from the results (2.03 mean, SD= 1.22, t=3.18, p<
0.05) reported by Flor et al., (1993).
Reliability of the PRSS – Cat-Br was tested using internal
consistency coefficient and correlation between forms (split-half). The
Catastrophising scale had a Cronbach’s α of 0.89, which is very similar to
the results reported by Flor et al. (1993) of 0.92. These authors also
reported a test-re-test correlation of 0.87, while results from this study
found a Pearson correlation between split-half forms of 0.74. These
correlation
coefficients
can
be
considered
adequate
within
the
150
recommended range of 0.70 to 0.90 (Jensen 2003), and suggest that this
measure is consistent and reliable to be used in this population.
The construct validity of the Catastrophising scale was examined
using principal component analysis (PCA) and discriminant validity
analysis. PCA indicated the existence of two factors named rumination
and helplessness. These factors accounted for 54.5% and 12.9%
respectively, with factors loading varying from moderate to high (0.68 to
0.98), except for item 3 which loaded in the rumination factor, but with a
low communality and loading (0.25 and 0.38). These findings are similar
to the ones reported by Sullivan et al. (1995, 2006) who found three
factors on the PCS – Pain Catastrophising Scale, named rumination,
magnification and helplessness, accounting for a 41%, 10% and 8 %
variance respectively. D’Leon et al. (2004) also reported the existence of
three factors. Other studies have found a two-factor model of the PCS
(rumination and powerlessness, which is a combination of magnification
and helplessness) (Chibnall and Tait 2005).
Internal consistency (Cronbach alpha values) for two factors were
similar to the one found for the whole scale (0.86 and 0.85). Mean interitem correlations (0.55 and 0.58) also support the existence of two
factors, suggesting as previously described by Sullivan and D’eon (1990),
that these factors are different dimensions of this construct.
The Catastrophising scale correlation coefficient (Pearson) with
PSEQ, DASS - Depression scale, RMDQ, CPAQ and its scales were in most
cases significant (p<0.001) but varied from low to moderate (0.29 to
0.59), with the highest correlation occurring with the depression scale.
151
These results indicate that there is not a large overlap between these
measures
and
that
catastrophising
is
conceptually
distinct
from
depression. These findings are supported by several previous findings by
other researchers (Sullivan et al., 1995; D’Leon et al., 2004; Geisser et
al., 1994; Turner and Leslie, 2001; Jones et al., 2003).
Altogether, the 2 factors found in this study, the internal
consistency coefficient and the correlation coefficient between the two
factors, are in consonance with recent studies (D'eon et al. 2004;
Sullivan et al. 2005).
Criterion validity was examined through comparisons of means
between different groups. There were no significant differences on means
between groups regarding level of education and working status. This
seems to be appropriate, since catastrophic thoughts should not be
related with level of education and might not be associated with work
status as well.
Altogether these results support the validity and reliability of this
measure, which will be also, explored in Study 2 and 3.
3.6.3 Psychometric properties of the DASS – Depression Scale
Brazilian version
The DASS – Depression Scale Brazilian version (DASS-Dep-Br) had
a mean score of 14.03 (SD: 12.02), while the original version for general
population had a mean of 7.19 (SD=6.54) (Lovibond and Lovibond
1995), and the mean for chronic pain patients was 15.15 (SD=12.22)
152
(Taylor et al. 2005). As expected, there was a significant difference
between the mean score for the general sample and the Brazilian chronic
pain sample, but no significant difference between the Brazilian and the
Australian chronic pain samples (t=1.23, expected t is 1.96, p =0.05).
Reliability of the DASS-Depression Brazilian version was also
tested using internal consistency coefficients and correlation between
forms (split-half). The depression scale had a Cronbach coefficient of
0.96, which is very high, but very similar to the results reported by
Taylor et al. (2005) in other samples (Alpha coefficients for general
population was 0.95, for clinical 0.96 and on chronic pain subjects was
0.96). A recent study proposing a short-version for the DASS with half of
the original items reported an internal consistency coefficient of 0.88
(Henry and Crawford 2005). In this study using the same items to run a
split-half correlation between forms, a Pearson correlation coefficient of
0.93 was found. This is also a high correlation and similar to the above
finding and support the reliability of the DASS-Depression-Br. But,
unfortunately there are no normative data published for the DASS, which
would enable further comparisons.
The construct validity of the DASS-Depression-Br was examined
using principal component analysis, discriminant and criterion validity.
PCA indicated the existence of only one factor that assesses only
cognitive symptoms of depression. This one factor solution accounted for
64.4% of total variance. High loadings (range .73 to .87) for all items
except for one (.64) and high communality among items confirms the
existence of only one factor on the DASS – depression scale. This result
153
is similar to Taylor et al. (2005) and Lovibond and Lovibond (1995) which
confirms the unidimensionality of this scale.
As described earlier in the literature review, a number of studies
have reported the existence of some distinct dimensions while analyzing
self-reports of depression (i.e. BDI, Zung) (Novy et al. 1995; Pincus and
Williams 1999; Robinson and Riley III 1999). This aspect has been
considered important due to the presence of somatic symptoms of
depression and the overlap of symptoms between chronic pain and
depression. Thus, this would generate an inflated score when using
measures that have somatic symptoms of depression to evaluate patients
with chronic pain, causing a biased result or diagnosis (Lovibond and
Lovibond 1995; Pincus et al. 2004; Taylor et al. 2005).
Based on this assumption, again the results presented earlier
showing the existence of only one factor on the DASS-Depression-Br that
assess
solely
cognitive
symptoms
of
depression,
enhances
the
importance of using this measure to assess depression in chronic pain
patients and the goodness of fit of the DASS-Depression-Br for this
purpose.
Regarding the discriminant validity of the DASS-Depression-Br, its
Pearson correlation coefficient with PSEQ, PRSS-catastrophising scale,
RMDQ, CPAQ and its scales were in most cases significant (p<0.001) but
varied from low to moderate (0.29 to 0.59), with the highest correlation
occurring with the catastrophising scale. Again, this finding suggests that
these scales assess different constructs.
154
Criterion validity was examined through comparisons of means
between different groups. No significant differences were found between
groups with different levels of education on the Depression Scale, but
there are differences in means between different groups depending on
their work status. Subjects not working due to pain had higher scores
than the partially working and the working group (F=11.91, p=0.01).
These results support the concurrent properties of the DASS-DepressionBr, and are somehow similar to the findings reported by Taylor et al.
(2005) when they compared the scores of a sample composed by chronic
pain patients, patients attending a psychology clinic and general
population, who had significant differences.
The significant differences found between different working groups
and the lack of difference between groups with distinct levels of
education is appropriate, since depression should not be expected to
correlate with level of education, but might be expected to be associated
with work status. This finding have been reported in the literature, that
often report a correlation between depression and disability which
appears to be mediated by other factors (Banks and Kerns 1996; Keefe
et al. 2001; Pincus and Williams 1999). The relationship between
psychological factors and disability will be further explored in Study 2.
Altogether, these findings supported by other studies suggest that
the DASS-Dep-Br is a valid and reliable measure to be used in the
Brazilian sample with chronic pain and may be used for other Brazilian
chronic pain populations.
155
3.6.4
Psychometric
properties
of
the
Pain
Self-Efficacy
Questionnaire - PSEQ Brazilian version
The Pain Self-Efficacy Questionnaire - PSEQ Brazilian version
(PSEQ - Br) had a mean of 34.84 (SD=14.08), while in a recent study
with two different chronic pain samples the mean was 25.8 (SD=12.4)
and (23.5 SD=13.1) (Nicholas 2007) . Although the results from the two
samples presented in Nicholas’ study did not differ, the mean from the
PSEQ-Br differ significantly (p=0.01) from both Australian samples. As
noted before, differences between an Australian and a Brazilian sample
will be examined in Study 3.
Reliability of the PSEQ-Br was tested using internal consistency
coefficients and correlation between forms (split-half). The PSEQ-Br had
a Cronbach Alpha coefficient of 0.90, which is very similar to r=0.92
reported by Nicholas (1989). In the present study a split-half correlation
between forms were also run, with a Pearson correlation coefficient of
0.76. The PSEQ-Br’s Cronbach alpha for internal consistency and the
split-half correlation coefficient can be considered adequate and therefore
supports its reliability (Tabachnick and Fidell 2001).
The construct validity of the PSEQ-Br was examined using PCA and
discriminant validity analyses. A principal component analysis indicated
the existence of only one factor accounting for 55.29% of total variance
156
and an eigenvalue of 5.53. Median to high loadings (range .67 to .83)
was found for all items except for item seven (.44, “I can cope with my
pain without medication”). Item seven also shared a low communality
with the other items while the other items shared a median to moderate
communality. These results are similar to Nicholas (2007), who reported
a total variance of 58.6%, median to high item-total correlations and a
moderate factor loading, and the smallest coefficients’ on item seven.
However as reported by Nicholas (2007) and (Ralphs et al. 1994) item
seven has a high correlation with other measures.
On the other hand, this result is different to Anderson et al. (1995)
findings who reported a three factor solution for their Chronic Pain SelfEfficacy Scale (CPSS has 22 items) named: self-efficacy for pain
management, self-efficacy for physical functioning and self-efficacy for
coping with symptoms. However, there is some divergence related to the
domains and content of self-efficacy these two scales assess.
The main difference of the PSEQ and the CPSS is that the PSEQ
asks how confident the respondent is that he/she can do things despite
their pain. While in the CPSS all the questions ask how certain people are
in managing their pain, do physical activities or cope with symptoms
without emphasising that they must take into account how confident they
are of doing things when in pain, which seems to be a important
distinction.
As expected, these two scales might be assessing different
constructs or domains of self-efficacy beliefs. The PSEQ seems to be
more specific than the CPSS and focus more on the beliefs of having
157
abilities to function while in pain, and not to manage pain or cope with its
symptoms as the CPSS does. However, comparing these two scales was
not the focus of this study.
Regarding
its
discriminant
validity,
the
PSEQ-Br
correlation
coefficient (Pearson) with the Depression scale, the catastrophising scale,
the RMDQ, the CPAQ and its scale was in most cases significant
(p<0.001), but varied from low to moderate (0.29 to 0.59), with negative
correlations with measures of depression, disability and catastrophising.
The relationship between depression and self-efficacy has also
been reported by Anderson et al. (1995) who found a moderate
correlation between their self-efficacy scale and depression (-0.42 to 0.62), and Arnstein et al. (1999) who found that self-efficacy contributes
to depression. Furthermore, PSEQ-Br had its highest correlation (0.67
and 0.64 respectively) with CPAQ and its’ activity engagement scale,
which theoretically measure acceptance and with the RMDQ that
measures disability. These low to moderate correlations suggest that the
PSEQ-Br
measures
different
constructs
than
these
instruments,
supporting its construct validity (Campbell and Fiske 1959). This findings
also indicate that self-efficacy beliefs might contribute to disability, which
is supported by the literature (Arnstein et al. 1999; Asghari and Nicholas
2001; DeGood 2000; Nicholas 2007; Williams et al. 1994). The
relationship between self-efficacy and acceptance is discussed in the next
study.
Criterion
validity
of
the
PSEQ-Br
was
examined
through
comparisons of means between different groups. Significant differences
158
were found between distinct educational groups (p<0.05), as well as with
subjects under different work status (p<0.01). Participants with higher
level of education (i.e. Tertiary) had higher means on the PSEQ-BR than
subjects with four to eight years of education. Subjects in the working
group had higher means than those in the not working due to pain group.
These differences will be explored further in Study 2 and 3, but it could
be hypothesised that level of education is related to work status. Beside
this, level of education may contribute to self-efficacy. Low self-efficacy
may also contribute to unemployment of chronic pain patients. No matter
what the relationships are between these variables detecting differences
among groups supports PSEQ-Br’ criterion validity.
Altogether these findings indicate that the PSEQ-BR has sound
psychometric properties in this Brazilian sample with chronic pain and
may be used for other Brazilian chronic pain populations.
3.6.5 Psychometric properties of the Chronic Pain Acceptance
Questionnaire - CPAQ Brazilian version
The Chronic Pain Acceptance Questionnaire - CPAQ Brazilian
version (CPAQ-Br) had a mean score of 60.20 (SD=18.11), the activity
engagement scale mean was 39.89 (SD=14.07) and the pain willingness
scale mean score was 20.21 (SD=11.08). McCracken and colleagues’
version (1999) had a mean of 56.3 (SD=20.4), the activity engagement
scale mean was 33.3 (SD=13.2) and the pain willingness scale mean was
13.8 (SD=7.9). A study from Nicholas and Asghari (2006) reported a
159
mean of 53.8 (SD=18.0) for the CPAQ total score. The CPAQ Brazilian
version mean score was higher and differ significantly from both studies
(t=2.30 and t=2.75 at p<0.05 respectively) and may raise a number of
hypotheses discussed at the end of this chapter and examined in Studies
2 and 3.
Reliability of the CPAQ-Br including its scale was tested using
internal consistency coefficients and correlation between split-half forms.
The Cronbach α for the CPAQ-Br (total score), the activity engagement,
pain willingness, thought control and chronicity factors were respectively
0.78, 0.87, 0.75, 0.50 and 0.58 which are similar to the results reported
by McCracken (1999) 0.89, 0.90, 0.79, 0.74 and 0.58 with a 22 item
version and McCracken et al. (2004) 0.78, 0.82, 0.78, 0.64 and 0.62,
with a 28 item version. The results from this study added to McCracken’s
findings suggest an adequate degree of internal consistency (Cronbach
Alpha > 0.70) for the whole scale, factors 1 and 2, but not for factors 3
and 4. Indeed the results from this study are similar to McCracken
(2004), but differ from McCracken (1999) on relation to factor 3.
The correlation coefficient for the CPAQ and its two major scales,
was 0.68 (CPAQ), 0.73 (AE) and 0.57 (PW), which can be considered a
little below the adequate correlation coefficients recommended range of
0.70 to 0.90 (Jensen 2003), especially for the pain willingness scale.
Altogether these findings suggest that the reduction of items
proposed by McCracken (1999 and 2004) was reasonable, but that
further analyses regarding the reliability and validity of the CPAQ and its
scales should be conducted.
160
The construct validity of the CPAQ-Br was examined using principal
component analysis (PCA), item-scale correlations and discriminant
validity analysis. PCA using an eigenvalue criterion greater than 1 initially
indicated the presence of five factors named: activity engagement, pain
willingness, thought control, chronicity and accepting pain. This fivefactor solution accounted for 57.2% of the variance. But based on
previous results of a four factor solution (McCracken, 1999 and
McCracken et al, 2004), face validity and clinical experience (item 3 the
only item in factor five was the most missed item on data collection), a
final four-factor solution was thought to be more appropriated. This fourfactor solution accounted for 51% of variance, which is similar to the
52.7% of variance found by McCracken (1999) and 46.8% variance in
(2004) with two factors. Based on these further analyses were conducted
using a four-factor solution and also examining the psychometric
properties of the CPAQ as proposed by McCracken et al. (2004).
Low mean inter-item correlation also confirmed a poor correlation
among the items in all factors, except for factor 1, which has a moderate
correlation (0.48). Regarding item-scale correlations, most correlations
between items and the two relevant scales were moderate (Pearson
correlation range 0.44 to 0.78 at a p< 00.1), except for item 3 which had
a correlation of 0.35 with factor one and 0.14 with factor two (items were
not adjusted). This result supports the reliability of factor one but not for
the other factors.
Discriminant validity was examined through the CPAQ-Br and its
two scales, and the five factors solution presented earlier and the
161
correlation coefficient (Pearson) with PSEQ, DASS - Depression scale,
RMDQ and PRSS – Catastrophising scale.
In most of cases significant correlations were found between
several tests, scales and factors (p<0.01) in the expected directions, as
well as a very low correlation coefficient between some measures. The
correlations between the five factors for the CPAQ-Br, the activity
engagement scale and the pain willingness scale are presented below:
a. Factor five had a very low to low correlations with all other factors,
as well as with the CPAQ-Br and its’ two scales. This result
confirms the preliminary findings of this study (low inter-item
and item-scale correlations, and split-half coefficient and PCA)
that supported only a four factor solution;
b. Factor four had a moderate correlation with factor one (0.53), the
CPAQ-Br total score (0.58) and a high correlation with the
activity engagement scale (0.75).
c. Factor three had a moderate correlation with factor two (0.44) and
with the CPAQ-Br total score, and a high correlation (0.74) with
the pain willingness scale.
d. Factor two correlated moderately with factor 3 (0.44) and the CPAQBr total score (0.61), and very highly with the pain willingness
scale (0.91).
e. Factor one had a moderate correlation with factor four (0.53), a high
correlation with CPAQ-Br total score and a very high correlation
with the activity engagement scale (0.95).
162
These results occurred in the expected directions, since factor one
and two had the majority of items from the activity engagement scale
and the pain willingness scale (7 out of 11 and 6 out of 9 respectively).
The high correlation between factor one and four, factor two and three
and its respective scales supports McCracken and colleague’s (2004)
proposal for the existence of two scales in the CPAQ, composed by two
factors each, but as noted previously with a different number of items on
each factor in different studies.
High to moderate correlations (0.78 to 0.41) between factor one,
two, three and four with CPAQ-Br total score suggest that there is more
than two dimensions on the CPAQ-Br. But that the main dimension
probably is captured by factor 1, which has seven items from the original
activity engagement scale.
The high correlation between the CPAQ-Br and the activity
engagement scale (0.80) and moderate correlation between the CPAQ-Br
and the pain willingness scale (0.64) also enhance the importance of the
first scale when compared to the other scale.
These findings are similar to those reported by McCracken (1999),
who reported a correlation coefficient of (0.92) for factor 1 and (0.74) for
factor 4 with the CPAQ total score. McCracken et al. (2004) also reported
a correlation of 0.80 for the activity engagement scale and (0.76) for the
pain willingness scale with the CPAQ total score. Nicholas and Asghari
(2006) have also found similar correlations between the activity
engagement factor (0.85) and the pain willingness factor (0.76) with the
CPAQ total score. These high correlations between the two more relevant
163
factors and the total score partially support the construct validity of this
measure, the existence of distinct dimensions in the CPAQ-Br, and the
possibility of reducing the number of items for the CPAQ-Br version.
Correlations between the CPAQ-Br and its scales with other
measures
were
also
examined
to
evaluate
discriminant
validity.
Correlations between the CPAQ-Br, the activity engagement and pain
willingness
scale
and
the
RMDQ,
the
Depression
scale,
the
catastrophising scale and the PSEQ varied from low to moderate (at a
p<0.01 range from 0.23 to 0.67), suggesting that the CPAQ-Br and its
scales measure different construct.
The highest correlations were obtained between the self-efficacy
measure and the activity engagement scale (0.67). On the other hand, in
contrast with the activity engagement scale and the total CPAQ, the pain
willingness scale had a low correlation with self-efficacy (0.22), but the
same low correlations with depression, catastrophising and physical
disability. These results support McCracken (1999), Nicholas and Asghari
(2006) findings that reported a low correlation between physical
disability, depression and CPAQ and its scales. These last authors also
found a similar relationship between the CPAQ total score and its scales
and self-efficacy. Viane et al. (2003) also did not found a correlation
between acceptance and catastrophising.
These correlations suggest that that the activity engagement scale
seems to be the more psychometrically sound scale of the CPAQ and also
that there is a relevant relationship between some cognitions and
acceptance, which has not yet being fully understood.
164
Criterion validity was examined through comparisons of means
between different groups. No significant differences (p≤0.01) were found
between the CPAQ and its scales on relation to education level, but there
were significant differences between groups under different working
conditions (working and not working due to pain) on the two scales and
the CPAQ-Br total score. These findings suggest that the CPAQ-Br and its
scales are sensitive to detect differences among groups.
As noted before, a few differences on mean score between groups
were found on the tests. The relationships between these socio-economic
and psychosocial variables examined in this study are investigated in
Study 2 and 3.
165
3.6.6 Summary of discussion
The results of the reliability (internal consistency and split-half
correlations),
construct
validity,
convergent
validity,
criterion
and
discriminant validity analyses suggest that the Brazilian version of the
examined measures: the Roland and Morris Disability Questionnaire, the
Pain Self-Efficacy Questionnaire, the DASS – Depression Scale, the PRSS
– Catastrophising Scale, the Chronic Pain Acceptance Questionnaire and
the activity engagement and pain willingness scale have in general sound
psychometric properties in this sample, and may indeed be used in the
Brazilian chronic pain populations.
The results of the present study support previous findings (Flor et
al. 1993; Lovibond and Lovibond 1995; McCracken et al. 1999;
McCracken et al. 2004b; Nicholas 1989; Nicholas 2007; Roland and
Fairbank 2000; Roland and Morris 1983; Taylor et al. 2005) suggesting
that all the studied measures are valid, reliable and that psychometric
norms can be established to be used in the Brazilian chronic pain
population.
However in relation to the CPAQ Brazilian version, it may be
prudent to use only the activity engagement scale (which consist of
factors 1 and 4) with a total of 10 items and eliminating item 3. This
hypothesis will be tested on Study 2 and 3 when the predictive properties
of acceptance (measured by the CPAQ-Br) will be examined and further
conclusions would be drawn.
166
All the other measures seem to be used in a similar way proposed
initially by researchers. Furthermore, other studies conducted in Brazil
with these standardised measures will also elucidate their properties and
collaborate to test and enhance their validity and reliability.
The limitations of the present study should also be acknowledged.
These may include data collection procedures related to psychometric
aspects and sample characteristics. In relation to the first aspect, testing
the reliability of the questionnaires could not be done through test-re-test
due to the difficulties in contacting subjects for a second application of
the questionnaires; however other reliability analyses were conducted.
Another limitation of this research concerns the sample employed. First
the sample was mainly constituted of chronic pain patients attending pain
clinics. This may produce some biased information, since this sample may
consist of subjects that did not respond to pain as successfully as a nonclinical pain population. Second, our sample was not intended to be
representative of the Brazilian population with chronic pain. It is also
important to acknowledge that some of the differences found between
the present study and other studies mentioned may be due to differences
in samples, cultural differences and health system contingencies.
As noted before, a number of relationships between the studied
factors as well as cultural differences are explored in Study 2 and Study
3. Those results may also contribute to examine the psychometric
properties of the used measures.
167
CHAPTER FOUR
Study
Two:
The
relative
contributions
of
self-efficacy
beliefs,
catastrophising and acceptance to disability and depression in a Brazilian
population with chronic pain.
4.1 Introduction
Research suggests that cognitive, emotional and social factors may
shape the individual’s pain experience, influencing the degree to which
pain is experienced, responses to it, and the degree of interference
caused by it (Eccleston 2001; Skevington 1995; Turk 1996).
Disability in people with chronic pain appears to be related at least
or as much to psychological and social factors as to pathophysiology
(Pincus et al. 2002; Rudy et al. 2003; Turk 2002b). Some attitudes,
cognitive styles, fear-avoidance beliefs, passive coping approaches, pain
cognitions (i.e. catastrophising) may actually be considered risk factors to
future physical disability and emotional maladjustment (Linton, 2000).
Depression in people with chronic pain also appears to be strongly
influenced by cognitive variables, such as catastrophising (Nicholas and
Asghari 2006; Sullivan et al. 2001a), self-efficacy beliefs (Nicholas and
Asghari 2006; Turk and Okifuji 2002), acceptance (McCracken and
Eccleston 2003) and disability (Pincus and Williams 1999; Worz 2003).
There is also evidence that there is a bi-directional relationship between
these variables (Pincus and Williams 1999; Turk et al. 1995).
168
As noted previously, the vast majority of the research on the
relationship between chronic pain and adjustment and the role of
psychological variables has come from high income countries in Western
countries. However a few studies have been conducted in the Brazilian
chronic pain population (da Silva et al. 2004; Pimenta 2001).
One study conducted with a small sample (n=79) has done a
preliminary
cross-cultural
validation
of
the
Coping
Strategies
Questionnaire - CSQ (Keefe and Williams 1990), which includes the
catastrophising scale. The role of catastrophising on disability and
depression was not the scope of this study. The findings suggested that
this measure is valid and reliable for this population and that there were
no major cultural differences on interpreting the items and responses
occurred in a similar trend (Portnoi et al. 2005).
Another study (n=132) has been conducted on pain-related selfefficacy beliefs (Salvetti and Pimenta 2004) using the Chronic Pain selfefficacy Scale - CPSS (Anderson et al. 1995). The results yielded a 3
factor
solution
and
reported
adequate
psychometric
properties,
confirming the initial validation of this measure. The authors also found a
moderate and negative correlation with depression measured by the BDI.
Furthermore, the Brazilian sample also had a mean score significantly
higher than the sample used in the initial validation of the CPSS.
The concept of acceptance and its relationship with chronic pain has
not been investigated yet. On the other hand, the relationship between
depression and chronic pain has been the most common studied factor.
169
Although, there is a lack of epidemiological studies in this population
in Brazil, some studies have reported a prevalence of depression around
50% (Figueiró 1999; Lorencatto et al. 2002; Novello et al. 2005); which
does not differ from other chronic pain population.
To date no research in Brazil has reported investigating depression
in a chronic pain population using a depression scale without somatic
items.
Based on this evidence, it is clear that further research in this area
will be helpful to test the generalizability of the psychological research
findings from other countries and cultures and confirm if they can be
applied to a Brazilian chronic pain population.
Accordingly, the intention in conducting this study is to explore the
relationship among self-efficacy, catastrophising, acceptance, depression
and disability in a Brazilian population with chronic pain.
If the findings are consistent with those reported in the pain
literature generally, it would provide further support for a biopsychosocial
perspective on chronic pain. This, in turn, would suggest that clinical
treatment procedures developed in other countries might be used
effectively in the Brazilian population.
170
4.2 Method
4.2.1 Subjects
Data from 311 participants described in Study 1 were analysed to
test the relationship among the variables previously described.
4.2.2 Inclusion and exclusion criteria
Participants were included or excluded in this study based on the
criteria described in Study One.
4.2.3 Procedure
Data collected from all the subjects were entered into a database
for statistical analyses using SPSS 14 for Windows.
4.2.4 Measures
As described in Chapter Three, data were collected using the
following questionnaires: the Roland and Morris Disability Questionnaire
(Roland and Morris 1983), the Pain Self-Efficacy Questionnaire (Nicholas
1989), the PRSS - Catastrophising Scale (Flor et al. 1993), the Chronic
Pain Acceptance Questionnaire (McCracken et al. 2004b), the DASS Depression scale (Lovibond and Lovibond 1993), a socio demographic,
and a clinical inventory. All the psychometric properties of these
measures have already been described in Study One, and all have
adequate validity and reliability.
171
4.3 Hypothesis
This study is intended to test three hypotheses.
(1) Pain self-efficacy beliefs, acceptance, catastrophising and
depression
are
controlling
for
significant
predictors
socio-demographic
of
and
disability
clinical
after
variables,
including average pain intensity.
(2) Pain self-efficacy beliefs, acceptance, catastrophising and
disability
controlling
are
for
significant
predictors
socio-demographic
of
and
depression
clinical
after
variables,
including average pain intensity.
(3) Socio-demographic
and
psychological
variables
are
risk
factors for unemployment due to chronic pain.
4.4 Aims of study
1. To analyse the predictive properties of the psychological and
demographic variables on disability, depression, pain intensity and work
status in a Brazilian population with chronic pain;
2. To examine whether the relationships among pain related selfefficacy beliefs, acceptance, catastrophizing on depression and disability
in a Brazilian chronic pain population are similar to the findings reported
in the literature and consistent with current biopsychosocial models of
chronic pain.
172
4.5 Statistical analyses
A number of statistical analyses, mainly t-tests4, analyses of
variance (ANOVA), multiple correlation, multiple hierarchical regression
and logistic regression analyses will be used to test the relationship
between the variables described above and its predictive properties
(Tabachnick and Fidell, 2001). All the analyses were conducted using the
SPSS for Windows version 14.0.
4
Whenever a t-test was conducted the assumption of equal variance between
independent variables was examined by Levene’s test for equality of variance.
173
4.6 Results
Initially data distribution was tested for skewed distributions and
kusrtosis (with all variables not exciding the expected range –1 to 1),
multicollinearity and singularity using SPSS-14. All data were normally
distributed, variables were not highly correlated and not redundant, thus
statistical transformations were not necessary.
However, due to the coding system used on data entry some
variables were transformed to dummy variables. Work status initially was
categorised into not working due to pain, partially working and working,
but for correlation and regression analyses the first category was coded
as 1, while both groups that were working (i.e. partially working and
working) were coded as 2. Similarly the variable pain site was re-coded;
all pain single sites were coded as 1, while pain in two or more sites was
coded 2.
A preliminary analysis using t-tests was conducted to test for
differences between genders and number of pain sites on measures of
disability, self-efficacy, depression, catastrophising and acceptance.
There were no significant differences between genders on the
mean scores on disability, self-efficacy, depression, catastrophising and
both factors of acceptance (t≤1.96, p=0.05). However there was a
significant difference (t=2.7 p=0.007) between genders on pain intensity.
Males had a lower mean score ( X =5.5, SD=2.33), than females
( X =6.4, SD=2.37).
174
There were also no significant differences regarding number of
pain sites on most measures. However, patients with pain in two or more
sites had higher scores on disability and depression (p<0.001). Disability
mean score for patients with pain in two or more sites was 13.42
(SD=5.81), while for pain in any other site was 10.90 (SD=6.31) (t = 4.8 p=0.001). Depression mean score for patients with pain in two or
more sites was 17.16 (SD=12.65), and for other sites the mean was
11.47 (SD=10.87) (t = -2.8 p=0.005).
The contributions of other variables such as work status and level of
education on the psychological variables described above have been
reported in Study One. As noted there were significant mean differences
on the Roland and Morris Disability Questionnaire only; the group with
higher education had significant lower means when compared with the 9
to 11 years of education group (p=0.001) and with the 4 to 8 years of
education (p=0.001). Regarding work status, significant differences on
mean scores were found between groups on all the measures, except for
the Catastrophising scale. However, further analyses revealed that the
only significant differences (p<0.01 Post Hoc analysis using Scheffe) on
mean scores were between people working and not working due to pain.
There were no significant differences for age and gender on level of
education and work status.
Correlational analyses were also conducted to examine the
relationship among age, pain intensity, pain duration, disability, selfefficacy, depression, catastrophising and acceptance scales.
175
Due to the large number of correlations (45) it was necessary to
adjust the Alpha level to avoid the increased chances of a Type I and
Type II error5. To avoid Type I error, a Bonferroni adjustment was
applied to the level of significance. In other words, the Alpha level was
divided by the number of variables used in the analysis (i.e. 0.05/45
=0.001). Therefore, only correlations at this level were considered
significant.
5
That is including false positives (Type I error) and excluding false negatives
(Type II error) in the analysis. Therefore a balance between lowering the p level
(0.01) or increasing p levels (0.0001).
176
Table 4.1 Pearson correlations among socio-demographic, clinical and psychological measures
Age
Age
Pain
Pain
duration
intensity
Disability
Depression
Self-efficacy
Catastrophising
Activity
Pain
engagement willingness
-
Pain duration
- 0.01
-
Pain intensity
- 0.08
- 0.01
-
Disability
- 0.06
0.08
0.30*
-
Depression
- 0.13
0.18*
0.25*
0.34*
-
Self-efficacy
0.06
- 0.07
- 0.25*
- 0.58*
- 0.38*
-
- 0.16*
0.22*
0.28*
0.34*
0.59*
- 0.39*
-
0.16*
- 0.09
- 0.11
- 0.33*
- 0.38*
0.67*
- 0.38*
-
0.06
-0.10
- 0.07
- 0.23*
- 0.24*
0.22*
- 0.28*
0.05
-
0.17*
-0.13
-0.12
-0.40*
-0.44*
0.64*
-0.47*
0.79*
0.64*
Catastrophising
Activity engagement
Pain willingness
Acceptance
* Significant correlations at P ≤ 0.001
177
There were significant correlations among several variables.
However, most of the significant correlations were low in size (less than
0.40) (Rowntree 1981). Only the correlations between disability and selfefficacy (-0.58), depression and catastrophising (0.59), and self-efficacy
and activity engagement (0.67), and self-efficacy and the acceptance
questionnaire (0.64) were in the moderate range (higher than 0.40).
Correlations between the CPAQ and its scales were in the moderate to
high range, as expected, due to the total CPAQ score being the sum of
the two scales.
Other correlations were nearly in the moderate range, such as,
depression and self-efficacy (-0.38), depression and activity engagement
(-0.38), catastrophising and activity engagement (-0.38) and self-efficacy
and
catastrophising
(-0.39).
Low
correlations,
but
at
statistically
significant levels were found between age and catastrophising and
activity engagement, pain duration and catastrophising and depression,
pain
intensity
catastrophising,
engagement
and
disability,
disability
and
pain
and
depression
depression,
willingness,
and
self-efficacy
catastrophising,
between
depression
and
activity
and
pain
willingness, and between pain willingness and depression, catastrophising
and self-efficacy.
To examine the relationships among three chosen criterion
variables (physical disability, depression and pain intensity), sociodemographic and clinic variables, and the psychological variables, a
series
of
Hierarchical
Multiple
Regression
Analysis
(HMRA)
were
conducted.
178
Among the socio-demographic, clinic and psychological variables,
only those with significant levels of correlation with the outcomes as
established previously using a Bonferroni correction (P ≤ 0.001) were
entered in the regression analyses and those with significant differences
according to t-tests and analysis of variance. In each regression model, a
block of socio-demographic (e.g. gender and level of education) and clinic
variables (e.g. pain severity) were entered first in order to control for the
associations between these variables and the dependent variable,
followed by the cognitive and mood block of variables (enter method)
(see Tables 2, 3 and 4).
In the first regression analysis, although depression is one of the
studied outcomes, due to its importance in relation to disability,
depression was entered in step two as an independent variable with the
other cognitive variables. In the second regression analysis, due to the
important effect of disability on depression this variable was entered in
step two as an independent variable with the other cognitive variables.
To test the contribution of these variables to pain intensity, the sociodemographic variable (gender) was entered in the first step, depression
but not disability was entered in a second step with the other cognitive
variables (enter method).
In order to control for the risk of Type I errors, a Bonferroni
adjustment was applied for each group of analyses. Level of significance
was adjusted dividing p at 0.05 by the number of variables entered in the
regression analyses for each predictor. The adjusted p value for the each
179
group of variables was: disability (0.05/13 = 0.004), for depression
(0.05/13 = 0.004), and for pain intensity (0.05/7 = 0.007).
Table 4.2 Multiple hierarchical regression analysis predicting disability.
Step and predictors
Criterion
Total R²
F
df
R² Change F change Betaª
t
variable:
Disability
0.22
Step1:
21.40** 306
0.22
21.40**
Level of education
-.19
-4.2**
Gender
.01
0.2
Pain intensity
.11
2.4
Pain site
.19
4.3**
Depression
.04
0.77
Active engagement
.08
1.32
Pain willingness
-.07
-1.52
Catastrophising
.07
1.31
Self-Efficacy
-.51
-8.23**
Step 2:
0.47
29.47** 301
0.25
28.30**
ª Standardised regression coefficient * P ≤ 0.004 ** p ≤ 0.001
In the first analysis (Table 4.2), physical disability measured by the
RMDQ was significantly predicted by level of education, gender, pain
intensity and pain site (i.e. presence of more than one pain site). These
variables accounted for 22% of the variance in disability, but only
educational level and pain site obtained significant p levels. In the second
180
step of the analysis, measures of depression, activity engagement, pain
willingness, catastrophising and self-efficacy were entered into the
regression equation as a block. These variables accounted for an
additional 25% of variance in disability, however among these variables
only self-efficacy beliefs were a significant predictor of disability (beta = .51, p<0.001).
Table 4.3 Multiple hierarchical regression analysis predicting depression
Step and predictors
Criterion
Total R²
F
df
R² Change
0.11
9.86**
306
0.11
F change Betaª
t
variable:
Depression
Step1:
9.86**
Gender
-.10.
-0.21
Pain duration
.04
1.01
Pain intensity
.76
0.12
Pain site
.08
1.71
Disability
.07
1.08
Active engagement
-.15
-2.48
Pain willingness
-.06
-1.38
Catastrophising
.45
8.48**
Self-Efficacy
-.02
-0.24
Step 2:
0.41
23.40**
301
0.30
30.44**
ª Standardised regression coefficient * P ≤ 0.004 ** p ≤ 0.001
181
In the second analysis (Table 4.3), depression measured by the
DASS-Depression scale was predicted by the combination of gender, pain
duration, pain intensity and pain site (accounting for 11% of the variance
as a block). However, when disability and psychological variables were
entered in the equation none of these variables obtained significant p
levels. After controlling for these variables, disability and cognitive
variables were entered in step two as a group. Altogether this group of
variables explained an additional 30% of the variance. However, only
catastrophising (beta = .45, p < 0.001) made a significant contribution to
depression.
In
order
to
further
investigate
the
relationship
between
catastrophising and depression, another MHRA was conducted by using
the identified factors in Study One, helplessness and rumination as the
independent variables, after controlling for gender and pain variables.
The contribution of acceptance factors was not analysed due to its
non-contribution to predict any outcome, and also due to the high
correlations between the 4 factors, which would cause multicollinearity.
In regression analyses described in Table 4.3.a the relevant sociodemographic and clinical variables were entered in step one and
catastrophising factors were entered after in step two.
In order to control for Type I error, a Bonferroni adjustment was
also applied for this analysis. Level of significance was adjusted dividing p
at 0.05 by the number of variables entered in the regression analyses.
The adjusted p value for this analysis was (0.05/10 = 0.005).
182
Table 4.3.a MHRA predicting depression from catastrophising factors
Step and predictors
Betaª
t
Gender
-.35
-0.15
Pain duration
.02
0.49
Pain intensity
.11
2.42
Pain site
.10
2.32
.17
2.90*
.44
7.73**
Criterion
Total R²
F
df
0.11
9.65**
306
R² Change F change
variable:
Depression
Step1:
Step 2:
0.40
33.41**
304
Catastrophising
0.11
0.29
9.65**
71.78**
Factor 1
Catastrophising
Factor 2
ª Standardised coefficient for the catastrophising regression * P ≤ 0.005 ** p ≤ 0.001
This MHRA of predictors of depression that excluded other
cognitive variables and disability, revealed that catastrophising factors
(r= 0.59) accounted for an additional 29% of the variance, over and
above the contribution of gender and pain variables. Both catastrophising
factors were significant predictors at the adjusted p level value, which
confirms the results of the second set of analyses (Table 4.3). Factor 2,
which was named helplessness, seems to be a stronger predictor of
depression (beta = .44, p= 0.001) than factor 1, named rumination (beta
= .17, p = 0.004). This finding is in consonance with the literature and
will be discussed further in this section.
183
In the third main analysis (Table 4.4), socio-demographic and
psychological variables were examined as predictors for pain intensity. As
noted previously, although not a major outcome variable in this study, it
was an option to examine the contribution of the studied variables to pain
intensity.
Table 4.4 Multiple hierarchical regression analysis predicting pain intensity
Step and predictors
Criterion
Total R²
F
df
R² Change
0.02
7.42*
309
0.02
F change Betaª
t
variable:
Pain intensity
Step1:
7.42*
Gender
.16
2.91*
Active engagement
.17
2.24
Pain willingness
.05
0.87
Depression
.12
1.73
Catastrophising
.17
2.47
Self-Efficacy
-.28
-3.82**
Step 2:
0.15
9.04**
304
0.13
9.17**
ª Standardised regression coefficient * P ≤ 0.007 ** p ≤ 0.001
The results of the third regression analysis (Table 4.4) show that
gender explained only 2% of the variance in pain intensity (beta = .16, p
= 0.007). Cognitive and mood variables entered in step 2 explained an
additional 13% of the variance. However, only self-efficacy (beta = -.28,
p < 0.001) made a significant contribution to the variance in pain
184
intensity. Although catastrophising contributed significantly to pain
intensity at a p = 0.01 level, it was not significant when the Bonferroni
correction (p < 0.007) was applied.
To examine the contribution of socio-demographic, clinical and
psychological variables
to
work status,
a
logistic regression was
conducted.
Correlations between the variables entered in the regression were
examined. As reported in table 4.1, there were no correlations among
variables superior to 0.67 (except between sub-scales of the same
measure), which indicates that multicollinearity is not a problem here.
This means it is valid to conduct a regression analysis.
As most of the variables were re-coded into dummy variables
correlations were examined again. All Pearson correlations were below
0.30, which confirmed the lack of multicollinearity even when the
variables were re-coded.
For the best interpretation of the analysis of logistic regression (i.e.
the measures had different ranges) all the variables were re-coded as
dichotomous. The dependent variable (work status) was coded as follows.
Patients who were working or partially working were coded 0, and
patients who were not working were coded 1.
Since work status is likely to be affected by age, only participants
aged more than 18 years and less than 65 years were selected for the
analysis. Thus, the number of subjects was 222. Mean age of this group
was used as the cut off point (i.e. 45) for the re-coded age variable (age
less than 45 was coded 0 and ≥ 45 was coded 1).
185
Patients having pain in any site were given 0, while 1 was equal to
pain in two or more pain sites. Pain duration was coded 0 for patients
with pain for up to 5 years, and 1 for patients who were in pain for 6
years or more. Pain intensity cut off point was set at 5.
Education was also coded as a dummy variable. Patients with less
than 11 years of education or equivalent levels were coded as 1, while
subjects with technical education or tertiary were coded as 0.
All the disability and psychological measures were coded in the
same direction using upper quartile score as a cut off point (i.e. scores
lower than the third quartile was coded 0 and the upper quartile scores
were coded 1). However, when higher scores on the measure was a
positive outcome it was coded 0 and lower scores were coded 1 (i.e. selfefficacy and acceptance). Upper quartiles and lower quartiles in case
were low scores indicated worse scores were choose instead of mean as a
cut off point because they would indicated more severe dysfunction
levels, which would not appear if mean was the cut off point.
Reduced (i.e. parsimonious models) were produced by a process of
backwards elimination of the independent variables. At each stage, the
effect of dropping out an independent variable was assessed using the
likelihood ratio test (G statistic) at a significant level p=0.05. Odds ratios,
beta coefficients and confidence intervals were inspected at each stage to
check for possible confounding or effect modification and the goodness of
fit of the model (Hosmer and Lemeshow 1989).
Step 6 (of seven) was the best fit model, and although not
attaining significant p levels some variables were kept in to the
186
regression model due to their contribution to the best fit of the model. In
this case if an independent variable with a p-value exceeding 0.05
improved the model fit it was retained in the reduced model.
After observing these criteria and examining other possibilities for
coding the variables, the best model was chosen. However preliminary
analyses were run coding questionnaire scores on groups according
percentile, quartiles and mean cut off point. Age was also coded in a
number of different categories (i.e. 18 to 28, 29 to 39, 40 to 50 and 51
to 65 and as a continuous variable). The results found for the best-fit
model
did
not
differ
significantly
from
others
using
different
categorisations for age.
Table 4.5 Logistic regression analysis for work status with adjusted odds
ratio, p values and confidence intervals (Brazilian chronic pain sample)
Variable
Adjusted odds ratio* 95% C.I. P level
Age (≥ 45 years = 1)
0.39
0.20 – 0.74 0.004
Educational level (≤ 11 years = 1)
3.49
1.81 – 6.74 0.001
Physical disability – RMDQ (≥ 13 = 1)
2.75
1.27 – 5.97
0.01
Self-efficacy - PSEQ (≤ 35 = 1)
2.52
1.06 – 6.00
0.04
Acceptance - CPAQ ª (≤ 60 = 1)
1.92
0.86 – 4.30
0.11
* Pain intensity, pain site, pain duration, gender, depression and catastrophising
were also included in the regression.
ª Retained for improved model fit.
Among
all the
socio-demographic,
clinical and
psychological
variables, only educational level, age, physical disability and self-efficacy
187
attained
the
unemployment
significance
due
to
level
pain.
(p
The
≤
0.05)
most
as
potent
risk
risk
factors
for
factor
for
unemployment due to pain was educational level (odds ratio=3.49
p=0.001). This means that those subjects with less than 11 years of
education had nearly 3.5 times more chance of being unemployed than
those with higher education. Physical disability measured by the Roland
and Morris Disability Questionnaire (odds ratio=2.75 p=0.001) also had a
high contribution; which means that patients who were in the top quartile
score group had nearly three times more chance of being unemployed
than those with lower scores. The same trend occurred with self-efficacy
(odds ratio=2.5 p=0.04); patients with low self-efficacy scores for pain
were 2.5 times more likely to be unemployed than those with high or
median self-efficacy scores. People aged 45 or over were 61% less likely
to be unemployed than those in the younger group (less than 45).
Although, acceptance was kept in the model due to its contribution
to the goodness of fit of the model it did not attain a significant p level
(p=0.05). In this model, gender, pain intensity, pain duration, pain site,
depression and catastrophising also did not seem to be risk factor for
unemployment in patients with chronic pain.
188
4.6.1 Summary of findings
In this sample of Brazilian chronic pain patients, disability was
predicted by level of education, number of pain sites and self-efficacy.
Depression was predicted by catastrophising only. When the contribution
of Catastrophising factors were analysed separately, both factors were
found to be significant predictors of depression, with helplessness being a
stronger predictor of depression than rumination. Pain intensity was
predicted by gender and self-efficacy.
Among all socio-demographic, clinical and psychological variables
only educational level, age, physical disability and self-efficacy were
found to be significant risk factors for unemployment associated with
chronic pain.
189
4.7 Discussion
This section examines the findings of this study in the context of
the existing literature regarding the contribution of socio-demographic
variables, clinical variables and cognitive variables to physical disability,
depression, pain intensity and work status. The limitations and strengths
of this study and Study Three will be discussed in the final discussion.
4.7.1
Contribution
of
socio-demographic,
clinical
and
psychological variables to disability
The findings that a number of socio-demographic and psychological
variables were significantly correlated with disability and were predictors
of it is consistent with the published literature (Jensen et al. 2001b; Lame
et al. 2005; McCracken and Eccleston 2005; Nicholas 2007; Stroud et al.
2000; Turner et al. 2000).
These findings are given added significance when it is considered
that such findings have not been reported previously amongst Brazilian
chronic pain patients. The following section will examine the findings in
each area.
190
4.7.1.1 Contribution of socio-demographic and clinical variables
to disability
The finding that pain intensity did not contribute to disability in the
studied population when psychological variables are taken into account is
consistent with other results reported in the literature. While some
studies have reported that pain intensity is an important predictor of
disability (Arnstein et al. 1999; Viane et al. 2003), at least 30% of the
variance in disability is related to other factors (Jensen et al. 1994; Viane
et al. 2003).
The findings that numbers of pain site contributed to disability is
also in accordance with the literature, although with some variance (Von
Korff et al. 1992).
Level of education was also a significant predictor of disability. This
finding suggests that participants who have lower levels of education may
be employed in jobs involving more physical demands and thus may be
exposed to employment job factors involved on disability (i.e. lifting)
(e.g. Waddell, 2003).
It should be recognised that this series of studies was conducted in
a developing country, where level of education can severely compromise
work status. It could be hypothesised that level of education contributes
to work status in at least 3 ways. 1). Participants with lower level of
education are usually employed in jobs involving physical work, which in
turn could contribute to disability more than jobs involving mental
activity; 2). People with higher level of education could have more
191
economic resources to help then treating a chronic disease (i.e. use of
private health system); and 3). Level of education could moderate coping
skills. All these hypotheses have social and clinical implications and
deserve further research, but they are not the focus of this series of
studies.
Altogether these findings support the conclusion that in Brazilian
chronic pain patients, as in chronic pain patients in other countries,
although disability might be influenced by clinical factors (e.g. pain
intensity), there is a high correlation between disability and lower socioeconomic status (Aggarwal et al. 2003; Blyth et al. 2001; Gureje et al.
1998; Hagen et al. 2006; Pimenta 2001; Volinn 1997).
4.7.1.2 Contribution of psychological variables to disability
Among all the psychological variables studied (i.e. depression, selfefficacy, catastrophising and acceptance) only self-efficacy was a
significant predictor of disability (beta weight = -.51, t = -8.23, p <
0.001). This is particularly significant as this relationship held even when
the effects of education level and pain intensity were controlled for.
This finding has been reported elsewhere with some variations.
Some studies have reported that self-efficacy is a better predictor of
disability than pain intensity (i.e. Nicholas and Asghari, 2006; Jensen et
al, 1994), while others found that self-efficacy is a poorer predictor of
disability than pain intensity (Arnstein et al. 1999; Geisser et al. 2003),
or not even correlated with disability (Altmaier et al. 1993). These
192
differences on findings may be due to the use of different self-efficacy
measures, as well as sample differences. In relation to differences in
measures, the PSEQ developed by Nicholas (1989); ask respondents if
they can do things despite pain, while other self-efficacy measures do not
specify that people should consider their pain while evaluating their selfefficacy. This aspect could make a significant difference when evaluating
one’s efficacy to a specific situation (i.e. coping with chronic pain).
The finding that self-efficacy is a stronger predictor of disability
than other cognitive and mood factors has also been reported in the
literature (Arnstein 2000; Asghari and Nicholas 2001; Nicholas and
Asghari 2006; Turner et al. 2005). The finding of this study is in
accordance with Bandura’s theory (1977) that proposes self-efficacy
beliefs and appraisal are one of the best predictors of behaviour, and
may
also
influence
the
development
of
coping
strategies.
The
contribution of self-efficacy to disability is also in accordance with coping
strategies models (Lazarus and Folkman, 1984 and Lazarus, 1993) who
recognised that coping strategies are a function of several factors, such
as values, commitments, appraisals, beliefs, personality, and other
aspects. Therefore, patients with low self-efficacy may have ineffective
coping strategies that may contribute to disability.
Based on the social learning theory (Bandura, 1977) and on
models of coping strategies (Lazarus and Folkman, 1984) it can be
hypothesised that the amount of resources people believe they have is a
central influence on how people cope with chronic pain. Thus, the belief
that one can cope with chronic pain or engage in activities despite pain
193
would contribute to efforts to do so and thus to decrease disability. The
corollary is that those whose pain self-efficacy beliefs are weak are less
likely to try active coping strategies or to engage in functional activities.
In turn, it also means that interventions, like cognitive-behavioural
therapy (CBT) pain management programs, should explore ways of
enhancing self-efficacy beliefs in participating patients as a key element
in reducing disability levels.
There is strong evidence that disability due to chronic pain is a
composite of several factors, with catastrophising, depression and
acceptance playing important roles (e.g. Turner, 2000; Turk, 2000;
McCracken and Eccleston, 2003). However, in this study the contribution
of these other variables to disability, such as catastrophising (e.g.
Sullivan et al.), acceptance (McCracken et al.) and depression (e.g.
Pincus and Williams, 1999) were not confirmed.
The low contribution of catastrophising to disability (p = 0.19),
could be due to some shared variance with other variables (e.g.
depression), but multicollinearity did not seem to be a problem in the
data set.
To examine this aspect, a post hoc analysis was conducted
entering only variables that attained significant levels (i.e. education and
pain site), self-efficacy and catastrophising. Even without entering
depression, activity engagement and pain willingness in the regression
analysis, catastrophising did not contribute to disability (beta weight =
.11, t = 2.40, p = 0.02) at the adjusted p=0.001. This finding confirms
that this result was not obtained by chance; supporting the finding that
194
self-efficacy
is
a
better
predictor
of
physical
disability
than
catastrophising.
Nicholas and Asghari (2006) have reported a low contribution of
catastrophising to disability when compared to self-efficacy. Turner et al.
(2000) also found that catastrophising was a better predictor of
depression than of disability. They suggested that catastrophising may
have an indirect effect on disability via to effects on depression. But in
the present study neither depression nor catastrophising contributed to
on disability, especially relative to self-efficacy it is possible that
differences in the sample studied (e.g. education, employment and
depression) could explain the different findings.
In sum, although, some studies have found that catastrophising
predicts physical disability (e.g. Sullivan et al., 2005) others have not
(Nicholas and Asghari, 2006). The different findings suggest that it is not
catastrophising alone that determines this relationship. What is clear in
the present study is that catastrophising does not predict disability in this
sample of Brazilian chronic pain patients.
The failure of the pain acceptance scales (i.e. activity engagement
and pain willingness) to contribute to the prediction of disability when
self-efficacy, catastrophising and depression are taken into account
conflicts with McCracken et al’s. findings (1999 and 2004). Acceptance is
a novel concept in this field and although promising needs more
conclusive evidence. The variation in findings across studies suggests the
role of activity engagement and pain willingness is not robust. Perhaps
significantly, it is notable that few studies have investigated the role of
195
acceptance on disability after accounting for the effects of other variables
like self-efficacy, catastrophising and fear-avoidance beliefs.
Nicholas and Asghari (2006) found that when controlling for age,
pain intensity, fear of movement, catastrophising and depression, both
scales of the acceptance questionnaire did not predict disability, while
self-efficacy did predict disability. Viane et al. (2003) also found no
relationship between acceptance and physical disability. Results from the
present study are more in accordance with these last studies that suggest
acceptance does not appears to be a strong predictor of disability.
However, the non-contribution of acceptance to disability could also be
due to same shared variance among variables, especially self-efficacy.
From a theoretical perspective, as suggested by Nicholas and
Asghari (2006), at face value the concept of self-efficacy and acceptance
appear to be quite similar. This is partially confirmed by the moderate
correlation between the pain self-efficacy questionnaire and the activity
engagement scale of the acceptance questionnaire (0.67) reported in the
first study. Even so, this relationship is not so high to make either
redundant.
Activity engagement is described by McCracken et al. as “the
pursuit of life activities in a normal manner even while pain is being
experienced” (2004, p.164), while, self-efficacy has been described by
Nicholas (2007) as “a belief in one’s ability to engage in normal activities
despite pain” (p. 160). However, McCracken et al. (2004) proposed that a
key difference between these two concepts lie in the fact that acceptance
does not include judging the value of being in pain or the ability to
196
manage it. Nicholas and Asghari (2006) also point out that the PSEQ
focuses more on functioning independently of pain, while the acceptance
questionnaire appears to focus on willingness to live with pain without the
need to control it. Based on these definitions, arguments and evidence
presented by the authors of the scales, it appears that the most
important difference between these measures is that acceptance focuses
more on an attitude towards living with pain, while self-efficacy intends
to examine beliefs about functioning while in pain. Acceptance seems to
be an attitude with emotional bases, while self-efficacy seems to be a
belief related more to behaviours than emotions.
Thus, it seems that from a conceptual perspective these constructs
could be defined differently and maybe the problem of their overlap is
related to their definition or to the lack of psychometric properties of the
acceptance measure (e.g. findings of study one).
4.7.2
Contribution
of
socio-demographic,
clinical
and
psychological variables to depression
The finding that work status, pain duration, pain intensity,
disability,
self-efficacy,
activity
engagement,
pain
willingness
and
catastrophising were significantly correlated with depression is in general
in conformity with the literature (Campbell et al. 2003; McCracken and
Eccleston 2006; Nicholas 2007; Sullivan et al. 2001b). Again, the
significance of these results is that for the first time, similar relationships
197
between these variables to those found in high income western countries,
have been found in a Brazilian chronic pain patient sample.
4.7.2.1 Contribution of socio-demographic and clinical variables
to depression
Socio-demographic and clinical variables were not found to be
significant predictors of depression (at p=0.001) in a multiple regression
analysis.
Pain intensity has been frequently reported as a predictor and/or
mediator of depression (Jensen et al., 1994; Pincus and Williams, 1999;
Arnstein et al., 1999). However, as suggested by Turk et al. (1995) and
Arnstein et al. (1999), it seems that pain intensity is not directly related
to depression, but is indirectly related to depressive symptomatology
through other mediating factors (i.e. catastrophising). The lack of
contribution by pain intensity to depression found in this study is in
accordance with the findings of Turk et al. (1995) and other researchers
(e.g. Pincus et al., 2004).
Results of the first study found a significant difference between the
working and the not working group on depression.
It is likely that work status and depression would have a bidirectional relationship. It has been known that unemployment is a risk
factor for depression and equally, that depression is a risk factor for poor
outcomes in rehabilitation (Haythornthwaite et al. 1991).
198
The finding that disability was not a significant predictor of
depression is interesting given the relationship of work status and
depression. This finding has been reported by other studies (Arnstein et
al., 1999; McCracken and Eccleston, 2005), and it suggests that work
status has more impact on a person’s psychological state than activity
limitations by themselves. It points to the view that work represents
more than a functional activity and implies that it provides important
value to a person’s life (e.g. Morley et al., 2005).
Having chronic pain in addition to being unemployed, may
represent an additional risk for psychological problems. The findings of
Study One have shown that on nearly all the psychometric measures
there were significant differences between the working and not working
group. However, further exploration of this issue is beyond the scope of
this study.
The
finding
that
age
was
not
correlated
significantly
with
depression in this chronic pain sample is consistent with previous findings
reported by a number of researchers (Nicholas and Asghari, 2006;
McCracken and Eccleston; 2005; Viane et al; 2003). Interestingly, there
is a higher prevalence of depression in elderly people (Campbell et al.
2003), but in older people with chronic pain it seems that relatively to
younger people with chronic pain, those over 60 years of age seem
slightly less depressed. It is not clear why this is the case, but it may be
that older people might accept pain more than younger people, and thus
become less depressed.
199
The finding that that number of pain sites was not predictive of
depression but was of disability is puzzling, especially given the
significant differences in depression between those with one main pain
site and those with two or more (p=0.001). What the MHRA finding
suggests is that it is not number of site, per se, that is the determining
factor of the difference in depression, but some other factor(s) that are
related to number of pain sites. This issue is considered further in the
discussion.
The finding that pain duration is not a significant predictor of
depression has also been reported in the literature (Von Korff et al.
1992).
In sum, the findings of this study in relation to the contribution of
socio-demographic and clinical variables to depression in this sample
appear generally consistent with the published international literature.
4.7.2.2 Contribution of psychological variables to depression
In the second step of the regression analysis to examine predictors
of depression, after controlling for gender, pain duration, pain intensity
and number of pain sites, measures of disability, activity engagement,
pain willingness, catastrophising and self-efficacy were entered in the
equation. These psychological variables were found to account for an
additional 30% of the variance in depression. However, of these variables
only catastrophising made a significant contribution to the prediction of
depression (beta weight = .45, p < 0.001).
200
The finding that disability, pain self-efficacy, activity engagement,
pain willingness, and catastrophising were significantly correlated with
depression is consistent with the published literature (e.g. Nicholas and
Asghari 2006, Arnstein et al., 1999, McCracken and Eccleston, 2003).
Among these variables, catastrophising had the highest correlation with
depression, which has also been frequently reported in the literature (e.g.
Sullivan et al., 1990, 2005; Nicholas and Asghari, 2006).
The contribution of all these variables to depression when analysed
together has received little attention in the literature, but the finding that
of these variables, catastrophising is the only significant predictor is
consistent with previous findings and explains its importance in the
assessment of adjustment to chronic pain (e.g. Sullivan et al., 2005;
Turner et al., 2000).
The finding that disability did not predict depression when selfefficacy beliefs are taken into account has also been reported by Nicholas
and Asghari (2006) and Arnstein et al. (1999). When these findings are
considered alongside those from the present study, they suggest that
cognitive variables are more predictive of depression in chronic pain
patients than disability (activity limitation). This conclusion is also
consistent with Turk’s diathesis-stress model of chronic pain (2002).
The finding that acceptance (activity engagement and pain
willingness scales) did not predict depression even at less stringent
higher p levels (e.g. p ≤ 0.01) diverges from other findings reported in
the literature (McCracken and Eccleston 2003; McCracken and Eccleston
2005; McCracken and Eccleston 2006; McCracken et al. 2004b; Nicholas
201
and Asghari 2006). However, except for the Nicholas and Asghari study
the other studies did not include catastrophising in their analyses. These
findings indicate that catastrophising makes a greater contribution to
depression than acceptance.
Nicholas and Asghari (2006) found that only activity engagement
was predictive of depression. In contrast, McCracken et al. (2004) found
that both CPAQ scales predicted depression. Subsequent studies by
McCracken’s group have found that sometimes one and sometimes the
other subscale is a better predictor of depression (McCracken and
Eccleston, 2005, 2006).
The reasons for these differing findings are unclear, but may be
related to different samples and different cultures. McCracken’s studies
were conducted with Americans and British patients, while Nicholas and
Asghari used an Australian sample, and the present study a Brazilian
sample.
Another issue that may need to be considered in relation to
acceptance is the capacity of the CPAQ to adequately capture it. As noted
in Study One, only the activity engagement scale was found to have
adequate psychometric properties. This is consistent with concerns raised
about the CPAQ (e.g. Nicholas and Asghari, 2006).
Regarding the contribution of self-efficacy to depression, in the
present study pain self-efficacy beliefs did not predict depression even at
less stringent p levels (i.e. p ≤ 0.01). This finding diverges from those of
Arnstein et al. (1999) and Nicholas and Asghari (2006). However, these
studies reported only a small contribution by self-efficacy to depression
202
(6% of variance in the first study, and a beta weight of -.16 at p=0.01 in
the second study).
On the other hand, the finding that self-efficacy is an important
predictor of disability may indicate that this variable could contribute to
depression indirectly, but this is only speculation and would have to be
tested. However, this hypothesis is in accordance with the nature of the
self-efficacy concept proposed by Bandura (1987) and supported by
Nicholas (2007). According to this concept it could be expected that pain
related self-efficacy beliefs would largely influence the efforts people in
pain would put into doing tasks or carrying on their normal life, which
might affect indirectly their mood. However, as discussed earlier it seems
that cognitions such as those covered by catastrophising are stronger
predictor of mood disturbance in chronic pain patients. In that respect,
the findings with self-efficacy are consistent with the disability and
catastrophising findings.
When examining the contribution of catastrophising to depression,
the findings of this study suggests that among all psychological variables
studied, catastrophising is the most important predictor of depression,
and even when accounting for physical disability measured by the RMDQ.
In the literature, catastrophising has been frequently reported as a
superior predictor of depression than other beliefs and coping responses
(Sullivan and D'Eon 1990; Turner et al. 2000), than acceptance (Nicholas
and Asghari 2006; Viane et al. 2003), and than self-efficacy and fearavoidance (Nicholas and Asghari 2006).
203
The
finding
of
this
study
regarding
the
contribution
of
catastrophising to depression supported by the literature could indicate
that the degree to which a patient experience depression is largely
influenced by other factors than pain intensity, physical disability, coping
and self-efficacy. As suggested by the cognitive and behavioural model
(Beck
1976;
Sullivan
and
D'Eon
1990),
cognitions
(specifically
catastrophising) strongly mediate how people interpret the nature of their
reality. Thus, being depressed in the context of having chronic pain has
not only to do with being in pain or disabled, but more to do with
cognitive-evaluative processes.
At times the large contribution of catastrophising to depression has
been thought to be due to some shared variance with depression (Sulliva
and D’Eon, 1990). However, several studies have shown that this
constructs are distinct although with some similar elements (Beck 1976;
Jones et al. 2003; Sullivan et al. 2005). According to cognitive models,
both constructs have a helplessness component, but catastrophising is
marked more by rumination and magnification components.
Sullivan et al. (2001)
suggested that catastrophising could
contribute to depression through biasing the information process,
heightening
the
pain
experience
and
thus
influencing
emotional
functioning and the development of depression. Jones et al. (2003)
suggested that catastrophising should not be conceptualised merely as a
cognitive coping construct, but as a construct with both cognitive and
affective components. Severeijnes et al. (2005) found that the role of
catastrophising
in
different
populations
(general
population
and
204
inpatients) seemed to vary in nature. Overall, while research into the
ways in which catastrophising might operate with people in chronic pain,
the results of the present study in relation to catastrophising are clearly
consistent with those found in a range of countries and cultures.
This suggests that interventions for chronic pain that are directed
at these different psychological factors would warrant a trial in Brazilian
chronic pain patients.
4.7.3
Contribution
of
socio-demographic,
clinical
and
psychological variables to pain intensity
As noted before, only gender and pain self-efficacy had a
significant contribution to pain intensity at the adjusted p level (p ≤
0.007), however catastrophising would be considered a significant
contributor of pain intensity at a less stringent p level (p = 0.01).
However, the impact of these variables is still quite small. The first set of
predictors (gender) explained only 2% of the variance in pain intensity.
The second group of cognitive and mood variables explained an
additional 13% of the variance, with only self-efficacy (beta weight= .28, p= -3.82, p<0.001) making a significant contribution to predict pain
intensity.
205
4.7.3.1 Contribution of socio-demographic and clinical variables
to pain intensity
The finding that there was a gender difference in pain intensity
scores and that gender is correlated and contributes to pain intensity
(beta weight = .16, t= 2.91, p=0.004) is in accordance with other
published studies in both experimental pain studies (Sheffield et al.
2000) and clinical results (Turp et al. 1997), Although, there is no
consensus
on
what
the
possible
mechanisms
involved
in
these
differences, some have suggested possible physiological and cultural
differences may be involved (Edwards et al. 2001a).
From a cultural perspective, there is evidence that in some cultures
it is more acceptable for women to express pain behaviour than men and
thus this could affect pain report (Hobara 2005). Furthermore, gender
differences have been reported on measures of catastrophising and
depression (Keefe et al., 2001), which could effect indirectly the
relationship between gender and pain intensity. However, in this series
of studies there were no differences on mean scores between males and
females on depression and catastrophising. Thus, the small contribution
of gender to pain intensity in the studied population may be explained by
cultural factors, but this is only a speculation.
206
4.7.3.2 Contribution of psychological variables to pain intensity
The
finding
that
pain
willingness,
activity
engagement
and
depression did not contribute significantly to pain intensity has been
reported in the literature, but not consistently (Nicholas and Asghari
2006; Viane et al. 2003).
Based on the concept of acceptance described by Hayes et al.
(1999) and McCracken et al. (2004), it could be hypothesised that
accepting any given situation would lessen the distress or unpleasantness
of it. Thus, it could be expected that an accepting attitude would
contribute to less unpleasantness, reflected in the affective component of
pain (e.g. the affective dimension of pain captured by the McGill Pain
Questionnaire). However, the influence of acceptance on pain intensity
varies considerably in the literature. Acceptance has been reported to
predict pain (p=0.05) by McCracken and Eccleston (2003), however that
was without controlling for demographic, clinic and other psychological
variables except for coping strategies. McCracken et al. (2004) and
McCracken and Eccleston (2006) found that only the pain willingness
scale is a significant predictor of pain intensity (p=0.001). On the other
hand,
Nicholas
and
Asghari
(2006)
reported
no
contribution
of
acceptance to pain intensity (at a p > 0.01).
The finding that depression did not contribute to pain intensity is
also in accordance with some studies. A review by Dickens et al. (2003)
found that depressed patients are less likely to perceive a noxious
stimulus as being painful than non-depressed patients. Sullivan et al.
207
(2001) reported that depression does not predict pain intensity when
catastrophising is taken into account, but could be associated with the
experience of heightened pain and emotional distress in response to pain.
Taken together, these findings may suggest that depression does not
play an important role on pain intensity.
Among the psychological variables self-efficacy had the strongest
contribution to pain intensity (beta weight= -.28, t = -3.82, p<0.001).
Nicholas and Asghari (2006) and Altmaier et al. (1993) also have found
that self-efficacy predicts pain intensity and plays an important role as a
mediator between pain intensity and disability, as described previously.
The results of this study support this evidence in this specific population.
It could be hypothesised that patients with lower self-efficacy could
feel more vulnerable to their pain, due to the lack of perceived resources
to cope with it. On the other hand, higher levels of pain would demand
more self-resources, which could be perceived by the patient as beyond
their capacity. The measure of self-efficacy used here does ask
respondents to take pain into account and accordingly the findings might
be interpreted in that light. However, as Nicholas (2007) reported, PSEQ
scores appear to be not only influenced by pain severity and other factors
such as the belief in one’s ability to perform a task, would also be
expected to play a role.
Catastrophising did not predict pain intensity in the present study
at the adjusted p level, but it was significant at the less stringent p level
of 0.01 (beta weight= .17, t= 2.47). Furthermore, a post hoc analysis
found that (after controlling for gender) the unique contribution of the
208
two catastrophising factors explained 9% of the variance for pain
intensity, but only factor 1, named rumination was significant (beta
weight =.29, t=4.25, p < 0.001).
The findings in relation to catastrophising and the rumination
factor are in accordance with the findings from experimental studies (e.g.
Sullivan et al., 1995) and clinical studies (e.g. Michael and Burns, 2004;
Nicholas and Asghari, 2006). Sullivan et al. (2005) in a study with
neuropathic patients found that the rumination scale of the PCS (which
has similar item contents to factor one of the PRSS catastrophising scale)
accounted for a significant proportion of the variance in affective pain.
However, in other studies with subjects with longer pain duration and
neuropathic pain the helplessness factor made a greater contribution to
pain intensity than the other factors. Sullivan et al. (2005) suggested
that the nature and duration of pain seemed to evoke different
catastrophic dimensions.
In the present study, the contribution of both factors (rumination
and helplessness) to depression, and the contribution of catastrophising
and the rumination factor to the prediction of pain intensity suggest that
different aspects of catastrophising differently affect depression and pain
intensity. In this case, helplessness seemed to play a more dominant role
in depression and rumination seems to contribute more to pain intensity.
This is in accordance with evidence gathered by Sullivan et al. (2001,
2005), who suggested that a helpless orientation might compromise
efforts to cope with pain and mood, while rumination would account for
an excessive focus on the noxious stimulus.
209
4.7.4 Examining risk factors for work status
In this sample of Brazilian chronic pain patients, of whom 41%
were unemployed due to pain, educational level, age, physical disability
and
self-efficacy
were
found
to
be
significant
predictors
of
unemployment. In contrast, of the variables measured, pain intensity,
pain
site,
pain
duration,
gender,
depression,
acceptance
and
catastrophising were not found to be risk factors for unemployment in
this sample.
Educational level had the strongest effect on unemployment due to
pain (odds ratio=3.49 p=0.001), followed by physical disability (odds
ratio=2.75 p=0.001), age (odds ratio=0.39 p=0.004)and self-efficacy
(odds ratio=2.52 p=0.04).
There is good evidence from elsewhere that individual and
workplace or system related factors play an important role in disability
and return to work (Marhold et al. 2002; Sullivan et al. 2005; Teasell and
Bombardier 2001). A number of studies have also suggested that
perceptions and beliefs about work and returning to work may play an
important role on recovery and disability (Marhold et al. 2002; Schultz et
al. 2004; Sullivan et al. 2005). Marhold er al. (2002) found that perceived
prognosis of return to work, social support at work, physical workload
and harmfulness, pain intensity and depression (measured by the
obstacles to return to work questionnaire) were significant predictors of
sick leave after 9 months. Blyth et al. (2005),
in a population based
study, found that people not working due to pain reported more use of
210
passive coping strategies. Other cross-sectional studies have also found
that catastrophising is a significant predictor of more prolonged work
absence in injured workers (Sullivan et al. 1998; Sullivan and Stanish
2003). Ghelfold et al. (2005) found that pain-related fears were
significant determinants of the inability to work in people with back pain.
Depression has also been associated with greater occupational disability
and is involved in transition from acute to chronic pain (Sullivan et al.
1992; Sullivan et al. 1998). Schultz et al.’s (2004) findings suggest that
perception of health change and expectations of recovery were significant
predictors of return to work.
Other studies of predictors for return to work after treatment, have
found that age, marital status, education and decreased length of
unemployment were important predictors of return to work (Tan et al.
1997). More recently, Vowles et al. (2004) found that age, pain duration
and levels of reported disability were predictive of work status.
The finding that age, educational level and disability were risk
factors for unemployment in this Brazilian sample with chronic pain is in
accordance with findings from other countries (e.g. Vowles et al., 2004;
Tan et al., 1997;).
However, it is important to recognise that work status was not one
of the main outcome variables investigated in this study. Thus this study
did not explore a range of other dimensions that have also been related
to return to work for injured workers. This applies specifically to work
related factors, such as suitable work availability, employer-related factor
and compensation (e.g. Teasell and Bombardier, 2001; Sullivan et al.,
211
2005). The present study focused only on individual factors, and intended
to interpret unemployment due to pain as an indicator of disability.
In considering why educational level was the most important risk
factor for this sample, it may be relevant to note that in a developing
country like Brazil, employment is likely to be influenced by level of
education. In this country interventions aiming to help chronic pain
patients to return to work would have to address this aspect as well (e.g.
training needs). This is not peculiar to Brazil, however, as studies in high
income countries have reported similar findings (Schultz et al. 2004).
The findings of this study that educational level was a predictor of
disability and the highest risk factor to unemployment in patients with
chronic pain are also often reported in the international literature (e.g.
Hagen et al., 2006; Tan et al., 1997). There are also a few Brazilian
studies reporting an association between low back pain and socioeconomic level (da Silva et al. 2004; Pimenta 2001). However, even in the
international literature these relationships are poorly understood.
There
are
diverging
models
and
evidence
regarding
the
relationship between educational level and work status in the general
population and in chronic pain patients.
The human capital theory outlines that educational level mediates
social mobility and work conditions (Henriques 2000). However, recent
studies (Pochmann 2004) conducted in Brazil with the general population
have found that in developing countries characterised by low economic
growth, lower investment in technology and worsening work environment
conditions (i.e. Brazil), increasing level of education has not contributed
212
to unemployment. On the other hand, it appears that people with higher
levels of education that are employed do earn higher salaries than those
with lower levels of education.
In the chronic pain field there is some evidence of the relationship
between
educational
level
and
work
status
but
the
underlying
mechanisms are not clear. Dionne et al. (2001) and Hagen et al. (2006)
suggest that this relationship could be related to the fact that people with
lower levels of education are more likely to work in physical and
psychological demanding jobs.
Therefore, having lower levels of education would increase the
likelihood of having a job that is physically demanding, thus not being
physically fit would increase the likelihood of not being able to work in
this population.
Furthermore, well-educated people are more likely to have
healthier life styles than those with lower education (e.g. obesity,
sedentary) (Leboeuf-Yde 2000). This could also explain the contribution
of educational level on disability, which could indirectly contribute to
unemployment.
Evidence of the relationship between educational level, disability
and work status in chronic pain patients is scarce in the Brazilian
literature. But it might be expected that this relationship would occur in
developing countries to a higher degree than in developed countries due
to more severe socio-economic conditions that may affect chronic pain
patients
even
more.
Therefore,
it
could
be
hypothesised
that
a
combination of factors (i.e. having low education and chronic pain) would
213
increase the likelihood of being unemployed in a developing country more
than in a developed country. However this is only speculation, suggesting
further research.
Other studies with working populations have found that gender
(female) and lower socio-economic level were predictors of disability due
to chronic pain (Enthoven et al. 2006; Jablonska et al. 2006). Findings
from this study could not examine the contribution of socio-economic level
to unemployment. However, in the studied sample, gender was not
associated with unemployment. It is possible that this might reflect
employment opportunities in Brazil being different for men and women.
Results from this sample also suggest that pain intensity did not
contribute to unemployment. Regarding this issue there is mixed
evidence in the literature. Shaw et al. (2005) investigated a group of
patients attending occupational health clinics and found that pain level
and mood were stronger predictors of return to work than health history
or physical findings. On the other hand, there is evidence that pain
intensity was an important predictor of disability and unemployment due
to pain (Enthoven et al. 2006; Jablonska et al. 2006).
As noted before, the biopsychosocial model of pain holds that pain
is a multidimensional phenomenon and that several factors interact in
shaping pain experiences. Therefore in different samples and different
cultures it is expected that the relationship between chronic pain and
disability will be slightly different but will be broadly similar.
Physical disability (measured by the RMDQ) was a significant risk
factor for unemployment (odds ratio=2.75). It could be expected that
214
patients with high levels of disability (scores higher than the third
quartile) would be on sick leave, retired or unemployed. Although, there
are a number of reasons for not returning to work, the contribution of
disability to not returning to work is frequently reported in the literature
(Enthoven et al. 2006; Vowles et al. 2004). Thus the findings of the
present study would seem broadly consistent with those from other
studies.
While previous studies have found that depression (Cohen et al.
2000; Robbins et al. 1996; Vowles et al. 2004), anxiety and lower levels
of self-efficacy have been associated with unemployment due to pain
(Robbins et al. 1996), this study found that self-efficacy was more
important than these other psychological variables. This finding is
interesting and may indicate differences in work environment and social
security
contingencies
between
Brazil
and
other
more
developed
countries.
As described in the results, although self-efficacy was a risk factor
for unemployment in this Brazilian sample with chronic pain, its
contribution
was
smaller
than
the
contribution
of
disability
and
educational level.
Based on this, it could be hypothesised that socio-economic and
clinical factors play an important role in work status, which could be also
influenced by the person’s belief in their ability to function despite pain.
It seems that self-efficacy might partially explain how some people
in pain can carry on with their working activities; especially in a
developing country were socio-economic factors can be more severe than
215
in a developed country, and that there is usually less government or
insurance support for the unemployment in the developing countries.
216
4.7.5 Summary of discussion and implications
As predicted, this study found that a number of psychosocial
factors might contribute to disability, work status, emotional adjustment
and pain intensity in patients with chronic pain.
These
findings
are
clearly
supportive
of
a
biopsychosocial
perspective of chronic pain and indicate that the model applies to
Brazilian chronic pain patients as well as to those from other countries
with more developed economies and different cultures.
The results show that in this population, socio-demographic factors
(i.e. educational level and gender) can interact with clinical variables (i.e.
pain site) and contribute to disability (i.e. reported physical disability and
work status). Furthermore, cognitions (i.e. catastrophising and selfefficacy) also seem to have an important contribution to pain intensity,
disability, work status and emotional adjustment. Biological factors (e.g.
pathophysiology) were not assessed in this study, but the strength of the
relationships found that psychological and demographic factors indicate
that regardless of pathophysiology, they make an important contribution
to the impact of chronic pain as outlined by the biopsychosocial model.
These findings also partially confirmed the hypotheses of this study
that some cognitions and mood would contribute to disability, that some
cognitions and disability would contribute to depression and that some
socio-demographic and psychological factors would contribute to work
status.
217
From a clinical perspective the findings of this study suggest that
interventions based in these concepts can be expected to be relevant to
the Brazilian chronic pain population.
The next study will examine more closely the relationships
reported in this study in a matched Australian sample with chronic pain,
which will be compared to the findings reported above.
218
CHAPTER FIVE
Study Three: A cross-cultural comparison of the contribution of
cognitions to disability and depression: A comparison between an
Australian and a Brazilian sample with chronic pain.
5.1 Introduction
In this series of studies the results of Study Two have supported
some of the basic tenets of the biopsychosocial model of pain; namely
that cognitive factors influence adjustment to chronic pain.
Among several psychosocial factors, it is also expected that
cultural factors may influence pain perception and responses to it, but
this feature has not been yet considered in this series of studies.
Cultural factors are thought to influence how a person perceives,
experiences and responds to pain. Cultural factors may include: values,
beliefs, norms and social practices (Magnusson and Fennell 2005).
Although there are mixed findings and a lack of conclusive
evidence regarding the influence of cultural factors on the impact of
chronic pain on individuals, most findings support the existence of
differences among ethnic groups on pain perception (Bates et al. 1993;
Moore and Brodsgaard 1999). Mechanisms involved in the relationship
between culture and pain are not clear and are likely to be complex with
a lot of variation even within a culture (Skevington, 1995; Dimsdale,
2000). Recent findings also suggest that ethnic groups differ regarding
emotional responses to chronic pain and present different coping
219
strategies (Edwards et al. 2005; Hastie et al. 2004; Riley et al. 2002).
However, a number of studies have shown that when ethnic groups are
matched on confounding variables (i.e. income or social classes) these
differences are relatively small (Edwards et al. 2005; Portenoy et al.
2004).
From a clinical perspective, responses to chronic pain seem to be
more important than variance in noxious stimulus perception (Tait and
Chibnall 2005). It has been argued that ethnicity influences the course of
chronic pain and its treatment (Dimsdale 2000; Tait and Chibnall 2005).
Recently, studies have focused on clinical implications regarding ethnic
differences on pain responses (i.e. treatment disparities, treatment
engagement, tailoring treatments according to individual or group
differences) (Edwards et al. 2005).
Examining ethnic differences may also be important from a
theoretical perspective. Since current pain models and much of the
evidence have largely been produced in economically advanced western
cultures (mainly European and North American). It is important to
understand to what extent these findings can be generalised to other
cultures. In this
study we
are
interested in determining
if the
psychosocial factors described in the international pain literature have a
similar role in a Brazilian chronic pain population.
While a number of studies have confirmed similar pain prevalence
rates (Macfarlane 2005), the role of psychosocial factors on pain and
disability (Gureje et al. 1998), as well the efficacy of multidisciplinary
CBT pain management interventions in different countries (Blyth et al.
220
2005), there is relatively little cross-cultural research in this field. In
particular few studies have compared very distinct populations in
different cultures regarding the contribution of psychosocial factors to
disability.
The results presented in Study Two indicated broad similarities in
relationship between psychosocial variables and pain dimensions between
Brazilian chronic pain patients and findings published in the pain
literature. However, that study did not compare the Brazilian sample with
a matched sample of chronic pain patients from a more developed and
English speaking country. So, the present study was intended to test the
generalizability of the previous findings with a matched comparison
sample of chronic pain patients in Australia.
If the previous findings are confirmed it would further strength the
generalizability of those findings.
5.2 Socio-demographic characteristics of Brazil and Australia
5.2.1 Brazil
According to the Brazilian Bureau of Statistics (Instituto Brasileiro
de Geografia e Estatística - IBGE 2000), the Brazilian population is
186.808.564, distributed in an area of 8.514.876 km2. Men account for
49.22% of the population while women are 50.78%. Age distribution is 014 years (29.60%), 15-64 years (64.55%) and over 65 years (5.85%).
Around 81% of the Brazilian population live in urban areas, while 18%
live in rural areas. Expectancy of life is 71.59 years. Portuguese is the
221
national language. The illiteracy rate is 11.6%, however most of the
population has 4 to 7 years of education.
The Brazilian Gross Domestic Product (GDP) is US$ 602 billion, with
a per capita income of capita US$ 8.017. However, Brazil has the second
worst income distribution in the world and unemployment rate is 9.1%
(Instituto Brasileiro de Geografia e Estatística - IBGE 2000). Nearly 56%
of the working force earn up to US$ 350.00 a month, 21% earn between
US$ 350.00 and US$ 800.00, around 17% earn between US$ 800.00 and
1700.00 a month, and only less than 5% of the working force earn more
than US$ 1700.00 a month.
The Portuguese started the colonisation of Brazil in 1500 and
although the Brazilian population is a blend of Portuguese, Indians
(aborigines) and Africans, there is a large contribution of several
ethnicities through immigration cycles. Most of immigrants came to Brazil
between 1884 and 1959 (approximately 4 million), and originally were
from Portugal, Italy, German, Spain, Lebanon and Japan (in order of
magnitude). According to the last census, 53.7% of the population is
White, 39.5% are Brown, 6.2% are Black, 0.4% are Asians and 0.4% are
Indians. Most of the Brazilian population is Christian and only 7% report to
have no religion (Instituto Brasileiro de Geografia e Estatistica - IBGE
2000). In general Brazilians have strong religious beliefs and religion plays
a big role in the Brazilian culture. Brazil is a very diverse culture and, in
general, well integrated.
The Health system in Brazil is publicly-funded and according to the
constitution every Brazilian should have free access to health service and
222
medication. The quality of the services varies from one region to another,
but long waiting periods can occur for some specialities (e.g. 6 months or
more). There are discrepancies on access to the health system related to
socio-economic levels. In the last decade, there has been an increase in
the private sector investment in this area. Therefore, it is increasingly
common for middle class people to have a private health plan and access
to better health services.
As in most health systems, treatment is a major priority, while
educative interventions and preventive approaches are not as well
supported. There is a small number of pain clinics in the public sector and
less
than
a
dozen
in
the
private
sector.
Furthermore,
general
epidemiological data for chronic pain is scarce in Brazil, but it could be
assumed to be similar to that obtained in other countries (Gureje et al.
1998).
5.5.2 Australia
The European colonisation of Australia followed the English
discovery of the continent in 1778. There have been several immigration
waves, firstly lead by the British and Irish settlers (often convicts being
sent for the rest of their lives), followed by other European countries
especially after World War II (i.e. eastern and southern European
countries), Asian, Middle Eastern countries and lately African countries.
Around 2.5 million immigrants arrived in Australia from 1985 to 2000,
making it a very multicultural society (Australian Bureau of Statistics.
223
2004). Due to its new immigration waves, a number of immigrants are
still in an acculturation process.
Most of the Australians report to have a religion (i.e. Anglican,
catholic or other), but 15% have no religion and nearly 12% have not
reported having a religion or responded wrongly in the Census (Australian
Bureau of Statistics 2006). In general, religion does not have a very
obvious role in the Australian culture as compared to Brazil.
Australia has a population of 20.592.324 people distributed in
7617930 kmh. Men account for 49.8% of the population. Age distribution
is 0-14 years (20.70%), 15-64 years (67%) and over 65 years (12.3).
Nearly 86% of the Australian population live in urban areas, while 14%
live in rural areas. Expectancy of life is 77 years for males and 82 years
for females, respectively. Regarding the educational level, 41% are below
upper secondary level (leave school at age 15), 30% are above upper
secondary,
10%
have
post-secondary
education
and
19%
reach
university. Literacy rate is thought to be nearly 100% (Australian Bureau
of Statistics. 2004).
The Australian’s GDP is US$ 637 billion, with a per capita income
of capita US$ 27.070. Wealth in Australia is more evenly distributed than
in most countries and the unemployment rate in 2004 was around 4.9%
(Parliamentary Library. 2002).
The Health system in Australia is publicly funded, but there is a
strong health private sector as well. The government subsidises the
private health fees and a number of medications. The quality of the
services tend to be better in the cities, but long waiting periods can occur
224
for some specialities
(e.g. 6 months or more
for some
elective
procedures). Therefore, it is common to have a health plan to try for
faster access to health services. As in most health systems, and similarly
to Brazil, treatment is the major priority, while educative interventions and
preventive approaches are less emphasised. There are discrepancies in
access to the health system related to socio-economic levels.
There are a number of pain clinics in public hospitals and some in
the
private
sector
as
well.
Contrary
to
Brazil,
there
are
some
epidemiological data confirming a similar prevalence of chronic pain to
that reported by the international literature (e.g. Blyth et al., 2001).
To summarise, there are many socio-economic and demographic
differences
between Australia and Brazil. Although in process of
development, Brazil is more characterised by social and economic
disparities (moderate level of unemployment, lack of housing, high levels
of criminality, but also extremely wealthy families). Due to their
colonisation processes and immigration waves, both countries are also
culturally diverse.
Despite the differences between these two countries, in many
areas the health systems of both countries face similar problems.
Although less problematic in Australia, in both countries the public health
system is struggling, there are difficulties in transcending the curative
model, to increase early interventions and to implement more holistic
approaches for managing chronic diseases. Beside these, working injury
legislation and work place issues can interfere with returning to work in
both countries.
225
Despite their differences, people living with chronic pain in these
two countries face a number of similar problems which may increase their
suffering and create difficulties in their ability to return to normal, daily
activities. These include the dominance of the bio-medical model in the
health system, delayed interventions for pain, multiple barriers for return
to work after being in pain for a number of years, and lack of training for
health professionals in the management of chronic pain.
Therefore, despite the differences in culture and language, living
with a chronic disease (i.e. chronic pain) in a western society even in
different countries may be an important homogenising factor.
As pain is a universal phenomenon, this feature may in turn make
this group of people much more similar than different. But this needs to
be tested.
226
5.3 Method
5.3.1 Subjects
Data collected from 311 subjects with chronic pain attending pain
clinics or similar facilities in public and private services in Brazil were
matched with data from a paired population that attended the Pain
Management and Research Centre - Royal North Shore Hospital located in
Sydney, Australia6. Data from the Pain Management Research Centre
(PMRC) was also derived from 311 patients.
5.3.2 Inclusion and exclusion criteria
Participants were included or excluded in this study based on
criteria described in Study One. In both groups, questionnaires with more
than 10% of missing items were not used in the statistical analysis.
5.3.3 Procedure
The Brazilian sample was recruited first, as described in Study
One. The Australian sample was selected from patients being seen at the
PMRC during 2005-2006. The Australian sample was identified by file
search, which aimed to match the Brazilian sample according to age and
gender.
The inclusion criteria for the Australian sample were similar to
those of the Brazilian sample, in that informed consent to use their
6
This series of studies had the approval of the Royal North Shore Hospital ethics
committee attached on appendix 2.
227
(anonymous) data for the research was required, they had to be able to
read English enough to complete the questionnaires, and they had to be
presented to the clinic with chronic (more than 3 months) non-cancer
pain.
Data
collected
from
questionnaires
previously
completed
by
patients attending the PMRC were entered in a database for statistical
analyses using SPSS 14 for Windows.
5.3.4 Measures
As described in Chapter Three data were collected using the
following questionnaires: the Roland and Morris Disability Questionnaire
(Roland and Morris 1983), the Pain Self-Efficacy Questionnaire - PSEQ
(Nicholas, 1989), the PRSS Catastrophising scale (Flor et al., 1993), the
Chronic Pain Acceptance Questionnaire - CPAQ (McCracken et al. 2004b),
the DASS Depression scale (Lovibond and Lovibond 1993), a socio
demographic, and a clinical inventory. All the psychometric properties of
these measures have been described in Study One and in the literature,
and all have adequate validity and reliability.
5.4 Hypothesis
This study is based on the hypothesis that the relationships
between
pain,
self-efficacy
beliefs,
acceptance,
catastrophising,
depression and disability should occur in a similar pattern in these two
samples.
228
5.5 Aims of study
The major aim of this study is to compare the relationships among
socio-demographic and clinical variables, self-efficacy beliefs, acceptance,
catastrophising, depression, and disability in a Brazilian and an Australian
chronic pain population and to examine if these findings are consistent
with those reported in the literature.
5.6 Statistical analyses
A number of statistical analyses were conducted to examine the
data,
mainly
independent
sample
t-tests,
ANOVA,
correlations,
hierarchical and logistic regressions (Tabachnick and Fidell, 2001). All the
analyses were conducted using the SPSS for Windows version 14.0.
Firstly,
descriptive
statistics
from
the
Australian
sample
is
presented. Second, similarly to Study Two the relationships between
socio-demographic, clinical and psychological variables were examined in
the
Australian
sample
using
correlation
coefficients,
hierarchical
regression and logistic regression analyses. After that the Australian and
Brazilian samples were compared.
The samples were compared using independent sample t-tests and
analyses of variance (ANOVA). Whenever, a t-test was run, Levene’s test
was performed to examine equal variances difference between groups,
when ANOVA was conducted a Scheffe post hoc tests was run. Findings of
the regression and logistic analyses are compared between samples.
229
5.7 Results
This section will present the findings regarding the contribution of
socio-demographic, clinical and psychological factors to disability and
depression within the Australian chronic pain sample. In the discussion
these findings will be compared with those from the Brazilian sample
(already presented in Study Two) and with the current literature.
The distribution of the data collected at the Pain Management and
Research Centre were inspected to check for skewed distributions,
multicollinearity and singularity. Data were confirmed as normally
distributed, correlations between variables were inferior to .90 and there
were no redundant variables, therefore no statistical transformations
were necessary.
Due to the coding system used on data entry some variables were
transformed to dummy variables. Work status initially categorised into
working, partially working and not working due to pain was coded as 0
(for working and partially working) and 1 (for not working due to pain).
Similarly the variable pain site was re-coded; all single pain sites were
coded as 0, while pain in two or more sites was coded as 1.
Descriptive
statistics
are
presented
in
Table
1
for
socio-
demographic and clinical characteristics of the PMRC sample. In table 2
mean scores on the psychological measures are described. In Tables 3
and 4 differences in mean scores associated with work status and
educational level were examined using t-tests and analyses of variance
(ANOVA) respectively, followed by comments of other differences
associated with gender and pain site on a number of measures.
230
Table 5.1 Socio-demographic and clinical characteristics of the Australian sample
Socio- demographic and clinical characteristics Australian sample No (%)
Age (mean)
49.2 (SD=14.8)
Gender
Male
83 (26.7)
Female
228 (73.3)
Marital status
Single
74 (23.7)
Married
188 (60.5)
Separated, divorced or widowed
49 (15.8)
Educational Level
Less than year 10
77 (25.7)
Up to year 12 or technical
146 (45.0)
Higher level of education (i.e. university)
88 (29.3)
Employment status
Working
183 (58.8)
Unemployed due to pain
128 (41.2)
Pain duration
From 3 months up to 1 year
55 (17.8)
1 to 3 years
72 (24.2)
3 to 5 years
72 (24.2)
6 to 9 years
27 (9.1)
Up to 10 years
74 (24.7)
Pain intensity (mean)
5.8 (SD=2.0)
Major pain sites
Head, face, neck
27 (8.7)
Cervical, shoulders and upper limbs
44 (14.1)
Back or spine
31 (10.0)
Lower back and lower limbs
46 (14.8)
Two or more major sites
107 (34.4)
Other
56 (18.0)
Most of the participants (60.5%) were married, 45% had up to 12
years of formal education, and nearly 41% of the participants were not
working due to pain. Mean pain duration was defined as an ordinal
231
variable, and the majority of participants (58%) had experienced pain for
more than 3 years. Mean average pain intensity was rated 5.8 out of 10.
Most of the participants had pain in two or more sites (34.4%), followed
by pain in lower back and lower limbs (14.8%), cervical, shoulder and
upper limbs (14.1%), and back or spine pain (10%). Other pain sites
with a smaller prevalence were grouped together (i.e. pelvic, anal,
genital, thoracic and abdominal).
In the next table, scores on the psychological measures are
described. Statistical analyses were run to analyse the distribution and
mean on a number of measures (disability, self-efficacy, depression,
catastrophising and acceptance) and a number of other variables (e.g.
age, pain intensity) in the Australian sample in a similar fashion to that
used in Study One.
The normal distribution of patients by gender at the PMRC was
57.4% of women, but in order to match the Brazilian sample the ration
had to be altered to select proportionally more women, until the PMRC
study sample was 73% women.
232
Table 5.2 Descriptive statistics for the Australian sample in all the measures
Questionnaires
Means (SD)
Skewness Kurtosis Score range
Roland and Morris Disability Quest. 11.66 (6.62)
0.42
-0.90
0-24
Pain Self-Efficacy Questionnaire
27.57 (13.65)
0.27
-0.63
0-60
DASS - Depression Scale
11.73 (10.44)
1.00
0.40
0-42
2.73 (1.50)
-0.06
-0.56
0-5
Chronic Pain Acceptance Quest.
59.65 (17.56)
-0.57
0.26
0-120
Activity Engagement Scale
32.67 (12.47)
0.07
-0.21
0-66
Pain Willingness Scale
28.08 (10.80)
-0.28
-0.53
0-54
PRSS - Catastrophising Scale
The results indicate that the data are normally distributed, with
skewness and kurtosis values inferior or nearly 1.0 (Tabachnick and Fidell
2001). Furthermore no clear outliers were identified. Thus, statistical
transformation to normalise the data was not necessary.
Differences regarding socio-demographic characteristics on mean
score are presented on the next tables.
233
Table 5.3 Comparison of scores on questionnaires by educational level
up to year 12
Higher level
Test of
years of
or technical
of education
significance
education
of education
Questionnaires Less than 10
ρ
F
mean (SD)
mean (SD)
mean (SD)
RMDQ
12.82 (6.09)
11.61 (6.18)
9.71 (5.86)
PSEQ
25.29 (14.07)
27.64 (13.37)
28.90 (14.29)
1.46
0.23
Depression Scale
11.72 (10.40)
10.86 (10.16)
10.94 (10.15)
0.19
0.82
2.72 (0.98)
2.69 (1.05)
2.50 (1.02)
1.28
0.27
CPAQ
57.10 (18.17)
60.73 (17.48)
59.46 (16.20)
1.03
0.35
AE Scale
33.07 (12.67)
33.03 (12.08)
32.25 (12.05)
0.13
0.87
PW Scale
24.12 (11.69)
27.71 (11.71)
27.12 (9.63)
2.71
0.07
Catastrophising
5.79
0.003
No significant differences were found between education levels on
measures
of
self-efficacy,
depression,
catastrophising,
activity
engagement, pain willingness, and total acceptance. However there was
a significant difference on the Roland and Morris Disability Questionnaire.
When further analysis (Post Hoc analysis using Scheffe to analyse
significance differences with in groups) were conducted, there was only
significant differences on the RMDQ mean score between the group with
less than 10 years of education and the group with tertiary education (p
= 0.004). Participants with lower educational level (up to 10 years) were
more disabled than those with tertiary education.
Comparison between groups on the basis of work status for each
measure is presented below.
234
Table 5.4 Comparison of scores on questionnaires by work status
Questionnaires
Not working
Working
due to pain
mean (SD)
mean (SD)
Australian
t-test of
total sample
significance
ρ
mean (SD)
t
11.37 (6.16)
3.81
0.001
RMDQ
12.67 (6.08)
9.81 (5.87)
PSEQ
24.00 (13.43)
29.13 (13.15)
27.39 (13.84)
-3.06
0.002
Depression Scale 13.64 (10.44)
9.29 (9.51)
11.11 (10.19)
3.45
0.001
Catastrophising
2.87 (0.89)
2.53 (1.07)
2.64 (1.01)
2.76
0.006
CPAQ
58.10 (16.96)
60.86 (16.85)
59.46 (17.10)
-1.21
0.19
AE Scale
31.52 (12.02)
33.12 (11.72)
32.81 (12.19)
-1.19
0.28
PW Scale
26.52 (11.65)
27.75 (10.54)
26.61 (11.20)
-0.62
0.38
N= 257 (only subjects with less than 65 years were selected for analysis)
Although, there was no difference between the two groups on pain
intensity (t=0.12, p=0.90), the not working due to pain group differ
significantly from those working on mean scores on disability, selfefficacy, depression and catastrophising, but not on acceptance and its
factors.
Scores of the not working group due to pain are lower on selfefficacy, and higher on disability, depression and catastrophising than the
participants that have pain but were still working.
Other possible differences on score associated with gender and
pain site were examined. There were no significant differences on mean
scores associated with gender and pain site on all the measures
(p≤0.001).
In the next table correlations between a number of variables are
described followed by regression analyses.
235
Table 5.5 Pearson correlations among socio-demographic, clinical and psychological measures
Age
Age
Pain
Pain
Disability
duration
intensity
Depression
Self-efficacy
Catastrophising
Activity
Pain
engagement willingness
-
Pain duration
0.14
-
Pain intensity
0.04
-0.02
-
Disability
0.03
-0.06
0.40*
-
Depression
-0.12
-0.02
0.14
0.38*
-
Self-efficacy
0.20*
0.09
-0.26*
-0.53*
-0.52*
-
Catastrophising
-0.20*
0.03
0.19*
0.31*
0.45*
-0.43*
-
Activity engagement
0.19*
0.09
-0.13
-0.22*
-0.45*
0.67*
-0.38*
-
Pain willingness
-0.14
-0.2
-0.19*
-0.12*
-0.27*
0.11
-0.19*
0.09
Total Acceptance
0.04
0.06
-0.21*
-0.23*
-0.49*
0.54*
-0.39*
0.76*
0.71*
* Significant correlations at P = 0.001
236
As expected there were significant correlations among several
variables. Most of the significant correlations were generally low in size
(less than 0.40) (Rowntree 1981). The correlations between pain
intensity and disability (0.40), disability and self-efficacy (-0.58),
depression and self-efficacy (-0.52), depression and catastrophising
(0.45), depression and activity engagement (-0.45), self-efficacy and
activity engagement (0.67), self-efficacy and catastrophising (-0.43),
acceptance and depression (-0.49), and acceptance and self-efficacy
(0.54) were in the moderate range (higher than 0.40). Some other
correlations
were
close
to
the
moderate
range.
These
included,
depression and self-efficacy (-0.38), depression and activity engagement
(-0.38) and acceptance and catastrophising (-0.39). As expected there
were high correlations between acceptance and its scales.
To examine the relationships among three chosen criterion
variables (physical disability, depression and pain intensity), sociodemographic and clinic variables and self-efficacy, acceptance of pain
(activity engagement and pain willingness scales) and catastrophising, a
series
of
hierarchical
multiple
regression
analyses
(MHRA)
were
conducted.
The rationale for the selection of independent variables to be
entered in the analyses was significant levels of correlation with the
outcomes as established previously using a Bonferroni correction (P=
0.001), significant differences according to t-tests and ANOVAs and
clinical importance. In each equation a block of socio-demographic and
clinic variables were entered first in order to control for the associations
237
between these variables and the dependent variable, followed by
cognitive and mood variables (enter method). In the first MHRA, although
depression is one of the studied outcomes, due to its importance in
relation to disability, depression was entered in step two as an
independent variable with the other cognitive variables (Table 6). In the
second MHRA, due to its importance on depression, disability was entered
in step two as an independent variable with the other cognitive variables
(see Table 7). In Table 8 the contributions of a number of variables to
pain intensity are described. In order to control for Type I error, a
Bonferroni adjustment was done once more for each group of analyses.
Level of significance was adjusted dividing p at 0.05 by the number of
variables entered in the regression analyses for each predictor. The
adjusted p value for the each group of variables was: disability (0.05/11
= 0.005), depression (0.05/13 = 0.004), and pain intensity (0.05/5 =
0.01).
238
Table 5.6 MHRA predicting disability (Australian sample)
Step and predictors
Criterion
Total R²
F
df
R² Change
F change Betaª
t
variable:
Disability
Step1:
0.20
21.80** 256
0.20
21.80**
Level of education
-.06
-1.2
Gender
-.01
-0.3
Pain intensity
.27 5.3**
Step 2:
0.41
22.21** 251
0.21
18.09**
Depression
.14
2.4
Active engagement
.26
3.9**
Pain willingness
-.02
-0.4
Catastrophising
.04
0.7
Self-Efficacy
-.51 -6.9**
ª Standardised regression coefficient * P ≤ 0.005 ** p ≤ 0.001
Physical disability measured by RMDQ was significantly predicted
by a block of variables that included level of education, gender and pain
intensity (accounting for 20% of the variance in disability), but of these,
only pain intensity contributed significantly to disability. In the second
step measures of depression, activity engagement, pain willingness,
catastrophising and self-efficacy were entered into the analysis as a
block. These variables accounted for an additional 21% of variance in
disability, but only self-efficacy and activity engagement were significant
predictors of disability (p ≤ 0.001).
239
Table 5.7 MHRA predicting depression (Australian sample)
Step and predictors
Betaª
t
Gender
-.01
-0.1
Pain site
.01
0.3
Pain intensity
-.08
-1.4
Pain duration
.01
0.1
Criterion
Total R²
F
df
R² Change
F change
245
0.03
1.89
variable:
Depression
Step1:
0.03
Step 2:
0.39
1.89
17.35**
240
0.36
28.86**
Disability
.15
2.2
Active engagement
-.18
-2.5
Pain willingness
-.19
-3.5**
Catastrophising
.18
3.1*
Self-Efficacy
-.26
3.2*
ª Standardised regression coefficient * P ≤ 0.004 ** p ≤ 0.001
Although gender, pain site and pain duration were not associated
with depression these variables were entered in the analysis to make it
more similar to the analysis conducted with the Brazilian sample.
Socio-demographic and clinical variables accounted for only 3% of
the variance and did not contribute significantly to depression, which
confirmed the lack of correlation between gender, pain site, pain duration
and pain intensity and depression.
240
After controlling for the variables entered in the first step, disability
and cognitive variables were entered in step two. Altogether this group of
variables explained an additional 36% of the variance on depression, with
pain willingness (beta weight = -.19, t= -3.5 p=0.001), catastrophising
(beta weight = .18, t= 3.1 p = 0.002) and pain self-efficacy (beta weight
= -.26, t= - 3.2 p = 0.002) predicting depression. Physical disability and
activity engagement did not predict depression at a significant level.
In the third MHRA (Table 5.8) psychological variables were
examined as predictors for pain intensity. A previous MHRA was
conducted entering gender in the equation, which did not predict pain
intensity (Rh= 0.0) and therefore was taken out of the equation.
Table 5.8 MHRA predicting pain intensity (Australian sample)
Step and predictors
Total R²
F
df
R² Change
F change
0.11
6.42**
255
0.11
6.42**
Betaª
t
Criterion variable:
Pain intensity
Self-Efficacy
-.34
-4.0**
Pain willingness
-.15
-2.4
.12
1.5
-.05
-0.6
.06
-0.9
Active engagement
Depression
Catastrophising
ª Standardised regression coefficient * P ≤ 0.01 ** p ≤ 0.001
Cognitions and mood variables explained 11% of the variance
however self-efficacy was the only variable to attain a significant p level.
241
In the next section the results of the logistic regression for work
status are presented.
For this purpose, correlations between the variables entered in the
regression were examined. As reported in Table 5.5 there were no
correlations among variables superior to 0.54 (except for the correlations
between activity engagement and self-efficacy 0.67, and acceptance and
its scales), therefore only total acceptance was kept in the analysis.
Correlation coefficients indicated multicollinearity was not a problem.
However, as all the variables were coded into dummy variables (into the
same way as it was coded in the Brazilian sample) correlations were
examined again. All correlations were below 0.30, which confirmed the
lack of multicollinearity even when the variables were re-coded.
For the logistic regression, all the variables were re-coded as
dichotomous. The dependent variable (work status) was coded as
follows: Patients who were working or partially working were coded 0,
and patients who were not working were coded 1.
Since work status is affected by age, only participants who were
more than 18 years old and less than 65 years old were selected for the
analysis. Thus, the numbers of available subjects decreased to 207. Mean
age was used as the cut off point (44). Patients with less than 44 years
old were coded 0, while those with more than 44 were coded 1).
Pain in any site was coded 0, while 1 was equal to pain in two or
more pain sites. Pain duration was coded 0 for patients with pain for up
to 5 years, and 1 for patients who were in pain for 6 years or more. Pain
intensity cut off point was established at 5.
242
Education was also coded as a dummy variable. Patients with less
than 12 years of education or equivalent levels were coded as 1, while
subjects with post-school technical education or tertiary were coded as 0.
All the disability and psychological measures were coded in the
same direction using upper quartile score as a cut off point (i.e. scores
lower than the third quartile were coded 0 and the upper quartile scores
were coded 1). However, when higher scores on the measure was a
positive outcome, it was coded 0 and lower scores were coded 1 (i.e.
self-efficacy and acceptance scales).
Reduced (i.e. parsimonious models) were produced by a process of
backwards elimination of the independent variables. At each stage, the
effect of dropping out an independent variable was assessed using the
likelihood ratio test at a significant level p=0.05. Odds ratios, beta
coefficients and confidence intervals were inspected at each stage to
check for possible confounding or effect modification and the goodness of
fit of the model.
Step 5 (of seven steps) of the regression for work status attained
the best goodness of fit. Although not attaining significant p levels, some
variables were kept in the regression model due to their contribution with
the best fit of the model. In this case if an independent variable with a Pvalue exceeding P=0.05 improved the model fit, it was retained in the
reduced model.
After observing these criteria and examining other possibilities for
coding the variables, the best model was chosen. Similar to the
procedure used in Study Two, analyses were run coding questionnaires
243
scores on groups according to percentile, quartiles and mean cut off
point, and different age grouping as well. The results found for the bestfit model did not differ significantly from the ones using other forms of
categorisation.
Table 5.9 Logistic regression analysis for work status with adjusted odds
ratio, p values and confidence intervals (Australian sample)
Variable
Adjusted odds ratio*
95% C.I.
P level
Pain site (two or more =1)
2.35
1.24 – 4.47
0.009
Age (≥ 44 years =1)
0.38
0.20 – 0.70
0.002
Educational level (‹12 years =1)
1.94
1.06 – 3.56
0.03
Depression – DASS (≥ 8 =1)
2.53
1.24 – 5.17
0.01
Disability (RMDQ) ª (≥ 12 =1)
1.81
0.85 – 3.87
0.12
Catastrophising (PRSS)ª (≥ 2.7 =1)
0.53
0.25 – 1.12
0.09
*Pain intensity, pain duration, gender, self-efficacy and acceptance were also
included in the regression
ª Retained for improved model fit.
In this model, pain site, educational level, age and depression were
significant risk factors for work status. These results indicate that
participants with pain in two or more sites had 2.35 more chances of
being unemployed due to pain than those with pain in only one site.
People aged 44 and over have 62% less chance of being unemployed
than those in the younger group (less than 44). Patients with lower
educational level (having up to 12 years of education) had nearly twice
the likelihood of being unemployed (odds ratio=1.94, p=0.04) than those
with higher education. Higher depression scores also was a potent risk
244
factor for unemployment due to pain (odds ratio=2.48). Although,
catastrophising was kept in the regression due to its contribution for the
goodness of fit of the model it did not attained a significant p level
(p=0.05).
Pain intensity, pain duration, gender, disability, self-efficacy and
acceptance did not seem to be risk factors for unemployment for patients
with chronic pain in the Australian sample.
245
5.8 Discussion
In this section the major findings regarding the Australian and the
Brazilian sample will be compared and examined in relation to the
existing literature.
Table 5.10 Socio-demographic and clinical characteristics of the
Australian and Brazilian sample
Australian sample
Brazilian sample
No (%)
No. (%)
49.2 (SD=14.8)
48.9 (SD=14.0)
83 (26.7)
81 (26.0)
228 (73.3)
230 (74.0)
74 (23.7)
55 (17.7)
188 (60.5)
200 (64.3)
49 (15.8)
56 (18.0)
77 (25.7)
101 (32.5)
146 (45.0)
89 (28.6)
88 (29.3)
121 (38.9)
Working
183 (58.8)
179 (58.9)
Unemployed due to pain
128 (41.2)
125 (41.1)
72 (24.2)
87 (28.0)
5.8 (SD:2.0)
6.2 (SD: 2.4)
27 (8.7)
36 (11.6)
Cervical, shoulders and upper limbs
44 (14.1)
48 (15.5)
Back or spine
31 (10.0)
16
(5.1)
Lower back and lower limbs
46 (14.8)
30
(9.6)
Demographic and clinical characteristics
Age (mean)
Gender
Male
Female
Marital status
Single
Married
Separated, divorced or widowed
Educational Level
Less than year 10 in Australia
4 to 8 years in Brazil
Year 10 to 12 or technical studies in Australia
9 to 11 years (and/or technical) in Brazil
Higher level of education (ie. university)
Employment status
Pain duration (Mode was 3 to 5 years)
Pain intensity (mean)
Major pain sites
Head, face, neck
Two or more major sites
Other
107 (34.4)
140 (45.0)
56 (18.0)
41 (13.2)
246
As expected, due to the matching process, there were no
significant differences (p>0.05) on age and gender between these two
samples. There was a significant difference in average pain intensity
between the samples, but this difference would not be considered
clinically significant. Pain duration on both samples also did not differ
significantly (p> 0.05). Furthermore, in both samples the majority of
participants had pain in two or more sites.
Regarding educational level, these two samples had a significant
difference on distribution (Chi-square = 111.26 p= 0.001). The Brazilian
sample had a higher percentage of participants with 4 to 8 years of
education compared to the Australian sample (32.5% and 25.7%), as
well as more participants with tertiary education (i.e. universitary or a
higher degree) (38.9% versus 29.3%). The Australian sample had a
higher percentage of participants with 10 to 12 years of education or
technical courses (45% and 28.6%).
The differences between samples are probably related to the
source of the data. In the Brazilian sample nearly half came from private
clinics (47.5%), thus had a higher socio-economic level (compared to the
general Brazilian population), while in Australia data were collected in a
public hospital (where only a third were privately insured). Although level
of education is distributed differently within the samples, this difference is
not extreme and should permit further comparisons. Furthermore, the
samples were matched on other important variables (i.e. age and
gender).
247
Although the two samples were not intended to be representative
of pain patients in both countries, these findings suggest that although it
could be expected that the Australian and Brazilian sample would present
several differences, they are more similar than different. The biggest
difference was regarding educational level, which is to be expected. The
samples presented several similarities (e.g. higher number of females,
similar pain intensity levels, pain duration, pain site, work status).
Therefore it can be hypothesised that the differences regarding the
relationships
among
socio-demographic,
clinical
and
psychological
variables are more related to cultural differences (e.g. social learning) as
proposed by some biopsychosocial models (e.g. Skevington, 1995) than
sample differences regarding some variables (i.e. educational level).
Although in a lower percentage in the original Australian sample
(57% when not matched for gender), the higher prevalence of women in
both samples is in accordance with the literature, which suggests that a
number of pain syndromes are more common among women and that
women seek health care more often than men (Blyth et al. 2001; Gureje
et al. 1998).
The high prevalence of unemployment associated with chronic pain
was very similar in both samples (41%). This finding is also reported in
the literature suggesting that chronic pain can have a great social and
economic impact (Blyth et al. 2001; Breivik et al. 2006; Raspe et al.
2004; van Leeuwen et al. 2006).
Scores of both samples on a number of measures will be described
and compared in the next table (Table 5.11).
248
Table 5.11 Comparison between questionnaire means of the Brazilian and Australian samples
Questionnaires
Brazilian
Australian
Sample
Sample
Means (SD)
Means (SD)
12.03 (6.21)
11.66 (6.62)
1.27
P = 0.20
-0.34
1.59
Pain Self-Efficacy Questionnaire
34.84 (14.08)
27.57 (13.65)
6.50
P = 0.001
5.07
9.46
DASS - Depression Scale
14.03 (12.02)
11.73 (10.44)
3.84
P = 0.001
1.66
5.14
2.38 (1.38)
2.73 (1.50)
-2.70
P = 0.007
-0.45
-0.07
Chronic Pain Acceptance Questionnaire
60.20 (18.11)
59.65 (17.56)
-0.66
P = 0.50
-3.72
1.83
Activity Engagement Scale
39.89 (14.07)
32.67 (12.47)
6.45
P = 0.001
4.81
9.02
Pain Willingness Scale
20.21 (11.08)
28.08 (10.80)
-8.92
P = 0.001
-9.60
-6.14
Roland Morris Disability Questionnaire
Catastrophising Scale
t-test of
Level of
95%
significance
significance
confidence
interval
Lower - Upper
Expected t is 1.96 at a significant level of 0.05
249
Significant differences in mean scores between the samples were
found on all scales except for the Roland and Morris Disability
Questionnaire and the Chronic Pain Acceptance Questionnaire total score.
The Brazilian sample had higher scores on depression, self-efficacy and
activity engagement than the Australian sample, and lower scores on
catastrophising and pain willingness. Mean scores on the disability
measure (RMDQ) indicate that these samples were similar on levels of
self-reported
disability.
A
similar
trend
occurred
with
levels
of
acceptance.
What might be more important than their respective differences on
these dimensions is whether or not different outcomes might be found
(e.g. different roles of psychological factors in relation to disability).
It is plausible to expect that as living conditions in a developing
country such as Brazil may be more demanding (e.g. socio-economic
disparities, lack of work, and competition) than in Australia. In Brazil, if
an adult is unable to work, there is no financial support from the
Government. Whereas in Australia, there is a universal welfare system
that provides some financial support for the unemployed. Accordingly,
Brazilians might be expected to be more resilient than Australians with
chronic pain. This might be reflected in higher pain self-efficacy levels in
the Brazilian chronic pain patients.
The fact that the Brazilian sample had higher scores on depression
and lower scores on catastrophising when compared to the Australian
sample also raises some questions. Firstly, it confirms that although
these two constructs are correlated they are distinct. Second, although
250
prevalence of depression varies in different countries and cultures (Bijl et
al. 2003; Jorge 2003) in Latin cultures display of affect and suffering is
more acceptable, thus Brazilians could be culturally encouraged to share
their
feelings
Furthermore,
and
some
cognitive
studies
symptoms
have
shown
more
that
than
Australians.
depression
can
be
associated with lower socio-economic level (Jorge 2003). It is also
possible that key drivers of depression in the two countries might be
different.
This same rationale could be extended to catastrophising, but as
noted,
Australians
had
higher
scores
on
catastrophising.
Another
explanation for this feature could be that in general Brazilians are usually
thought to be very optimistic, have a strong faith in God and to have
positive expectations about the future. Indeed, the researcher observed
that when answering item 5 of the catastrophising scale (i.e. “I am a
hopeless case”) several subjects verbally replied or exclaimed “no there
is hope for me, I cannot say that”. This may illustrate that this type of
belief is not socially acceptable.
As outlined by several authors (e.g. Skevington, 1995; Raspe et
al., 2004; Bates et al., 1993; Edwards et al., 2005), there is no a priori
reason to expect noxious stimuli perception differences based in the
biological basis, however there is evidence supporting intercultural
differences
in
perceiving
and
reporting
pain,
as
well
as
other
psychological features. Therefore, the differences on scores of selfefficacy, catastrophising, depression and activity engagement and pain
willingness are expected to occur due to inter-cultural differences.
251
In relation to catastrophising, although in the Brazilian culture
displays of emotions are encouraged, not having a faith in future or being
negative is discouraged. This may occur due to religious beliefs, since the
Brazilian culture and social beliefs are strongly influenced by religion. As
described by Rippentropa et al. (2005), religion/spirituality can have
costs and benefits for the health of those with chronic pain. Therefore, it
can be hypothesised that this positive outcome/feature (i.e. having lower
levels of reported catastrophising than the Australian sample) may be
related to this issue.
Results from the Chronic Pain Acceptance Questionnaire were
mixed. Whilst there were no differences between the samples in the total
mean
score,
Brazilians
had
higher
mean
scores
in
the
activity
engagement scale (which reflect engaging in normal life activities despite
pain), while Australians had significant higher mean scores in the pain
willingness scale (which reflects need to engage into activities to avoid
pain). Due to the mixed results, lack of evidence and the novelty of this
concept, it is unclear what to make of these differences, and further
investigation of this issue is clearly needed.
There was no significant difference between samples regarding
gender on mean scores for all measures. As noted previously, disability,
depression and catastrophising are reported to be moderated by gender
differences (e.g. Sullivan et al., 2005), however these findings were not
replicated in this study in both samples.
There was no significant difference on mean scores on most of the
measures in both samples regarding pain site. However, in the Brazilian
252
sample patients with pain in two or more sites scored significantly higher
on disability and depression compared to the Australian sample.
The findings that pain site contributed to disability is often reported
in the literature, although with some variance (Von Korff et al. 1992). In
general, multiple pain sites appear to be more disabling, although specific
sites do not seem to play an important role on emotional adjustment
(Von Korff et al. 1992). This finding was partially confirmed in these
samples, since in the Brazilian sample, pain in more than one site was
associated with higher levels of disability and depression, and predicted
disability. Whilst in the Australian sample having pain in two or more
sites was a predictor of unemployment.
Regarding differences associated with educational level. In both
samples participants with lower levels of education had higher scores on
disability (p ≤ 0.01), which suggests that they are more disabled than
those with higher levels of education.
Although economic/social levels were not assessed in these series
of studies, it can be expected that lower levels of education will be
associated with lower socio-economic levels. The findings that lower
levels of education (i.e. less than 10 years) were associated with higher
scores on disability (measured by the RMDQ) is consistent with others in
the literature in different cultures and countries (Blyth et al. 2001;
Eriksen et al. 2003; Hagen et al. 2006; Tan et al. 1997; Vowles et al.
2004).
253
The relationship between scores on the different dimensions was
also analysed. In both samples participants who were not working due to
pain had lower scores on self-efficacy and higher scores on disability,
depression and catastrophising than the participants who had pain but
were still working. In the Brazilian sample the not working group also
differed significantly on levels of acceptance. This did not occur in the
Australian sample. This pattern suggests that in both samples, people
that have chronic pain and are working are better adjusted emotionally
and less physically disabled.
Although the relationship between chronic pain, disability and
psychological factors can be bi-directional, a number of studies have
shown that some psychological factors can play an important role in
transition from acute to chronic pain and in disability (Linton 2000; Linton
2005; Pincus et al. 2002).
The
relationship
between
socio-demographic,
clinical
and
psychological variables and disability, depression and pain intensity also
occurred in a slightly different fashion in these samples, but a similar
trend was evident in both.
5.8.1 Variables contributing to disability in the Australian and in
the Brazilian sample
Only in the Australian sample did pain intensity contribute
significantly to disability, while in the Brazilian sample level of education
and pain site had a similar contribution to disability. Although different
254
factors contributed to disability in the Australian and in the Brazilian
sample, as noted before similar findings have been reported in the
literature (i.e. pain intensity) (Marhold er al., 2002). The contribution of
educational level to pain prevalence and disability is often reported in the
literature (e.g. Blyth et al., 2001), supporting the findings of Study Two
as well.
Due to socio-economic conditions, in the Brazilian sample it could
be expected that people with lower levels of education are in jobs that
are more physical in nature. As a result, this group could be subjected to
higher physical loads and demands (when compared with those with
higher educational levels), which could contribute to chronic pain and
associated disability.
The fact that level of education only contributed to disability in the
Brazilian sample may reflect the contribution of social factors to chronic
pain and disability, and the need to consider population, socio-economic
and
cultural specificities
when
treatments
produced
in
developed
countries or in other contexts are applied to the Brazilian population. For
example, due to social contingencies level of disability in Brazil may be
more influenced by biological and social factors than individual factors
(i.e. psychological), while in more developed countries the availability of
treatment for organic pathologies and more favourable socio-economic
features may make individual factors (e.g. activity engagement) more
important. As outlined earlier, it is not expected that the two samples
would differ markedly in organic factors (i.e. type of pathology),
therefore it can be hypothesised that socio-economic and cultural factors
255
have a different contribution to disability in the Brazilian sample than in
the Australian. This issue will be further explored when comparing both
samples on factors involved in prediction of work status.
Among psychological variables, in both samples self-efficacy had
the highest contribution to disability among all the psychological
variables. However, in the Australian sample activity engagement
contributed to disability as well, which did not occur in the Brazilian
sample.
These findings confirm the role of self-efficacy on disability
(Altmaier et al. 1993; Arnstein 2000; Arnstein et al. 1999; Nicholas
2007; Nicholas and Asghari 2006), specially when considering that in the
Brazilian sample pain intensity did not contribute to disability and that in
the Australian sample self-efficacy had a higher contribution than pain
intensity.
The finding that self-efficacy was the most important predictor in
both samples confirms the role of self-efficacy in disability as proposed by
Bandura (1977) and Nicholas (2007). Based on these authors, the belief
that one can cope with chronic pain or engage in activities despite pain
makes a large contribution to levels of physical disability.
The finding that pain willingness also contributed to disability, but
only in the Australian sample also confirms McCracken and Eccleston
findings (2005, 2006) to some extent. On the other hand, the lack of
contribution of CPAQ and the activity engagement scale in both samples
raises doubts about the CPAQ and the role of acceptance in relation to
disability.
256
5.8.2 Variables contributing to depression in the Australian and in
the Brazilian sample
Regarding the contribution of socio-demographic and clinical
variables to depression, in both samples these variables did not predict
depression at significant levels. However in the Australian sample
catastrophising,
pain
willingness
and
self-efficacy
contributed
to
depression. Whilst in the Brazilian sample, catastrophising was the only
predictor of depression.
These findings confirm the role of psychological factors in
depression associated with chronic pain. In both samples clinical factors
(e.g. pain intensity and physical disability) were less important than the
psychological factors. This confirms previous findings (e.g. Linton, 2000).
The contribution of catastrophising to depression, which occurred
in both samples, is often reported in the literature (eg. Sullivan et al.,
2005; Nicholas and Asghari, 2006). However, findings reporting the
contributions of self-efficacy and pain willingness to depression have also
been
reported
(i.e.
Nicholas
and
Asghari,
2006;
McCracken
and
Eccleston, 2006 respectively). Therefore, while the role of catastrophising
in relation to depression has been confirmed, the findings on the
Australian sample suggest that other factors may contribute as well. This
last finding could suggest that in different populations different factors
might play a differing role in a specific outcome, such as depression.
257
5.8.3 Variables contributing to pain intensity in the Australian and
in the Brazilian sample
When examining the predictive factors for pain intensity, gender
contributed to pain intensity in the Brazilian sample, but not in the
Australian.
Gender differences (female) have been found to be associated with
higher reports of pain intensity (Keogh et al. 2006; Woodrow et al.
1972). Although in many societies it may be more acceptable for women
to report pain and suffering than men (Hobara 2005), these findings have
been replicated only in the Brazilian sample. On the other hand, the
higher percentage of female subjects in both samples confirms the
evidence described in the literature (i.e. there is different pain prevalence
associated to gender and different responses to pain) (Blyth et al., 2001).
Among psychological variables self-efficacy was the only predictor
of pain intensity and occurred in a similar trend in both samples.
Although, the contribution of self-efficacy to pain intensity has not
been widely investigated, other findings that report the contribution of
catastrophising, control and acceptance to pain intensity (e.g. Sullivan et
al., 2005 and McCracken 2005 respectively) could support the role of
self-efficacy in pain intensity. That is, a person’s belief in their ability to
function despite pain (Nicholas 2007) may contribute to lessen the focus
on pain, as well as provide some sense of control of the pain. This would
have an effect opposite to what happens in people who catastrophise (i.e.
keep or increase attention on pain or noxious stimuli).
258
5.8.4 Examining risk factors for work status in the Australian and
in the Brazilian sample
When examining risk factors for unemployment in both groups a
similar pattern was found, but there were some different trends. Age and
educational levels were significant risk factors for both samples, but
educational level was the most important risk factor for unemployment
and had a much higher odds ratio in the Brazilian sample. On the other
hand, in the Australian sample pain site and depression were also risk
factors for unemployment. While in the Brazilian sample physical
disability and self-efficacy were risk factors for unemployment.
Age
and
educational
level
are
in
general
risk
factors
for
unemployment independently of having chronic pain. For chronic pain
patients, age and lower level of education or qualification have been
found to be a barrier to return to work (Tan et al. 1997; Vowles et al.
2004; Watson et al. 2004), and can be considered an additional risk for
unemployment in chronic pain patients in different countries.
Nevertheless,
the
contribution
of
educational
level
to
unemployment in the Brazilian sample (3.49 at a p=0.001), nearly 2
times more than in the Australian sample (1.94 at a p=0.03) is
meaningful when considering that the rate of unemployment in Brazil
(9.1%) is nearly two times higher than in Australia (4.9%) and that
educational level might mediate unemployment in a developing country
more than in a developed country (Lampreia 1995). Therefore, due to
social contingencies (e.g. availability of jobs for disabled people), having
259
a chronic disease for people that have lower educational levels may
increase the likelihood for unemployment in Brazil more than in Australia.
Another major difference between the samples was that in the
Australian sample among all variables depression was the most potent
risk factor for unemployment, while in the Brazilian sample, depression
did not attain a significant level. On the other hand, among the
psychological variables self-efficacy obtained the higher odds ratio for the
Brazilian sample, but did not reach significant levels in the Australian
sample.
Considering the characteristics of a developing country, the risk
factors for unemployment found in the Brazilian sample are relevant and
meaningful. Beside educational level and age, being physically disabled
increases the risk for unemployment. Having a low self-efficacy belief in
the ability to function despite pain, could also contribute to failure to
return to work (or to remain at work).
While,
pain
unemployment,
site,
being
age
and
depressed
education
seems
to
are
risk
contribute
factors
largely
for
to
unemployment in the Australian sample. The contribution of depression
to unemployment has been reported in other studies conducted in
developed countries (Marhold et al. 2002; Sullivan et al. 1992; Sullivan
et al. 1998).
It could be hypothesised that, considering the socio-economic
characteristics of Australia (i.e. low level of unemployment and flexibility
of working conditions) individual factors such as being depressed could
be a major risk factor for not returning to work.
260
5.8.5 Summary of discussion
Taken together, these findings suggest that in both samples
biological, social and psychological factors interact dynamically and
contribute to disability, depression, pain intensity and work status.
In general, the Australian and the Brazilian sample presented a
several similarities and only a few differences regarding the contribution
of psychosocial factors to disability and emotional adjustment.
These findings confirm the hypothesis that the relationship
between self-efficacy beliefs, acceptance, catastrophising, depression and
disability would occur in a similar pattern in these two samples and in
accordance with broader biopsychosocial perspectives.
Furthermore these findings are in accordance with the literature
regarding ethnic variations in responses to pain (e.g. Bates et al., 1993;
Edwards et al., 2001; Raspe et al., 2004; Skevington, 1995), specially
when considering the findings regarding risk factors for unemployment.
The bulk of evidence and perspectives suggest that biological factors
cannot account for differences in perception of noxious stimuli, but
cultures vary in the way they respond to chronic pain. On the other hand,
there is evidence that ethnic differences regarding responses to pain
seem to be smaller when ethnic groups are matched on confounding
variables (i.e. socio-economic variables) (Tait and Chibnall 2005).
This conclusion would suggest that the evaluation of patients with
chronic pain and treatment for chronic pain based on models generated
in other countries could be applied to the Brazilian population with
chronic pain.
261
CHAPTER SIX
General Discussion
6.1 General discussion
In this section the main findings of this series of studies will be
highlighted according to the existing literature in this field. The strengths
and limitations of this study will be also presented, as well as suggestion
for further research.
Study One
The findings of Study One suggest that the Roland and Morris
Disability Questionnaire (Roland and Morris 1983), the Pain Self-Efficacy
Questionnaire (Nicholas 1989), the DASS – Depression Scale (Lovibond
and Lovibond 1995) and the PRSS – Catastrophising Scale
(Flor et al.
1993) have adequate validity and reliability properties when used in a
Brazilian chronic pain population. On the other hand the psychometric
properties of the Chronic Pain Acceptance Questionnaire (McCracken
1999) were not confirmed, except for the activity engagement scale.
The results of the present study support previous findings (Flor et
al. 1993; Lovibond and Lovibond 1995; Nicholas 1989; Nicholas 2007;
Roland and Fairbank 2000; Roland and Morris 1983; Taylor et al. 2005)
suggesting that all the studied measures are valid, reliable and that
norms can be established to be used in the Brazilian chronic pain
population.
262
Furthermore, when analysing the predictive properties of the
above measures, correlational and regression analyses conducted in
Study Two and Three confirmed the findings of Study One.
This series of studies also examined the predictive properties of a
number of socio-demographic and psychological factors on disability and
depression associated with chronic pain, and tested whether the
relationships among self-efficacy beliefs, acceptance, catastrophising,
depression and disability in a Brazilian chronic pain sample were
consistent with the evidence reported in the international pain literature
and consistent with current biopsychosocial models of chronic pain.
Study Two
The findings of Study Two suggest that in the Brazilian sample
although socio-demographic (i.e. educational level) and clinical variables
(i.e. pain site) contribute to disability, self-efficacy had a greater
contribution to disability as well as to pain intensity. The role of selfefficacy on disability has been reported elsewhere (Altmaier et al. 1993;
Arnstein 2000; Arnstein et al. 1999; Keefe et al. 2004; Nicholas 2007;
Nicholas and Asghari 2006; Turk and Okifuji 2002) and is supported by
the findings of this study in a different culture than the ones investigated
by most studies. These findings suggest that even when a number of
socio-demographic, clinical and psychological variables are taken into
account, self-efficacy seems to be an important predictor of disability.
Indeed, in this Brazilian chronic pain sample self-efficacy was also an
important risk factor for unemployment as well.
263
These findings reinforce Bandura’s (1977) position that selfefficacy is an important predictor of behaviour (e.g. reported disability,
pain intensity and work status). The contribution of self-efficacy to
disability is also in accordance with coping strategies models (Lazarus
and Folkman, 1984 and Lazarus, 1993) which consider that coping
strategies are also a function of beliefs, among other factors. Based on
this perspective, it can be expected that chronic pain patients with low
self-efficacy are likely to have ineffective coping strategies that may
mediate physical disability (Turk 1999), as well as efforts to work despite
pain. Indeed, recent evidence suggest that self-efficacy is one of the
most important contributor to disability and a number of treatment
outcomes (Keefe et al. 2004; Turner et al. 2007).
When the contribution of socio-demographic, clinical and cognitive
variables to depression was examined, catastrophising was the most
important (and the only) predictor of depression.
This finding is often reported in the literature, which suggests that
catastrophising is a superior predictor of depression compared to other
beliefs and coping responses (Sullivan and D'Eon 1990; Turner et al.
2000), acceptance (Nicholas and Asghari 2006; Viane et al. 2003), and
self-efficacy and fear-avoidance (Nicholas and Asghari 2006).
Altogether, these findings may suggest that the degree to which a
chronic pain patient experiences depression is largely influenced by
factors other than pain intensity, physical disability, coping and selfefficacy. As suggested by cognitive and behavioural models (Beck 1976;
Sullivan
and
D'Eon
1990),
cognitions
(specifically
catastrophising)
264
strongly mediate how people interpret the nature of their reality and
consequently could possibly affect their mood. Thus, being depressed in
the context of having chronic pain has to do not only with being in pain or
disabled, but more to do with cognitive-evaluative processes.
Regarding
depression,
the
Geisser
catastrophising
relationship
et
contribute
al.
between
(1999)
more
to
pointed
the
catastrophising
out
evaluative
that
and
it
and
seems
affective
dimensions of pain. Therefore, based in this conception it could be
expected that catastrophising would have an important contribution to
depression; especially if depression is understood as one of the
consequences of pain.
This view is also is accordance with the existence of three
dimensions
of
catastrophising
(i.e.
rumination,
magnification
and
helplessness) as suggested by Sullivan et al. (1995) or two dimensions
(i.e. rumination and helplessness) as found in Study One and supported
by other studies (Chibnall and Tait 2005). As it can be observed these
dimensions are related to evaluative and affective components of pain,
and therefore it could be expected that they would interact more with
other dimensions from the same sphere.
The finding that in Study 2 factor 2 of the catastrophising scale
(i.e. helplessness) was a stronger predictor of depression than factor 1
(i.e. rumination) confirms the evidence that catastrophic beliefs have
cognitive and affective dimensions (Sullivan et al. 1995).
The finding that the helplessness component of catastrophising
would have a more important contribution to depression than the other
265
dimension found (i.e. rumination) is in accordance with the pain literature
on the relationship between depression and catastrophising (Keefe et al.
2004; Sullivan et al. 2001b).
The finding that acceptance did not contribute significantly to
disability, depression and pain intensity was at variance with some
previous findings reported in the literature (i.e. McCracken et al., 2003;
2004; 2005; 2006). These differences may be due to measurement
problems with the CPAQ and the fact that McCracken et al. (1999; 2004)
did not control for the possible effects of other cognitive variables such as
catastrophising,
fear-avoidance
and
self-efficacy.
Clearly,
further
research should be conducted on this concept in relation to chronic pain
(e.g. Nicholas and Asghari, 2006).
Depression also did not contribute to disability and pain intensity in
the studied sample.
Although there is a high prevalence of depression in chronic pain
patients and the role of depression in chronic pain is recognised (i.e. poor
responses to treatment), the nature of this relationship remains unclear
(Worz, 2003). Broadly there are three models that describe the
relationship of chronic pain and depression (i.e. antecedent, consequence
and bidirectional hypotheses (Worz 2003). Most of the evidence suggests
that depression may follow chronic pain (Fishbain et al., 1997).
In addition, the relationship between pain intensity, disability and
depression has been widely reported in the literature, but with a large
variance in findings (McCracken and Eccleston 2005; Turk et al. 1995),
These variance on results may occur due to several reasons; one of them
266
may be related to measurement problems (Pincus and Williams 1999;
Taylor et al. 2005). Since a number of measures used in these studies
have somatic items, this feature may inflate scores and thus increase the
contribution of depression to a number of outcomes.
Furthermore, some studies have reported that depression does not
appear to be an important predictor of physical disability, especially when
compared to other factors such as catastrophising and self-efficacy (e.g.
Nicholas and Asghari, 2006; Turner et al., 2007).
Therefore, when taking into account only cognitive symptoms of
depression, it may be possible that depression will lose its power to
predict disability, and may be better understood as a consequence of
having chronic pain, which may mediate other outcomes.
Altogether, the findings of this study are in accordance with the
literature, and although depression did not contribute to disability and
pain intensity in this population, it seems reasonable to expect that
depression will somehow influence other pain-related outcomes indirectly
(e.g. number of consultations, use of medication).
When examining risk factors for unemployment in the Brazilian
sample, educational level, age, physical disability and self-efficacy were
found to be significant predictors of unemployment. However it is
important to mention that in this series of studies, in the chronic pain
context unemployment was interpreted as an outcome or an indicator of
disability, and a number of variables that are related to work status (i.e.
work conditions) were not analysed.
267
The finding that age, educational level and disability were risk
factors for unemployment is in accordance with findings reported in
studies conducted in developed countries (e.g. Vowles et al., 2004).
These
findings
are
clinically
meaningful
and
in
accordance
with
biopsychosocial perspective of chronic pain.
Furthermore, in general, age and educational level can be considered
risk factors for unemployment even for healthy subjects, so when
considering that these aspects were investigated in patients with chronic
pain in a developing country it would be expected that they would occur
and contribute to unemployment even in a higher magnitude.
The contribution of self-efficacy to unemployment in patients with
chronic pain has not received much attention, but there is some evidence
that self-efficacy is related to work status in people with chronic pain
(Adams and Williams 2003; Cohen et al. 2000). The present study’s
findings that self-efficacy was predictive of work status is therefore
consistent with these earlier findings and suggests the topic merits
further investigation.
While other work related factors (e.g. social security, availability of
modified work duties) may contribute to work status (Teasell and
Bombardier 2001), self-efficacy beliefs, as an individual factor, seems to
make an important contribution to work status; in a similar fashion that it
occurred to physical disability.
As outlined by a number of authors (e.g. Adams and Williams,
2003), the work status of chronic pain patients seems to depend less on
268
medical variables than psychosocial factors. The findings of this study
although with some limitations are in accordance with this evidence.
Study Three
In Study Three, the same variables examined in Study Two were
tested in an Australian sample with chronic pain and compared with the
findings of the Brazilian sample and the current literature.
In the Australian sample pain intensity, self-efficacy and pain
willingness
contributed
significantly
to
disability.
Regarding
the
contribution of socio-demographic, clinical and psychological factors to
depression, in the Australian sample catastrophising, pain willingness and
self-efficacy contributed to depression. In relation to the contribution of
socio-demographic, clinical and psychological factors to pain intensity,
self-efficacy was the only variable to attain a significant p level.
Regarding work status, pain site, educational level, age and depression
were significant risk factors for unemployment in the Australian sample.
Most of the findings of the Australian sample confirmed the results
that occurred in the Brazilian sample and have been discussed before.
That is: self-efficacy was the strongest predictor of disability and pain
intensity, and catastrophising was an important predictor of depression.
However, in the Australian sample other factors contributed to depression
as well (i.e. pain willingness and self-efficacy, in order of magnitude).
The contribution of self-efficacy and pain willingness to depression
has not been often examined, but it has been reported previously by
Nicholas and Asghari (2006) and McCracken et al. (2004), respectively.
269
In the Australian sample it could be hypothesised that high scores
on self-efficacy (i.e. having the belief in one’s ability to engage in normal
activities despite pain) would contribute to less emotional suffering and
depression. As noted before, broadly speaking the cognitive and
behavioural model (Beck 1976; Sullivan and D'Eon 1990) outline that
cognitions (e.g. catastrophising) mediate how people interpret the nature
of their reality. Accordingly, being confident in one’s ability to deal with
chronic pain and disability would minimize feelings of helplessness and
promote a sense of control regarding this situation.
The same rationale could be extended to pain willingness (i.e
recognition that avoidance and control often do not work to adapt to
chronic pain), that is; patients that would have an accepting attitude
towards pain would not engage in efforts to avoid or control pain, or
would be prepared to engage in activities while in pain. It could be
hypothesised that this attitude would generate less frustration, suffering
and feelings or depressive thoughts.
The concepts of self-efficacy and acceptance (measured by the
activity engagement and pain willingness scales) have some similar
features and both have been found to make a contribution to depression
(Nicholas and Asghari, 2006; McCracken and Eccleston, 2005). This raises
the question of whether they are different concepts.
Self-efficacy and acceptance involve acknowledging pain, however
self-efficacy also involves the recognition of personal abilities to cope with
pain or carry on with activities while in pain, whilst acceptance involves
only an attitude towards pain and not efforts to deal with pain. Thus,
270
close inspection does reveal conceptual differences, as outlined by
McCracken et al., (2004a). Even so, it could be hypothesised that both
factors would lead to less stress while experiencing pain.
It is generally agreed that pain is a multidimensional phenomenon
and that people living with chronic pain vary substantially in their
responses to it (Morley and Keefe 2007). Although a number of factors
have
been
adjustment
identified
(i.e.
as
important
acceptance,
contributors
catastrophising,
to
disability
self-efficacy,
and
fear-
avoidance) (Keefe et al. 2004), it is likely that they may share some
variance, and that for some people, populations and in different cultures
these factors may play slightly different roles. For example, self-efficacy
may have a more important contribution to disability than acceptance for
patients who are trying to return to work than those that are making an
injury related
insurance
claim. While
acceptance
might be
more
important to disability than self-efficacy in patients who have chronic pain
due to cancer and are in a terminal stage.
This is only speculation but it illustrates the possibility that the
contribution of different variables to disability and adjustment may vary
according to circumstances. As outlined by Vlaeyen and Morley (2005), it
can be expected that different people and populations may benefit from
interventions aimed at different factors involved in disability and
adjustment.
When comparing the contribution of psychosocial factors to work
status between the Australian and Brazilian sample, the findings confirmed
the role of educational level and age as risk factors for unemployment in
271
both samples. As noted, these findings have been reported in the pain
literature as important risk factors for unemployment (Hagen et al. 2006;
Vowles et al. 2004).
It is also important to notice that level of unemployment in both
samples was similar (41%), suggesting that despite having different sociodemographic and economic conditions in both countries chronic pain has a
large impact on patients living with chronic pain.
Nevertheless, the contribution of educational level to work status in
the Brazilian sample was nearly twice as high as in the Australian sample.
When taking into account the socio-economic conditions of both countries
this finding may reflect the impact of social factors on pain outcomes (i.e.
work status).
As discussed previously, level of education is not always a predictor
of work status but is frequently a predictor of higher income. The higher
contribution of educational level to work status found in the Brazilian
sample, suggests that in a developing country having a chronic illness (i.e.
chronic pain) and lower educational level may increase the risk for
unemployment. This may also occur in a developed country, but seemingly
to a lesser extent.
The contribution of depression as a risk factor for unemployment
that occurred in the Australian sample has been reported elsewhere (e.g.
Marhold er al., 2002) in similar conditions (i.e. developed countries), but
did not occur in the Brazilian sample. Therefore, it could be hypothesised
that in Australia depression might be more influential to work status than
272
in Brazil, where the contingencies mean you have to keep working
regardless of how you feel.
Since there is a greater availability and flexibility of jobs and a
welfare system in developed countries, being at work may be more
influenced by affective factors (i.e. depression); understood here as
motivational factors rather than cognitions (i.e. self-efficacy). This picture
seems not to be the case in Brazil where being disabled (which had the
second highest odds ratio among all significant variables) and having a
belief in the ability to perform an activity despite pain were stronger
determinants of work status.
In general, the findings of this series of studies confirmed the
biopsychosocial perspective of chronic pain, since they showed that
biological factors interact with social-demographic and psychological
factors in shaping disability and emotional adjustment in people with
chronic pain in a similar pattern, but in a slightly different way in two
different social contexts.
The slight differences that occurred in these two samples may be
due to sample differences, but also due to economic and cultural factors.
Hence, in different populations different factors might play a differing role
in a specific outcome, such as depression or unemployment due to pain.
As
proposed
by
some
ethnic/social
models
of
pain
(e.g.
Skevington, 1995; Bates, 1987) social learning is instrumental in the
development of meanings and attitudes toward pain.
Ethnic/social perspectives
regarding chronic
pain poses
that
attitudes, beliefs, attribution, expectations and assumptions are shaped
273
socially and that culture has an important role in pain perception and
response to pain and thus should be taken into account. However, it also
seems that when ethnic groups are matched on confounding variables
(i.e. income or social classes), these differences are relatively small
(Edwards et al. 2005; Portenoy et al. 2004).
Although, the Australian and the Brazilian sample were matched
for gender and age, and did not differ significantly on a number of other
variables such as pain intensity, pain site, pain duration, social class and
other confounding variables (e.g. work related factors) were not
controlled. Therefore other unknown variables could interfere in the
studied outcome.
The differences between samples regarding risk factors for work
status (which were the biggest differences between samples) would be
expected to occur as work status can be considered a variable that is
more likely to be influenced by social contingencies (i.e. culture and
demographic-economic factors) than physical disability, depression and
pain intensity.
Nevertheless, if other variables were studied (i.e. pain behaviour,
factors involved in compensation) other differences might appear due to
the fact that they are also mediated by other social contingencies.
However in general, the findings in both samples occurred in a
similar trend, which could be expected as both countries share a Western
cultural orientation, when compared to other cultures such as countries in
the Middle East or Asia.
274
Furthermore, data was collected in South and Southeast of Brazil,
which has a large number of European immigrants and it is more
influenced by western cultures when compared to other regions of Brazil.
It can be hypothesized that although there are differences
regarding responses to pain among different groups; that should be
taken into account. It seems that pain is a universal phenomenon, and
chronic
pain
patients
may
tend
to
share
more
similarities
than
differences.
6.2 Limitations and strengths
Limitations
Although the limitations of Study One have been previously
described, in this section the limitations of this series of studies will be
acknowledged in a broader way.
The limitations of this series of studies include collection of data
using only psychometric questionnaires, the cross-sectional design, and
to what extent the results could be generalised to the Brazilian population
with chronic pain.
All data were obtained by self-report measures, which could lead
to a number of problems: shared variance could contribute to the
magnitude of some correlations; lack of reliability and/or validity of the
measures;
and
factors
influencing
test
answer
(i.e.
recall
bias).
Furthermore, when examining the reliability of the measures, test re-test
reliabilities was not conducted due to the difficulties in contacting
275
subjects for a second application of the questionnaires; however other
reliability analyses were conducted.
Nevertheless, when considering the subjective nature of the topic
collecting data without using questionnaires would be difficult to do.
Furthermore, one of the main goals of this series of studies was to
validate a number of relevant psychometric measures to be used in the
Brazilian chronic pain population.
On the other hand, self-report is considered being the most direct
way to access pain dimensions (Turk and Melzack, 2001). Observing a
few statistical parameters and guaranteeing the psychometric properties
of the measures would minimize the influence of these problematic issues
(Jensen 2003).
The cross-sectional design of these studies also imposes limits to
any consideration of causal relationships between the studied variables
and their directions. Thus, findings based on cross-sectional data should
be supported with further replication and prospective studies.
Another limitation of this research concerns the sample employed.
The sample was not selected to be representative of Brazilian or
Australian chronic pain patients and these impose some barriers to the
generalizability of these findings. In fact, the sample was a convenience
sample constituted of chronic pain patients attending certain pain clinics.
This may produce some biased information, since this sample may
consist of subjects that did not respond to pain as successfully as a nonclinical pain population. It is also important to acknowledge that some of
the differences found between the present study and other studies may
276
be due to differences in samples, cultural differences and health system
contingencies.
Therefore, the findings of this series of studies cannot be
generalised to the Brazilian and Australian chronic pain population, but
the degree to which the findings were consistent with the literature does
provide some support for their generalizability.
Strengths
On the other hand, these studies have a number of strengths. The
psychometric properties of the questionnaires were examined and proven
to be reliable and valid, which enhance the quality of the data collected.
Second, although not representative, the sample size is moderate
(311 in each country), heterogeneous and comes from nine chronic pain
facilities in two regions of Brazil and the largest chronic pain centre in
Australia, which permits generalisation of the findings to some extent.
This study is also one of the first studies to analyse the
simultaneous contribution of a number of socio-demographic and clinical
variables and self-efficacy, acceptance and catastrophising to disability,
work status, pain intensity and emotional adjustment.
Considering these limitations and strengths, this series of studies
provides support for the use of a number of pain measures with
Brazilians with chronic pain (increasing considerably the number of
available psychological measures from 16 to 21). This series of studies
have also supported the existing evidence about the role of cognition in
adjustment to chronic pain, and they confirmed some of the features of
277
biopsychosocial models of chronic pain and the validity of internationally
produced evidence in this Brazilian population.
Furthermore, since most findings of this series of studies were in
accordance with the literature confirming biopsychosocial models of pain,
to an extent it could also be expected that treatment for chronic pain
patients based on them could be applicable to Brazilians with chronic
pain.
6.3 Conclusion
This series of studies aimed to explore some key cognitive and
affective aspects of pain in a Brazilian and an Australian sample based on
the premises of biopsychosocial models of chronic pain.
The major findings of this series of studies are in accordance with
the literature that suggest that a number of psychosocial factors may
shape the individual’s pain experience, influencing the degree to which
pain is experienced, responses to it, and the degree of interference
caused by pain (Keefe et al. 2004; Linton 2000; Pincus et al. 2002;
Skevington 1995; Turk and Okifuji 2002; Turner et al. 2007)
The major findings of this series of studies have partially confirmed
the hypotheses on which this research project was based on, that is:
1. Pain self-efficacy beliefs, acceptance, catastrophising and
depression are significant predictors of disability;
2. Pain self-efficacy beliefs, acceptance, catastrophising and
disability are significant predictors of depression;
278
3. Socio-demographic and psychological variables are risk factors
for unemployment due to chronic pain;
4. The relationship between cognitions, depression and disability
occur in a similar pattern in the Australian and in the Brazilian samples.
Although these hypotheses were stated in a general fashion, it was
not expect that all the psychological variables would equally contribute or
predict disability, work status, depression and pain intensity. As matter of
fact, based on the literature reviewed it was expected that self-efficacy
would be an important predictor of disability and that catastrophising
would contribute to depression and pain intensity. Educational level, age
and some clinical variables were expected to be risk factors for
unemployment.
It was also expected that similar findings would occur in both
samples but with some variation. Furthermore the biopsychosocial
perspective of chronic pain was expected to be confirmed in the Brazilian
chronic pain population.
A number of findings from these studies are in accordance with the
international literature
and the
biopsychosocial perspective;
which
confirms that cognitions play an important role in disability and emotional
adjustment even in different populations.
From a clinical perspective, since these findings have confirmed
the current biopsychosocial model of chronic pain, clinical treatment
procedures (based on this model) developed in other countries may be
used effectively in the Brazilian population with chronic pain. Thus, the
279
use of multidisciplinary pain treatments, like CBT pain management
programs (Blyth et al. 2005), would seem to be warranted in Brazil.
Furthermore, due
to
the
availability
of internationally used
measures provided by this series of studies, as well as the confirmation
of the international literature, this series of studies may contribute to
improve research in this area in Brazil and collaborative work with other
countries.
6.4. Further directions
It is important to replicate and expand these findings in other
chronic pain population in Brazil and worldwide. Although this study was
conducted in a large sample, it was not representative and probably
there are cultural, across-person and within-person differences that
should be explored.
Due to the fact that the present study was cross-sectional, it is
possible that the relationships between the examined variables may vary
over time. Therefore, further prospective studies should investigate and
determine process involved in the development of chronic pain and
factors affecting this population.
There is also room for improvement regarding theoretical and
measurement issues involving acceptance and catastrophising (i.e.
relevant dimensions of acceptance and catastrophising, validity and
reliability of the Chronic Pain Acceptance Questionnaire).
The use of the validated measures should be encouraged in
Brazilian clinical settings in treatment evaluation and in identifying
280
treatment
targets.
Further
research
could
also
investigate
the
effectiveness of multidimensional interventions for this population.
Considering that a number of cognitions and depression were
considered simultaneously when examining their contribution to disability
and emotional adjustment, and the fact that self-efficacy played an
important role in disability, the contribution of self-efficacy should be
investigated further.
281
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Appendix I
List of institutions participating in the study
300
301
Appendix II
The consent form
302
303
Appendix III
Ethic committee approvals
304
305
306
307
308
309
310
311
312
313
Appendix IV
Original measures and translations
314
315
316
317
318
319
320
321
322
323
324
325
326
327
Appendix V
Publications
328