CBT for Catastrophizing?

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Cognitive behavioral therapy for chronic pain is
effective, but for whom?
Article in Pain · May 2016
Impact Factor: 5.21 · DOI: 10.1097/j.pain.0000000000000626
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Joan E Broderick
University of Southern California
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Duke University Medical Center
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Alan T Kaell
Stony Brook University
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Cognitive behavioral therapy for chronic pain is effective, but for whom?
Joan E. Brodericka,b*
, Francis J. Keefec,d
, Stefan Schneidera,b
, Doerte U. Junghaenela,b
, Patricia
Bruckenthalf
, Joseph E. Schwartze
, Alan T. Kaellg
, David S. Caldwelld,
, Daphne McKeec
, Elaine Gouldh
a
Center for Self-Report Science
b
Center for Economic & Social Research
c
Department of Psychiatry and Behavioral Sciences
d
Department of Medicine
e
Department of Psychiatry and Behavioral Science
f
School of Nursing
g
Department of Medicine, Rheumatology Division
h
Department of Radiology
Stony Brook University
*Current contact information for corresponding author:
Joan E. Broderick, Ph.D.
Dornsife Center for Self-Report Science
Center for Economic & Social Research
Los Angeles, California 90089-3332
Email: Joan.Broderick@usc.edu
Grant support: NIH/NIAMS R01 AR054626
ClinicalTrials.gov identifier: NCT00636454
Total number of pages: 33
Total number of tables: 4
Keywords: treatment effectiveness, pain coping skills, osteoarthritis, chronic pain,
clinical nursing research

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Abstract
Moderator analyses are reported for post-treatment outcomes in a large,
randomized, controlled effectiveness trial for chronic pain for hip and knee osteoarthritis (OA)
(N=256). Pain Coping Skills Training, a form of cognitive behavioral therapy, was compared
to usual care. Treatment was delivered by nurse practitioners in patients’ community doctors’
offices. Consistent with meta-analyses of pain CBT efficacy, treatment effects in this trial
were significant for several primary and secondary outcomes, but tended to be small. This
study was designed to examine differential response to treatment for patient subgroups to
guide clinical decision making for treatment. Based on existing literature, demographic (age,
sex, race/ethnicity, education) and clinical variables (disease severity, BMI, patient treatment
expectations, depression, and patient pain coping style) were specified a priori as potential
moderators. Trial outcome variables (N=15) included pain, fatigue, self-efficacy, quality of life,
catastrophizing, and use of pain medication. Results yielded five significant moderators for
outcomes at post-treatment: pain coping style, patient expectation for treatment response,
radiographically-assessed disease severity, age, and education. Thus, sex, race/ethnicity,
BMI, and depression at baseline were not associated with level of treatment response. In
contrast, patients with interpersonal problems associated with pain coping did not benefit
much from the treatment. Although most patients projected positive expectations for the
treatment prior to randomization, only those with moderate to high expectations benefited.
Patients with moderate to high OA disease severity showed stronger treatment effects.
Finally, the oldest and most educated patients showed strong treatment effects, while
younger and less educated did not.

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Introduction
During the last 30 years, well over 100 treatment studies for managing pain have
been conducted using cognitive behavioral therapy (CBT) and disease self-management
interventions [73]. In general, meta-analyses report small to moderate beneficial effects for
pain, disability, mood, pain catastrophizing, and self-efficacy immediately after treatment
when compared to usual care [19; 73].
Despite the large number of CBT clinical trials, very few reports of predictors
(moderators) of the treatment effects have been published. This is unfortunate, since
investigation of moderators can identify patient subgroups that exhibit different treatment
responses. Turk argued that the field needs to advance beyond conceptualizing chronic pain
as homogeneous and applying the same interventions to everyone [66]. He cited many
papers that observed important psychological and biological heterogeneity among patients
with persistent pain. Jamison conducted some of the early work on psychosocial distinctions,
identifying three patient clusters generated by the Multidimensional Pain Inventory [28].
These data suggested the possibility of tailoring treatment to address the specific patient
features to yield improved outcomes. In contrast, others have argued that multimodal
therapies deliver generic benefits irrespective of patients’ individual psychosocial profiles [14;
24].
The importance of finding predictors of treatment response in patients with chronic
pain is widely recognized. Recently, the Nijmegen Decision Tool was published to guide
recommendations for surgical or non-surgical interventions for chronic back pain [69]. At pre-
treatment, high levels of disability, unemployment, and involvement with litigation or
compensation claims were found to bode poorly for surgical outcomes. In a 2009 review,
older age and longer duration of pain as well as somatization, depression, anxiety, and poor
coping were pre-treatment factors associated with poorer outcomes for back surgery and

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implanted spinal cord stimulation [13]. Regarding CBT treatment for chronic pain, Vlaeyen &
Morley suggest that the next generation of research should be determining “what works for
whom” [70]. Moreover, the personalized medicine movement argues for more tailored
patient-treatment matching [44].
Based on a survey of CBT chronic pain literature, we found few outcomes of
demographic variables moderating treatment response. Education, marital status, and pain
duration were not significant predictors [50]. Higher treatment expectations were associated
with more improvement [23; 40]. The literature on depression is mixed with some studies
finding that depression is associated with greater improvements [68], while others find
depression results in poorer outcomes [51; 67]. While some studies examining pain coping
profiles found that MPI “dysfunctional” patients benefited the most from treatment,
“interpersonally distressed” somewhat less, and “adaptive” patients showed little or no
improvement [59; 63-65]; other studies found no differential treatment response. Baseline
catastrophizing, a maladaptive form of coping, was found in one study to be associated with
a poorer outcome [67]. Finally, we found no studies examining disease severity as a
predictor of treatment response.
This paper reports on a priori-specified (grant application) moderator analyses of five
demographic and three clinical variables in one of the largest randomized controlled
effectiveness trials of CBT for chronic pain [10]. Outcomes reported are for the change from
baseline to post-treatment assessment.
Methods
Study Design
This study was a multi-site, randomized controlled trial examining the
effectiveness of Pain Coping Skills Training (PCST) delivered by trained nurse
practitioners (NP) in community primary care and rheumatology offices [10]. Patients

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with osteoarthritis (OA) were randomized in equal numbers to one of two conditions:
PCST (treatment condition) or Usual Care (control condition). Patients in the PCST
treatment condition received 10 sessions of individual PCST designed to teach and
promote the use of cognitive-behavioral pain management coping skills. Patients in the
control condition continued with their usual care for OA. Consistent with usual care,
patients in both conditions were provided with an OA informational brochure from the
Arthritis Foundation and information on programs (support groups, arthritis education,
and aquatic exercise classes) offered in the community.
Participants
Patients with chronic pain due to OA of the knee or hip were recruited from
community primary care and rheumatology practices in New York, Virginia, and North
Carolina. Advertisements with information about the study were posted in the waiting
rooms, and participating doctors informed eligible patients of the opportunity to
participate in the clinical trial at the time of a regular office visit. Patients were told that
the purpose of the study was to evaluate the effectiveness of a 10-session program for
coping with persistent pain delivered by nurses in their doctor’s office. Patients randomly
assigned to the control group would continue with their usual care and participate in the
periodic assessments. Interested patients were invited to contact the research office for
further details and to be screened by telephone for eligibility. Eligibility criteria were (1)
physician-confirmed diagnosis of hip or knee OA, (2) 21 years of age or older, (3) usual
pain ≥ 4 on a 10-point scale for a duration of at least 6 months, (4) ability to read, write,
and understand English, (5) ability to attend 10 treatment sessions at the doctor’s office
if randomized to treatment, (6) no cognitive/mental impairment that would interfere with
participation, (7) no expected joint replacement surgery in the next two years.
Measures
Moderator variables assessed

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Demographic characteristics. Demographic measures included age at the time of the
baseline interview, sex, race/ethnicity, body mass index, and level of highest education.
Baseline OA disease radiographic severity ratings. The widely-used Kellgren-
Lawrence system for osteoarthritis joint damage based on radiographs was used to
grade disease severity at baseline [37]. Patients were not informed of their grade.
Severity was graded from 0 (no radiographic findings of OA) to 4 (definite osteophytes
with severe joint space narrowing and subchondral sclerosis). Scoring based on
radiographs has been shown to correlate moderately with articular surface grading
during knee arthroscopy [39]. All X-rays were graded using K-L criteria by two
independent raters, and a third rating was obtained in cases where the ratings disagreed
by 2 grades or more (n = 24; 9% of the sample). Inter-rater reliability was acceptable
among the first two raters, with linear weighted kappa = 0.74 (95% CI = 0.68 to 0.79)
and Krippendorff's [26] ordinal alpha = 0.76 (95% CI = 0.71 to 0.80). Reliability was
slightly improved by the third rating (ordinal alpha = 0.78, 95% CI = 0.75 to 0.81).
Baseline treatment expectations. A 5-item questionnaire was modified for this study
based on the Credibility/Expectation Questionnaire [18]. Patients were asked to rate on
a 10-point scale whether PCST seems logical, if they feel confident about the training,
whether the training will help to control their pain, if they expect the nurse delivering the
training to be helpful, and if they would recommend this training to others. The overall
scale score for this measure showed good internal consistency (Cronbach α=0.87) [9].
Beck Depression Inventory-II (BDI). This 21-item self-report questionnaire measures
cognitive, affective, and somatic aspects of depressed mood [5; 6]. It is widely used as a
treatment outcome measure and is sensitive to the range of depressed mood in chronic
pain patients [20; 27; 74]. The BDI has demonstrated validity and sensitivity to treatment
change [4]. The internal consistency of the BDI total score was 0.89 in the present study.

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Multidimensional Pain Inventory (MPI). The MPI is a 61-item instrument that
evaluates the impact of and adaptation to chronic pain. Section one addresses patients’
pain severity, pain-related interference, appraisals of social support, life control, and
affective distress. Section two measures patients’ perceptions of significant others’
positive and negative behaviors in response to patient pain. Section three assesses
patients’ general activity level [38]. Internal consistencies for the subscales assessed at
baseline ranged from 0.71 to 0.92 in the present sample. There are two scoring systems.
The classical MPI scoring system uses 9 of the 13 subscales to classify patients into 3
main adaptational styles: adaptive, dysfunctional, and interpersonally distressed patients
[38]. In addition, a more recent scoring method based on Rasch modeling yields two
dimensional composite scores: an interpersonally distressed score and a dysfunctional
score [58].
Outcome Measures
Arthritis Impact Measurement Scales (AIMS2). This 78-item questionnaire measures
the health status of patients with arthritis and has been used extensively in survey and
treatment outcomes research [25; 52]. The AIMS2 addresses pain, mobility, walking and
bending, extremity functioning, self-care, household tasks, social activities and support,
work, tension, and mood. The recall period for this instrument was changed from “in the
past month” to a 2-week period. Internal consistency subscale estimates ranged from
0.72 to 0.90 in the present study.
Brief Pain Inventory (BPI). Four items from the BPI were used to measure current pain
and “average”, “worst”, and “least” pain in the past two weeks. The inventory is reliable,
valid and has achieved widespread use among medical conditions with chronic pain [15;
17]. The internal consistency of the four-item scale was 0.89 in the present study.
Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). The
WOMAC is the most widely used outcome measure in hip and knee arthritis

8

pharmaceutical and surgical studies. Several studies support the reliability and validity of
the WOMAC [7; 46]. The instrument has 24 items covering three domains: pain,
stiffness, and physical function experienced during the past 48 hours. Internal
consistency estimates ranged from 0.70 to 0.95 for the three subscales in the present
study.
Coping Strategies Questionnaire (CSQ). The 42–item Coping Attempts subscale of
the CSQ [35; 57] was used to assess how often a patient engages in seven different
coping strategies when they feel pain: coping self-statements, praying or hoping,
ignoring pain sensations, reinterpreting pain sensations, increasing behavioral activities,
catastrophizing, and diverting attention. This instrument has shown sensitivity to
treatment change in various chronic pain samples [21; 48] as well as good internal
consistency and construct validity [35]. Internal consistency estimates for the seven
subscales ranged from 0.77 to 0.86 in the present study. Since the catastrophizing
subscale has been shown to be a very important variable in pain research, it is
examined separately in our analyses.
Arthritis Self-Efficacy Scale. This 8-item instrument measures patients’ perceived
ability to perform specific behaviors aimed at controlling arthritis pain and disability
(ranging from 1=very uncertain to 10=very certain) [22]. The scale was adapted from the
20-item questionnaire developed by Lorig and colleagues [47] that has shown sensitivity
to increases in a sense of mastery over arthritis pain in many outcome trials [45; 61].
The 8-item version has shown adequate reliability and validity [22]. The internal
consistency of the total score was 0.92 in the present study.
Quality of Life Scale. This 16-item instrument measures quality of life across different
life domains in patients with chronic illness. The measure is reliable and content-valid;
among medical patients, internal consistency coefficients are above 0.85, and 6-week

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test-retest reliability is 0.76 [12]. The internal consistency of the total score was 0.91 in
the present study.
Brief Fatigue Inventory (BFI). Like the BPI after which it was modeled, the BFI was
designed to measure fatigue in cancer patients, but its use has expanded to many
medical conditions [3; 53]. Four items from the BFI were used to measure current fatigue
and “average”, “worst”, and “least” fatigue; the recall period was changed from the past
24 hours to the past two weeks. A factor analysis determined that the BFI assesses a
single fatigue dimension with good internal consistency and adequate correlations with
other fatigue scales [53; 75]. The internal consistency of the four items was 0.86 in the
present study.
End-of-day symptom diaries recorded on interactive voice recording (IVR). Several
key constructs that are central to the arthritis pain experience were measured via IVR (a
telephone computer interface) for seven consecutive days at each assessment period
(baseline, post-treatment, 6- and 12-month follow-up). These constructs included ratings
of pain intensity, interference with physical, work, and social activities due to pain,
fatigue, satisfaction with the day’s accomplishments, and pain medication usage. IVR
data capture is reliable and valid when compared to paper-and-pencil assessment, and
compliance is typically good [10; 11; 42; 54].
Creation of composite measures
Several key constructs were a priori specified as primary outcomes: pain
intensity, physical functioning, psychological distress, coping strategies, catastrophizing,
self-efficacy, and quality of life. Given the multiple scales administered for several
domains, and to reduce Type 1 error, composite measures were created for four of the
primary outcomes (pain, physical functioning, psychological distress, and coping). The
other outcomes were measured with single scales. The pain composite was comprised
of the BPI pain, AIMS2 pain, and WOMAC pain subscales (average inter-correlation

10

across scales at baseline = 0.70). Physical functioning was composed of the AIMS2
physical and WOMAC difficulties performing activities subscales (r = 0.58).
Psychological distress was comprised of the BDI and AIMS2 affect (tension and mood)
scales (r = 0.70). A coping strategies composite was created by averaging the CSQ
subscales (average r = 0.47), excluding the catastrophizing subscale, that is important in
its own right. In each case, scale scores were first standardized based on the baseline
means and standard deviations (SDs) across all patients, and then were averaged into
composites. Thus, the composite z-scores at each assessment time point indicate where
a patient scored in relation to all patients at pre-treatment.
Procedure
All study procedures were approved by the Stony Brook University and Duke
University Medical Center Institutional Review Boards. The study was registered at
ClinicalTrials.gov (NCT00636454). Eligible patients were scheduled for their baseline
visit at the patient’s participating community clinic site. Prior to initiating study
procedures, patients provided written informed consent. During the baseline visit,
patients completed a battery of outcome questionnaires, were instructed on how to use
the Interactive Voice Recording (IVR) telephone system for the seven daily ratings
following the baseline visit and had their weight and height measured. Patients were also
sent for an X-ray of their most painful OA-diagnosed joint at no cost to them to determine
their baseline disease severity. If a recent X-ray (within the past 9 months) was already
available, the research staff obtained a copy and no new x-ray was obtained. Patients
were informed that they needed to complete their daily ratings and provide an X-ray
within 4 weeks of the baseline assessment.
Upon completion of all baseline assessment components, patients were
randomized to one of the two study conditions. Randomization to experimental condition

11

(PCST or usual care) was done using a permuted block randomization algorithm with
block sizes of 6 and 8. The study statistician created a randomization program accessed
by site coordinators at the time of each patient’s randomization. The randomization
assignment was only provided after the patient’s unique identifier and initials were
entered into the randomization program. The study coordinator then called patients and
informed them of their assignment to study treatment group. Patients assigned to PCST
were then scheduled for their first appointment with a NP who provided 10 individual
weekly sessions at the patient’s doctor’s office (window for treatment completion 10 to
20 weeks from randomization). Patients assigned to usual care were instructed to
continue with their regular treatment for their OA. Both study groups were asked to
complete a post-treatment assessment, a six-month follow-up and a 12-month follow-up
assessment. As in the baseline assessment, research assistants met with patients for
each assessment when patients completed outcome measures, had height and weight
measures, and completed the seven daily IVR ratings. The research team maintained
assessor blinding, but patients sometimes revealed their experimental condition. Data
collection was conducted from 2008-2013.
Pain Coping Skills Training (PCST)
PCST interventions teach patients cognitive and behavioral skills to manage their
pain and enhance their perception of pain control. Four broad coping skills were taught
across the 10 30-45-minute sessions: relaxation response, attention diversion
techniques, altering activity and rest patterns as a way of increasing activity level, and
reducing negative pain-related thoughts and emotions. The sessions were outlined in
detail in a treatment manual and followed a format of review of home practice assigned
at the previous session, instruction in a new coping skill, guided practice in that skill, and

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a home practice assignment. Homework assignments are an integral component of
PCST followed by review and problem-solving in the subsequent session.
Consistent with the goal of testing the effectiveness of NPs delivering PCST in
the patients’ doctors’ offices, all treatment sessions were conducted in the clinics or by
telephone (phone sessions). Up to 4 sessions could be conducted via telephone with
some discretion on the part of the NP and patient. The first 3 sessions and the last
session had to be conducted in person. Patients were provided with a treatment binder
divided into sections for each session. These sections included handouts and logs to
record home practice of the skill, which were reviewed by the NP at each session.
Treatment sessions with a patient were stopped if they were not completed within 20
weeks of randomization.
Nurse practitioners (NPs) delivering the treatment
Treatment sessions were conducted by several NPs hired by the research grant.
Study nurses received 2-3 days of intensive training in PCST and individual supervision
of their cases for several months. Additional oversight for purposes of quality assurance
was provided for the duration of the study.
Analytic Strategy
Tests of moderated treatment effects were conducted using analysis of
covariance models for categorical moderator variables and using multiple regression
procedures as outlined by Aiken and West [2] for continuous moderator variables. In
each case, post-treatment scores on the outcome variable were regressed on the
baseline scores of that variable, group (treatment versus control), the moderator
variable, and the group by moderator interaction term. Clinic site was included as an
additional covariate. Thus, the interaction term tests whether the treatment effect, as the
group difference in change from pre-treatment, differs across levels of the moderator,

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controlling for potential site differences in outcomes. Significant interactions for
continuous moderators were probed by analyses of simple slopes. Specifically, these
analyses probed the group difference in change for high (1 SD above the mean),
average (at the mean) and low (1 SD below the mean) values of the moderator variable
[16]. To facilitate interpretation of the magnitude of the moderated treatment effects, we
report effect sizes (Cohen’s d) for high, average, and low values of the moderator,
computed as the group difference in change on the outcome relative to the standard
deviation at baseline (scaled such that positive effect sizes indicate improvement in the
treatment group relative to the control group). Unstandardized group mean changes and
moderated treatment effects in raw scale scores are provided in the supplemental
appendix. Because some patients were missing at post-treatment, analyses were
conducted using full information maximum likelihood estimation, which yields unbiased
parameter estimates and standard errors under the assumption that the data are either
Missing Completely at Random (MCAR) or Missing at Random (MAR) [60]. The
significance level was set at .05, consistent with the suggestion by Kraemer [41] that
these moderator analyses are primarily hypothesis-generating rather than hypothesis
testing activities.
Results
The treatment and control groups (N=256) were not significantly different on
demographic and health variables at baseline with the exception of employment status in
which the control group had a higher rate of employment than the treatment group (see
Table 1). Likewise, the groups did not differ on any of the outcome measures at
baseline; and comparisons of treatment effects across the two clinical sites did not yield
any differences. Overall, PCST produced significant improvements in a range of pain-
related variables including pain intensity, coping with pain, self-efficacy for controlling

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pain, activity interference due to pain, and reduced use of pain medication when
compared to usual care [10].
Demographics
Five demographic variables were examined for evidence of moderation of treatment
outcome. Sex, race/ethnicity, and body mass index were not significant moderators for
any of the outcomes.
Age (M = 67.2 years; range = 36-100) significantly moderated post-treatment pain
(p <.05) and daily ratings of “Quality of Days” (p = 0.004). Specifically, the youngest
patients (age = 57.7) experienced no reduction in pain from treatment, whereas the
treatment effect for the average-age (age = 67.2) was d = 0.19 and for the oldest
patients (age = 76.7) d = 0.37. More pronounced effect modification by age was
observed for Quality of Days: the youngest patients reported poorer Quality of Days after
treatment (d = -0.25), the average age patient reported a small improvement (d = 0.14),
and the oldest patients experienced a much larger improvement (d = 0.52) in the
treatment group compared to controls.
Level of education moderated post-treatment level of catastrophizing (p = 0.005)
even within a sample that tended to be more educated (up to high school: 28%; college:
51%; post-grad: 21%). A marked treatment effect for catastrophizing (d = 0.57) was
observed in the highly educated patients (post-graduate), whereas there was little
improvement for the college educated (d = 0.08) and a worsening in the high school
educated (d = -0.20).
Clinical Variables
Disease severity at baseline, as measured by Kellgren-Lawrence radiograph
ratings, moderated several outcomes: pain intensity composite (p = 0.02), fatigue

15

(p = 0.004), quality of life scale (p = 0.05), and daily quality of days (p = 0.03). Close to
25% of the sample was classified into each of the four K-L severity groups. With a good
deal of consistency, as shown in Table 2, patients with the most severe organic disease
had a robust response to treatment on measures of pain (d = 0.51), quality of life (d =
0.40) and fatigue (d = 0.75) . Those patients with little joint damage reported no
improvement on these variables and a worsening for quality of life and daily quality of
day measures.
Baseline ratings of treatment expectation significantly moderated five outcome
variables: pain intensity composite (p = 0.03), catastrophizing (p = 0.04), self-efficacy
(p = 0.05), fatigue (p = 0.03), and daily IVR pain ratings (p = 0.03). Patients with lower
expectations for the helpfulness of treatment had no improvement in pain,
catastrophizing, and fatigue, though they did show an improvement in self-efficacy
(d = 0.37) (see Table 3). The highest expectations were associated with the greatest
improvement on these outcomes, especially for IVR pain (d = 0.59), self-efficacy (d =
0.83), and fatigue (d = 0.60). Those with “average” (still strong) expectations
experienced more moderate improvements IVR pain (d = .37), self-efficacy (d = .60),
and fatigue (d = .36).
Our measure of depression at baseline, the BDI, did not moderate treatment
response on any outcome. This may be due to very low levels of depressive symptoms
in the sample: 74% minimal, 9% mild, 2% moderate, and 2% severe.
The Multidimensional Pain Inventory (MPI) is scored using the original method of
assigning patients to three pain coping styles based on classical test theory: adaptive,
interpersonally distressed, and dysfunctional [38], and a more recent method based on
Item Response Theory (IRT) that yields two Rasch Scale composite scores:

16

interpersonal distress and dysfunctional [58]. We examined moderation using both
methods. Using the original clusters, 46% of our patients were identified as Adaptive,
26% as Interpersonally Distressed, and 7% as Dysfunctional with identical distributions
in our treatment and control groups. The remaining 20% of patients could not be
classified into one of the three clusters, as is common with the MPI, and were not
included in this analysis. The proportion of patients classified as Interpersonally
Distressed was comparable to that observed in prior research with various
musculoskeletal disorders, including low back pain, fibromyalgia, and arthritis; in
contrast, the proportion of patients with an adaptive coping style was slightly higher, and
the proportion classified as having a dysfunctional coping style was lower than
previously observed [8; 31; 65]. All patients’ data could be analyzed for the Rasch
scoring. Our patients’ mean Dysfunctional score was, on average, lower (M = 42.1, SD =
10.33) than in the large chronic pain “normative” sample (M = 55.1, SD = 12.0) reported
in the MPI Version 3 Handbook [58]. In contrast, the patients in our sample had
somewhat higher Interpersonal Distress scores (M = 43.3, SD = 12.3) than the MPI
“normative” sample (M = 39.5, SD = 14.0).
The traditional MPI cluster groups yielded no significant moderator effects for the
primary composites and other outcome variables. The newer Rasch Scale Score for
Interpersonally Distressed, however, yielded several significant moderator effects for
treatment outcomes: the psychological distress composite (p = 0.01), self-efficacy (p =
0.05), catastrophizing (p = 0.02), and quality of life (p = 0.03). In addition, change in
aggregated daily measures of quality of day (p = 0.03), satisfaction with
accomplishments (p = 0.02), and need to take additional medication for pain (p = 0.03)
were moderated by the MPI Interpersonal Distress score. Specifically, the higher the
Interpersonally Distressed Coping score, the poorer the treatment response for these

17

outcomes (see Table 4 showing effect sizes for various scores). The MPI Rasch
Dysfunctional score did not moderate treatment response.
Discussion
This study examined moderators of treatment response in a large RCT of
osteoarthritis patients with chronic pain [10] who received either Pain Coping Skills
Training, a form of CBT, or usual care. Overall, RCT treatment effects were significant
for several of the primary and secondary outcomes; however, they tended to be small as
has been found in meta-analyses of CBT for pain [70; 73]. Thus, the question of
differential patient response to this treatment is important. Do some patients benefit
substantially more or less than the average? Is there evidence that this treatment can be
recommended with greater confidence to patients with particular demographic or clinical
presentations? Do we need to consider revisions to the treatment or alternative
treatments for patients with other characteristics?
As noted earlier, only a few published trials have examined moderators of treatment
effects for CBT for pain. Variables that have been examined include demographics,
treatment expectation, disease severity, depression, and style of coping with pain (MPI);
and we specified these variables a priori for moderation analyses. In our study, five
variables emerged as moderators of several outcomes.
The MPI coping style variable was the strongest moderator. Prior literature
examining moderation by MPI clusters usually found that the Interpersonally Distressed
patients benefited less from treatment than Dysfunctional patients. Often, Adaptive
patients showed little treatment response due to positive baseline coping. In this trial, we
found no differences in treatment response among the three MPI clusters. In the revised
MPI scoring, the new Rasch approach assigns each patient a score for the two
maladaptive coping style. Dysfunctional scores did not moderate outcomes indicating

18

that degree of Dysfunctional coping did not influence treatment response. However, our
patients with mid to higher Interpersonally Distressed styles of coping with pain benefited
significantly less from the treatment on the following outcomes: psychological distress
composite, quality of life, self-efficacy, catastrophizing, and daily ratings of satisfaction
with accomplishments, quality of day, and need for pain medication. In fact, with one
exception, only patients with relatively low Interpersonally Distressed ratings showed
benefit on these outcome variables. The exception was self-efficacy in which all patients
showed improvement, but the effects were much stronger for those with less
Interpersonal Distress. On a positive note, patients’ treatment responses for pain and
physical functioning did not vary by level of Interpersonal Distress coping style.
These data are consistent with prior research that usually found that patients,
classified as Interpersonally Distressed in their pain coping, benefit the least from pain
treatment [59; 63-65]. This refines and underscores the importance of Interpersonal
Distress in pain coping. Patients with a strong Interpersonally Distressed pain coping
style report a greater number of negative behaviors by their significant others in
response to their pain compared to other patients. In addition, these patients report less
social support from their significant others. As such, their experiences of chronic pain are
intertwined with problematic interpersonal relations within their immediate social
network. Specific management of interpersonal difficulties associated with pain is not
usually a focus of CBT protocols for pain, including the one implemented in the present
study. As noted by Turk, addressing social relationships (e.g., guidance for interpersonal
problem solving and assertion training) might be particularly beneficial for patients with
an Interpersonally Distressed pain coping style [65; 66]. Importantly, some research,
including our own, has demonstrated the utility of including spouses and family members
in chronic pain treatment [32-34; 49]. The emerging consistency of the association of the

19

Interpersonally Distressed coping style with poorer outcomes suggests these patients
need additional or other treatment approaches to yield more positive outcomes.
Second, patients’ baseline expectation of the benefit of the PCST (assessed prior to
randomization) moderated several important outcomes: pain, fatigue, self-efficacy, and
catastrophizing. This was evident even in the context of overall positive treatment
expectations in the recruited sample. Patients with relatively lower (scores of 6.4 on 10-
point scale) experienced very little benefit from treatment, while patients with average to
high expectations experienced moderate to large effects. This finding is also observed in
two prior studies [23; 40]. Perhaps, some patients are not inclined toward self-
management approaches to deal with their pain; that is, they recognize that the
treatment is not a good fit for them, although, they did agree to participate and accept a
50% probability of being randomly assigned to the treatment group. Or, they may require
preliminary work using motivational interviewing to enhance their “readiness for change”
to more fully reap the benefits of treatment [29; 43].
Third, radiograph measures of disease severity predicted treatment response. The
30% of patients with the most severe joint disease (Kellgren-Lawrence ratings of greater
than 3) experienced moderate to large treatment benefits for pain, fatigue, quality of life,
and daily quality of day. In contrast, the 22% of patients with the lowest levels of
objective disease (KL ratings of 0-1) showed no benefit or worsening. Mid-level disease
severity patients (49%; KL ratings of 2-3) experienced some treatment effects, especially
for fatigue and quality of day. This result is likely of interest to rheumatologists and
primary care clinicians who are frequently involved in the management of pain in OA
patients with severe disease [36]. It is very encouraging that patients with the most
severe disease benefit from this intervention to better manage their disease. We believe
that this is the first report of the relationship of disease severity with PCST pain
outcomes.

20

The outcomes for demographic variables were encouraging in that for both men and
women, patients of different race and ethnicity, as well as BMI, all benefited equivalently
from the treatment. This speaks to the generalizability of treatment efficacy across a
range of patient groups. However, age and education did moderate outcomes on three
variables. The oldest patients showed the most robust treatment effect for pain and daily
quality of day, whereas the younger patients did not. Our most highly educated patients
showed improvement on catastrophizing, whereas high school and college educated
patients did not; though our PCST treatment protocol did not specifically target
catastrophizing. It is possible that PCST protocols that do target catastrophizing may
yield a more universal effect. Overall, the results for moderation by demographic
variables are positive news. Across 5 demographic moderator variables by 15 outcome
variables, only 3 of 75 possible moderator relationships were detected which is within
the realm of statistical chance. Thus, our data are generally consistent with the
conclusions of a 2002 review that age, sex, and education did not moderate treatment
effects [51]. Nevertheless, the results that show older patients experience the best
improvements in pain suggest that this treatment can be provided to even the very old
with good results.
The differences in treatment effect sizes observed across the continuums of the
moderator variables are important. While the overall trial’s effect sizes are modest, for
subgroups the effects rise substantially and warrant consideration in clinical decision-
making [44]. Results from two of the moderators, pain coping style and treatment
expectations, suggest incorporation of additional psychological approaches into the
treatment. A higher score on the MPI Interpersonally Distressed dimension likely
requires examination of the social environment of the patient and the role of the patient’s
pain in those relationships. This style of coping with pain may reflect a more
generalizable pattern of problematic social interactions. Indeed, treatment effectiveness

21

may benefit from some involvement of the patient’s significant other(s) [32-34]. As such,
these patients might benefit from PCST delivered by health professionals who can be
trained to augment PCST with interventions focused on the social context of pain [56].
Similarly, lower treatment expectations may warrant inclusion of other interventions,
such as motivational interviewing, in order to orient patients to the value of self-
management approaches for managing their condition [29; 30]. However, the factors
underlying expectations are not well elucidated. Therefore, when patients present with
low to moderate treatment expectations, this should be explored to identify treatment
preferences and barriers.
The data from this study also suggest that age and educational level impact
treatment outcomes for reasons that are not apparent. Older and very educated patients
benefited more from the treatment. As Internet-based interventions for pain management
are developed, it will be interesting to see how demographics moderate those treatment
effects compared with in-person interventions. The next generation of PCST treatment
should consider approaches that may be more relevant for younger, and perhaps busier,
patients as well as those that are less educated.
Finally, this study has several important health economic implications. First, there is
growing concern about the long-term costs and benefits of biological treatments for OA
[71; 72]. There is also growing agreement about the need to identify patients who will
and will not respond to biologic therapy in order to efficiently manage medical resources
[62; 71]. Likewise, the ability to identify patients who might respond best to behavioral
approaches may be particularly useful to clinicians working with patients who fail to
respond adequately to biologic approaches. And, finally, our results are the first to
document the high levels of PCST effectiveness among patients with the most severe
disease as assessed by imaging. Treatment options for these older patients often are
very limited, i.e., medications contraindicated, or the patient is not a surgical candidate

22

because of co-morbid conditions [1; 55]. Thus, patients who must delay joint
replacement or who are unable to receive replacement are particularly good candidates
for this treatment.

23

Acknowledgments
Research reported in this publication was supported by the National Institute of
Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health
under Award Number AR054626 and General Clinical Research Center Grant
#M01RR10710. The content is solely the responsibility of the authors and does not
necessarily represent the official views of the National Institutes of Health.
Conflict of Interest statement
We declare that there are no conflicts of interest.

24

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29

Table 1.
Demographic and medical characteristics by experimental group.
Control group
(N = 128)
Treatment group
(N = 129)
P for diff.
between
groups
n a
M (SD) or % n a
M (SD) or %
Age 128 66.37 (10.26) 129 68.00 (8.67) .17
Years with OA 121 13.59 (9.09) 128 13.95 (10.63) .77
BMI 123 32.87 (8.00) 124 33.77 (8.24) .38
Disease severity (K-L grading) 122 125 .22
0 - 1 27.0% 16.8%
>1 - 2 20.5% 27.2%
>2 - 3 23.0% 26.4%
>3 - 4 29.5% 29.6%
Female 128 78.9% 129 74.4% .40
White race 128 85.9% 129 87.6% .69
Married/living with partner 123 62.6% 126 64.3% .78
Education 126 127 .18
High school graduate 27.0% 28.4%
College graduate 56.4% 46.5%
Master's degree 16.7% 25.2%
Currently employed 121 39.7% 128 21.1% .001
Currently on disability 125 15.2% 128 13.3% .66
Current smoker 126 5.6% 127 7.1% .62
Past smoker 123 52.9% 127 54.3% .81
Regular exercise 121 49.6% 124 45.2% .49
Treatment for psychiatric
disorder
126 15.1% 128 16.4% .77
Treatment for drugs 125 1.6% 128 0.0% .15
Memory/thinking problems 125 9.6% 126 10.3% .85

30

Table 2.
Standardized intervention effect sizes by disease severity groups
Kellgren-Lawrence disease severity ratings
0-1
(n=54)
>1-2
(n=59)
>2-3
(n=61)
>3-4
(n=73)
Pain intensity composite -.06 .22 .06 .51
Quality of life -.20 .08 .07 .40
Fatigue -.03 .13 .43 .75
IVR quality of days -.34 .29 .41 .20
Note: Intervention effects are standardized based on the pooled baseline standard
deviation. Positive values indicate treatment benefits. IVR = Interactive voice recording
(end-of-day diary reports).

31

Table 3.
Standardized intervention effect sizes by baseline treatment expectations
Baseline treatment expectation scores
Low
(-1 SD, X=6.4)
Average
(X=7.9)
High
(+1 SD, X=9.3)
Pain intensity composite .00 .20 .40
Catastrophizing -.07 .13 .33
Self-efficacy .37 .60 .83
Fatigue .11 .36 .60
IVR pain .15 .37 .59
deviation. Positive values indicate treatment benefits. IVR = Interactive voice recording
(end-of-day diary reports).

32

Table 4.
Standardized intervention effect sizes by baseline interpersonal distress levels
MPI interpersonal distress Rasch scores
Low
(-1 SD, X=31.0)
Average
(X=43.3)
High
(+1 SD, X=55.6)
Psychological distress composite .35 .15 -.04
Catastrophizing .39 .16 -.06
Self-efficacy .86 .63 .40
Quality of life .33 .12 -.10
IVR quality of days .43 .17 -.09
IVR satisfaction with accomplishments .38 .14 -.11
IVR medication taking .29 .15 .00
deviation. Positive values indicate treatment benefits. MPI = Multidimensional Pain
Inventory. IVR = Interactive voice recording (end-of-day diary reports).

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