Reducing Disparities with Literacy-adapted Psychosocial ...the PI evaluated 2 group-administered...
Transcript of Reducing Disparities with Literacy-adapted Psychosocial ...the PI evaluated 2 group-administered...
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Reducing Disparities with Literacy-adapted Psychosocial Treatments for Chronic Pain:
A Comparative Trial
Beverly E. Thorn, PhD1, Deborah Tucker, MBA2, Toya Burton, DC, MPH.2, Lisa Campbell, PhD3,
John Burns, PhD4, 1University of Alabama, Tuscaloosa, AL 2Whatley Health Services, Inc., Tuscaloosa, AL 3 East Carolina University, Greenville, NC 4 Rush University Medical Center, Chicago, Il Original Project Title: Reducing Disparities with Literacy-adapted Psychosocial Treatments for Chronic Pain: A Comparative Trial PCORI ID: 941 HSRProj ID: 20142266 ClinicalTrials.gov ID: NCT01967342
_______________________________ To cite this document, please use: Thorn B, Tucker D, Burton T, et al. 2019. Treating Chronic Pain Using Approaches Adapted for Patients with Limited Reading Skills. Washington, DC: Patient-Centered Outcomes Research Institute (PCORI). https://doi.org/10.25302/5.2019.CER.941
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Table of Contents
Abstract ....................................................................................................................................................................................... 3
Background ................................................................................................................................................................................ 5
Participation of Patients and Other Stakeholders...................................................................................................... 8
Methods ..................................................................................................................................................................................... 10
Study Design ................................................................................................................................................................ ....... 10
Study Cohort/Study Setting ......................................................................................................................................... 11
Study Outcomes ................................................................................................................................................................ . 17
Data Collection/Sources/Follow-up ......................................................................................................................... 18
Analytic and Statistical Approaches .......................................................................................................................... 19
Conduct of the Study/Protocol.................................................................................................................................... 21
Results ........................................................................................................................................................................................ 21
Primary Outcome (Pain Intensity) ............................................................................................................................ 32
Secondary Outcomes (Pain Interference, Depression) ..................................................................................... 35
Heterogeneity of Treatment Effects—Exploratory Analyses ......................................................................... 39
Adverse Events .................................................................................................................................................................. 41
Discussion ................................................................................................................................................................................. 41
Study Results in Context/Addressing Methodological Gaps .......................................................................... 41
Decisional Context ............................................................................................................................................................ 43
Implementation of Study Results ............................................................................................................................... 45
Generalizability/Subpopulation Considerations ................................................................................................. 47
Study Limitations .............................................................................................................................................................. 49
Future Research ................................................................................................................................................................ 50
Conclusions .............................................................................................................................................................................. 51
References ................................................................................................................................................................ ................ 53
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Abstract
Background: Chronic pain is a major public health problem in the United States, most recently
underscored by the spiraling opioid epidemic, and unequally borne by low-SES, ethnic
minorities. Treatment, when available, is biomedical, expensive, and fraught with undesirable
side effects. Psychosocial treatments show promise as adjuncts or alternatives but are usually
unavailable to low-SES individuals and have not been adapted to their education or literacy
levels.
Objectives: In individuals with chronic pain receiving care at low-income clinics in Alabama,
assess the effectiveness of 10 weekly 90-minute literacy-adapted group sessions of cognitive-
behavioral therapy (CBT) or pain education (EDU) compared with a usual medical care control
(UC). The primary end point is immediately after the 10-week treatment and the secondary end
point is at 6 months follow-up. The primary outcome is pain intensity, and secondary outcomes
are pain interference, depression, and clinical meaningfulness of results.
Methods: Parallel-group randomized, controlled, interviewer-blind, comparative effectiveness
trial of 2 evidence-based group-administered chronic pain interventions (CBT, EDU) compared
with usual care (received by all participants). The primary outcome was pain intensity (Brief
Pain Inventory – Intensity scale, 10-point numeric scale); secondary outcomes were pain
interference with daily activities (Brief Pain Inventory [BPI]-Interference scale, 10-point numeric
scale) and depression (Patient Health Questionnaire – 9 items [PHQ-9], 27-point scale). Primary
analyses used piecewise linear mixed models with an intent-to-treat approach to produce non-
standardized change estimates at our primary end point (10-week posttreatment) and at 6
months follow-up across treatment allocation arms. Secondary analyses examined the
percentage of participants with clinically meaningful improvements (> 30% improvement on
outcomes). Additionally, change estimates for pain intensity (BPI-Intensity) and pain
interference (BPI-Interference) were compared against minimally important change criteria
established by IMMPACT criteria for each allocation arm. Furthermore, we compared numbers
and percentages of the sample (by allocation arm) with PHQ-9 scores above the “probable
depression” cutoff (≥ 10) at baseline, posttreatment, and 6 months follow-up.
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Results: Participants were 290 patients (71% women; 67% African American; 72% below
poverty threshold; 68% high school, GED, or no degree), with a mean age of 50.6 years, pain
duration of 16.5 years, and reading grade level of 7.5.
Participants in CBT and EDU had larger decreases in pain intensity scores (primary outcome)
between baseline and posttreatment (after completion of 10-session treatment period) than
those in UC (estimated differences in change scores: CBT –.80, 95% CI, –1.48 to –0.11, P < .05;
EDU –.57, 95% CI, –1.04 to –0.10, P < .05). At 6 months follow-up, treatment gains were not
maintained for CBT but were for EDU. For pain interference (secondary outcome), participants
in CBT and EDU had greater improvements than those in UC at posttreatment, and these
improvements were maintained at 6 months follow-up. Neither CBT nor EDU changes in
depression (secondary outcome) were different from UC.
Conclusions: Psychosocial interventions adapted to reduce cognitive demands are effective
treatments for multiply disadvantaged patients with chronic pain. Although, based on
comparison of effect sizes and clinically meaningful differences, CBT may have conferred a
slight advantage over EDU when compared with usual care, EDU may present an attractive
alternative to usual medical treatment alone in CHCs, which may not have the resources to
implement CBT.
Limitations and subpopulation considerations: The majority of participants were multiply
disadvantaged, with low income and relatively low primary and health literacy and were mostly
minority and female; participants often lived in rural settings. Thus, findings may not generalize
to other populations. Participant coordinators from the community maintained close contact
with patients, and close community partnerships with the CHC were crucial to recruitment and
retention. Thus, recruitment and retention rates may not be as favorable in health centers with
less-intensive community partner participation. Assessment questionnaires were read aloud to
participants, which limits the feasibility of use of non-literacy-adapted questionnaires in clinical
settings. Methods for dissemination and implementation of this treatment into other clinical
settings and durability of treatment effects will require further research.
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Background
Chronic pain (CP) is a widespread and growing problem in the United States, with 20%
of physician visits and 10% of drug sales attributed to pain.1,2 The Institute of Medicine (IOM)
estimates that more than 116 million Americans (37.3%) experience CP, costing $600 billion
annually, and that CP disproportionately affects vulnerable populations, especially economically
disadvantaged individuals, ethnic minorities, women, and older adults.2 Psychological disorders,
such as depression, are commonly comorbid with CP3 and worsen pain outcomes.4-6 Standard
CP treatment focuses on biomedical techniques, such as medication and surgery, which are
expensive, invasive, high in adverse effects, and limited in long-term effectiveness, as the
spiraling opioid epidemic attests.7-10 Even with biomedical treatment, many patients with CP
continue to experience disabling pain. Recently published national clinical practice guidelines
stress nonpharmacological evidence-based alternatives to pain medications,11-13 yet many
providers are not familiar with treatments such as cognitive-behavioral therapy (CBT), and
access to CBT is limited, particularly in low-income communities.
Financially disadvantaged individuals face societal-, system-, and provider-level
disparities that can exacerbate the negative effects of CP and reduce the effectiveness of
interventions.14 These patients usually lack access to comprehensive health care resources,
including appropriate facilities, personnel, and treatments.2,15-17 Low-SES (socioeconomic status
individuals experience higher rates of CP and a higher likelihood of pain-related disability, as
well as higher rates of major chronic physical and psychological comorbidities such as
depression and anxiety,11,18 all while obtaining less support and care for their conditions.
According to the IOM, patients are not adequately educated about their pain, and
research refining such educational approaches is necessary.2 Further, the IOM calls for
continued research on psychosocial interventions, particularly to reduce disparities in pain and
comorbid psychological dysfunction. Both cognitive-behavioral therapy and pain education
(EDU) show promising effectiveness in reducing the negative outcomes associated with CP.
Several researchers, including the principal investigator (PI; Thorn),19 have demonstrated that
pain education programs, if based on a biopsychosocial model, can result in improved pain
outcomes.20-23 However, biopsychosocial pain education as an intervention is in the early stages
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of development as a viable therapeutic option. In contrast, the effectiveness of CBT for
reducing pain, suffering, and disability in people with CP has extensive empirical support.24-31
CBT helps patients with CP learn new thought and behavior patterns linked with positive
outcomes and replace thoughts and behaviors associated with negative outcomes. To do this,
CBT prominently features behavioral skills training and practice.32-34
Notably, data supporting the efficacy of psychosocial interventions for chronic pain are
based primarily on middle-class patients with high health literacy; very few attempts have been
made to evaluate these treatments in disadvantaged populations. Many researchers and
practitioners have questioned the feasibility of an approach such as CBT for low-SES people
facing challenges of limited resources, logistics, and low literacy skills. CBT requires a certain
amount of abstract thinking and problem solving; utilizes written workbooks, handouts, and
worksheets; and assigns homework, thus requiring more patient effort than taking analgesic
medication or receiving biomedical interventions. Even group pain education utilizes written
workbooks and requires patient time and effort during classes.
Low health literacy presents a significant and widespread difficulty for many
disadvantaged populations. Recognizing the extent of this problem for health care,35,36
researchers are now generating materials that are more acceptable and influential in
underserved populations—and perhaps more appropriate for most of the population.19, 37-39
However, due to the complexity of their core components, psychosocial interventions present
unique challenges to health literacy adaptation efforts. Among those with low health literacy, a
substantial portion also demonstrates lower cognitive ability, compounding the difficulty of
successful adaptation.40,41 Thus, there is a need to adapt psychosocial treatments to reduce
both literacy level of patient materials and the cognitive demands associated with the
treatments.
Although deficits in literacy can limit patients’ ability to understand and benefit from
psychosocial treatments, other reasons reinforce the potential benefit of simplifying treatments
for everyone with chronic illnesses. Pain demands attention, leaving fewer cognitive resources
available to devote to understanding, remembering, and adhering to medical and psychological
regiments. Cognitive abilities are also diminished by the numerous medications often
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prescribed to patients with pain and other chronic illnesses. Further, the stress of any chronic
illness reduces one’s cognitive reserve, as does the aging process. Thus, it is argued that anyone
dealing with a chronic medical illness, including pain, would benefit from simpler psychosocial
treatment approaches.
In previous research19,38,42,43 the PI evaluated 2 group-administered psychosocial
treatments (CBT and EDU) for chronic pain in a low-SES population; these treatments had been
adapted to decrease the literacy demands of patient materials and reduce the cognitive
demands of the interventions. For example, the reading level of patient written materials were
lowered from 10th grade (in original format) to fifth grade, font size was increased, more white
space was incorporated into the workbook, and key illustrations were used to help emphasize
certain points. Further, during treatment groups, jargon and multisyllabic words were avoided;
interactive teaching methods were used, including working through examples using a flip chart,
incorporating the group members’ own words; and cotherapists provided one-on-one
assistance when group members seemed to be struggling with a concept. EDU was structurally
equivalent to the CBT intervention regarding treatment modality (group administered,
interactive teaching with group discussion), therapist attention, and treatment duration (10
weekly 90-minute sessions)44,45 but did not contain active skills-building components that were
specific to CBT. Study results revealed moderate treatment effects on pain intensity and pain
interference in daily functioning for both interventions, with no significant differences between
them on the pain outcome variables at posttest; most effects maintained at 6 months. EDU
produced greater-than-anticipated improvements in the primary outcome variables (pain
intensity, pain interference) for this low-SES population and was better tolerated than CBT,
producing fewer dropouts. CBT showed significant pre–post reductions in depressive symptoms
that were maintained at follow-up and not observed with EDU. Together, these findings
suggested that both health literacy–adapted CBT and EDU interventions for the reduction of
pain may be efficacious in this population; however, this trial was underpowered to reliably
detect differences between treatment allocation arms and lacked a usual care (UC) comparison
group, which precluded the evaluation of whether the therapies could augment existing
medical practices.
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The research questions of the current study were the following: (1) In individuals with
chronic pain and low socioeconomic standing who are receiving care at a federally qualified
health center in the southern United States, does participating in a health literacy–adapted
psychosocial treatment group improve their self-reported pain intensity and interference in
physical functioning by the end of treatment when compared with a group receiving usual
medical care, and are these effects maintained 6 months later? (2) In these same individuals,
does participation in the CBT pain management group improve depressive symptoms better
than a pain education group by the end of treatment, and are these effects maintained 6
months later?
Previous studies have not focused on a multiply disadvantaged population, have not
tested simplified psychosocial treatments, have not included a usual care control group, and/or
have not included a large enough sample to be able to detect potentially small treatment
differences. This study moves the field forward by testing the effectiveness of literacy-adapted
and simplified psychosocial treatments (CBT, EDU) with a concurrent usual medical care control
group (UC) in order to determine whether CBT and/or EDU provide treatment benefits over and
above usual medical care in a large sample (290) of patients attending clinics for low-income
individuals in Alabama.
Participation of Patients and Other Stakeholders
The main stakeholders involved in the project were patients, including those in focus
groups prior to proposal, demonstration groups, participants in the research trial, and Research
Advisory Board members; medical staff at a community health clinic consortium administered
by Whatley Health Services (WHS), including medical providers, clinical staff, Research Advisory
Board members, and a clinical investigator–provider; trained patient coordinators living in the
community; and administrators at WHS, including the chief executive officer (CEO; clinical
investigator and Research Advisory Board member), the chief medical officer (Research
Advisory Board member), and 1 member of the WHS board of directors (Research Advisory
Board member).
As the newest component of an ongoing research program into treatment of low-SES
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individuals with chronic pain, the current project benefited from a solid background of
stakeholder involvement in research. The PI (Thorn) involved staff and patients from rural
Alabama community health centers in the planning and execution of her previous community-
based research, and patient focus groups served a key advisory role in the multiple stages of
adaptation of patient materials. In these focus groups, patient stakeholders reviewed all
materials for acceptability; readability; usability (i.e., easy to understand); and layout, design,
and graphics. One suggestion made early in the process was to replace clip art with actual
artwork and photographs, which was done. Patient stakeholders also reviewed the assessment
materials and planned format, and they suggested that the materials would need to be read
aloud to participants to help them be accessible to all participants. They also suggested a break
in the 90-minute assessment session. Both suggestions were adopted. WHS was identified as a
potential site for the current project via conversations with a university colleague who
personally knew the CEO and arranged a meeting of introduction. The PI subsequently
conducted 2 10-week demonstration treatment groups for interested patients and WHS staff.
Thereafter, several key stakeholders were recruited to join the PI in project planning,
representing administrators, clinical staff, patients (past treatment completers), and
researchers. As an example of how the engagement of patient and other stakeholder partners
changed a specific aspect of the research, the researchers had intended to have a 12-month
follow-up period, after which patient participants in the medical treatment as usual condition
would be invited to attend a gratis 10-week treatment group. Our community partners felt
strongly that a 12-month waiting period was too long, and we therefore modified the design of
the study to have a 6-month follow-up period, after which usual care participants were invited
to participate in a treatment group at their participating site. We held future planning and
troubleshooting meetings with the CEO of WHS as necessary, with weekly face-to-face
meetings with our clinical investigator and our patient coordinators. As the project progressed,
additional community stakeholders were recruited to participate on the Research Advisory
Board, which met every 6 months. Key points for Research Advisory Board involvement
included study preparation and finalization, study implementation, interpretation of study
results, and (ongoing) dissemination. Other prominent engagement points included
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recruitment and retention of patient participants, which was accomplished by the patient
coordinators and our clinical investigator as well as by referrals from clinical staff at
participating WHS sites. Informal and formal patient feedback avenues included post-
participation qualitative interviews (at the end of treatment and at 6 months follow-up) and
community dissemination and feedback at a closing reception (in September 2016) to which all
patient participants and Whatley staff were invited. During the project, patient stakeholders
consented to be interviewed and were featured in both a PCORI article on its website and a
very high-profile article in the New York Times. Our community partners have participated in
multiple presentations at local and national meetings, including 3 PCORI presentations, 1
presentation at the American Psychological Association, and 2 presentations at the Alabama
Primary Healthcare Association. The WHS CEO, patient coordinators, and our clinical
investigator are contributing authors on our main outcomes paper (submitted to a refereed
journal, invited for revision, and revisions currently under review). Furthermore, 1 of our
patient stakeholders attended the 2017 PCORI Annual Meeting with the PI (Thorn) and
participated in a presentation regarding the process and outcomes of the study.
The biggest perceived impact of engagement involved recruitment and retention of
patient participants. Medical staff referring the greatest number of patients were also clearly
patient champions and very well regarded by their patients, who trusted them to have their
best interests in mind. Not only did patient coordinators serve as telephone recruiters and
eligibility screeners, but also, perhaps more importantly, they fielded telephone calls from
participants, served to encourage and reinforce their participation, and often made face-to-face
“check-ins” with patient participants when they attended a non-study medical appointment.
We believe these extra efforts meaningfully influenced our ability to recruit and retain a large
sample of multiply disadvantaged patient participants.
Methods
Study Design
The study design was a parallel-group, randomized, controlled, comparative-
effectiveness trial that assessed patients on measures of interest at pre-intervention, mid-
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intervention, immediately post-intervention, and 6 months post-intervention in 3 allocation
arms: medical usual care, biopsychosocial pain education intervention, and cognitive-behavioral
therapy pain management. We chose the study design with guidance by the “Decision Tree for
Comparative Effectiveness of Therapeutics” table published as part of the Translational
Framework in the PCORI draft methodology. Given that the current study employed baseline
randomization and did not vary exposure to treatments within participants but does vary
exposure between participants, we selected a parallel-group randomized controlled trial as the
best method of determining the answers to our research questions.
Study Cohort/Study Setting
We recruited participants within a network of federally qualified health clinics
administered by Whatley Health Services, a private, 501(c) 3 nonprofit corporation. Patients
attending these clinics are typically economically disadvantaged. Several other disparities are
often comorbid with low incomes, including, but not limited to, low educational attainment and
low health literacy, and patients are often racial minorities, women, and older adults. Because
the purpose of the research was to test the acceptability and efficacy of patient materials and
therapeutic approaches meant to reduce the cognitive demands of treatment, we chose the
target population because it was multiply disadvantaged. The flow of all 290 participants
through the study is reported in Figure 1.
Two WHS employees served as paid participant coordinators to recruit adult patients
with at least 1 diagnosis consistent with chronic pain in their electronic medical records. The
patient coordinators, as WHS employees, examined the medical records. Potential participants
were phoned by patient coordinators, informed of the study by a clinical staff member during a
clinic visit, or responded to flyers posted in the waiting areas or examination rooms. Interested
patients were screened and enrolled by telephone or in person. Enrolled individuals were at
least 19 years of age, reported having had pain most days of the month for at least 3 months,
had the
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Figure 1. CONSORT Diagram
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ability to speak and understand English and had a telephone or other means of contact.
Excluded individuals were those with pain related to malignancies (e.g., cancer), significant
cognitive impairment, current uncontrolled substance abuse or serious psychological
disturbance, less than minimal literacy skills (at least first-grade reading level, as determined at
baseline testing), major changes in current pain or psychotropic medication in the past 4 weeks,
or current psychosocial treatment of any pain condition. We assessed eligibility based on the
inclusion and exclusion criteria using data from screening interviews.
Interventions and Comparator/Control Interventions
The target health condition was chronic pain, regardless of type, pain site, or cause
(with the exception of malignancies). In other words, the participant sample was not predefined
based on type or cause of pain (e.g., low back pain, headache pain), but could have 1 (or more)
of a variety of pain-related diagnoses. The study interventions were either cognitive-behavioral
therapy or pain education. These interventions were administered in 10 consecutive weekly 90-
minute sessions using a closed-group format and are the products of adaptation and
refinement processes begun in previous research.19,38 For example, the reading level of patient
written materials were lowered from 10th grade (in original format) to fifth grade, font size was
increased, more white space was incorporated into the workbook, and key illustrations were
used to help emphasize certain points. Further, during treatment groups, jargon and
multisyllabic words were avoided; interactive teaching methods were used, including working
through examples using a flip chart, incorporating the group members’ own words; and co-
therapists provided one-on-one assistance when group members seemed to be struggling with
a concept. Further, audio summaries of each session were given out at the end of each session,
rather than relying on the written workbook summary, and for the CBT treatment arm, we
removed the requirement that patients do written homework on worksheets and turn them in.
Table 1 presents an outline of session content for each of the CBT and EDU sessions. The
patient workbooks and therapist supplements are copyrighted but freely available at
pmt.ua.edu/publications.html.
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Table 1. Session Content of Cognitive-Behavioral Therapy and Pain Education Cognitive-Behavioral Therapy Pain Education
Session 1 Let’s Get Started: Pain Is Stressful (purpose of group; how pain and stress are related; relaxation training)
Welcome (purpose of group; chronic pain as a common problem; stress and pain connection; 4 parts of stress response)
Session 2 Manage Your Brain to Manage Your Pain (how pain works in the brain; how to reduce pain signals; relaxation)
Pain Is in the Brain (how pain works in the brain; what decreases or increases pain signals in the brain)
Session 3 Getting Active (fear of pain and activity connection; training in pacing activity; scheduling pleasant activities; relaxation)
Short-term and Chronic Pain (differences between short-term and chronic pain and their treatments; pros and cons of physical activity)
Session 4 Pain and Emotions (link between pain and emotions; emotional expression training; relaxation)
Pain and Your Emotions (link between pain and emotions; chronic pain and feeling sad, mad, or scared)
Session 5 Stand Tall Talk (3 ways of communicating; assertiveness training; relaxation)
Ways of Talking to People (3 ways of communicating)
Session 6 Thoughts That Work Against You (link between thoughts, feelings, and actions; training in recognizing unhelpful thoughts; relaxation)
Talking With Health Care Workers (importance of relationships with health care workers and maintaining good relationships with them)
Session 7 Making Your Thoughts Work for You (recognizing “red flag” words; training in changing unhelpful thoughts; relaxation)
Types and Costs of Chronic Pain (different types of chronic pain and their treatment; multiple costs of having chronic pain)
Session 8 Master Your Thoughts to Manage Your Pain (recognizing deeper beliefs; training in changing deeper beliefs, “Acting as If” exercise; coping self-statements; relaxation)
Pain Behaviors (understanding pain behaviors, what affects them, and what they might communicate; pain and behavior cycle)
Session 9 Get Better Sleep (sleep and pain connection; training in changing unhelpful sleep habits; relaxation)
Sleep (common sleep problems, normal sleep, and the sleep cycle)
Session 10 Your Pain Coping Toolbox (review of information and skills used; planning for continued pain self-management; coping with pain flare-ups)
Knowing Your Pain (review of information learned; discussion of how you will use what you’ve learned going forward)
CBT: “Learning About Managing Pain” Group. The CBT intervention is based on the PI’s
published and empirically validated group CBT treatment for chronic pain.46 It provides literacy-
adapted cognitive-behavioral techniques (“skill-building”) based on a biopsychosocial model
that includes motivational reinforcement, education about chronic pain, and pain management
skills training (e.g., cognitive restructuring, activity pacing, relaxation).
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EDU: “Learning About My Pain” Group. The development of the EDU intervention was
informed by existing pain education interventions designed for non-disadvantaged populations
and the PI’s CBT manual.46,47 Its format was matched to standard group CBT treatment for pain
on group modality, discussion, and therapist engagement. Our adaptations of EDU included a
biopsychosocial focus on enhancing motivation for pain self-management that emphasized
therapeutic alliance and group cohesion and gave participants relevant information to discuss
and use but without explicit skills training such as those employed in CBT (e.g., cognitive
restructuring, activity pacing, relaxation). Thus, both CBT and EDU provide information
promoting pain self-management.
All sessions were video-recorded and a study investigator uninvolved in treatment
evaluated therapists’ adherence to the protocol and quality for 26% of the sessions, randomly
selected, using a structured scale. Table 2 provides a summary of the treatment integrity
process for the trial as well as relevant findings.
Table 2. Summary of Treatment Integrity Process for the LAMP Protocol
Treatment Fidelity
Treatment condition Quality Rating
Adherence Rating
Protocol Deviation
Mean (SD) SE Mean (SD) SE Occurrences (%) Cognitive behavioral therapy
2.75 (.36) .07
100.00 (.00)
.00
0
Pain education
2.53 (.33)
0.6 97.00 (5.57)
1.02
3 (10)
Of the sessions, 63 (30%) were randomly selected for review; however, 7 sessions were not
rated due to technical difficulties (e.g., audio unavailable due to technical issues at remote site).
In total, 56 (26.7%) sessions (26 CBT and 30 EDU) were successfully reviewed and scored for
adherence, therapist competence, and quality of treatment. Any protocol deviations were also
noted for each session reviewed.
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We used the Therapy Adherence and Competence Scale, an adapted version of the
Cognitive Adherence and Competence Scale,10 to measure adherence, therapist competence,
and quality of treatment. Three sessions were randomly selected from each group cohort and
rated on quality based on common therapeutic factors (e.g., co-interventionist alliance) and
coverage of unique elements specific to each session and treatment condition (e.g., assertive
communication skills training, unique to Session 5 in CBT). Each session received a quality rating
based on a 4-point scale with end points ranging from 0 (poor) to 3 (excellent). Scores indicate
that average ratings of both conditions were in the good to excellent range. Adherence ratings
were provided based on demonstrated delivery of unique elements and treatment components
for each session. Adherence rating scores in EDU indicate that there were several instances in
which interventionists did not demonstrate coverage of a specific element for that session.
Specifically, there were 5 EDU sessions in which coverage of a specific element was not
demonstrated, the most common missing element being “did not encourage participants to
review materials during the coming week.”
From the sessions reviewed, three incidents of protocol deviations occurred in EDU.
These protocol deviations included one instance of a therapist discussing a unique element
from CBT in an EDU session (e.g., behavioral pacing); one instance of a therapist providing the
wrong audio CD at the end of one EDU session, which included a relaxation exercise; and one
instance of three participants in the same EDU cohort receiving a faulty EDU manual that
included a section of CBT material. In the latter two cases, the incorrect audio CDs and the
workbooks were replaced at the beginning of the next session. Of note, each protocol deviation
occurred at a different session and for different group cohorts.
All participants received usual medical care, which could include specialty care such as
chiropractic or physical therapy, through WHS or external providers. Those randomized to only
UC received parallel study contact with participant coordinators as well as assessments and
intermittent phone contact to facilitate participant retention, but no group treatment (CBT or
EDU) as part of the study. We chose UC as a control group after carefully considering several
alternative controls. The most important outcome of this research for researchers, patients,
and clinicians was to demonstrate that the treatment allocation arms produce additive benefits
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over the standard medical care that patients are already receiving. UC served as a passive-
control condition, allowing us to estimate treatment effectiveness over usual medical care.48,49
Thus, the choice of the comparators provided valuable information about what additive
benefits are provided by these adapted pain education (EDU) and pain management (CBT)
classes over UC and what additive benefits (if any) the CBT treatment has over EDU.
Study Outcomes
The primary and secondary outcome measures, presented below, were the key
measures of interest and were selected based on guidelines provided by the Initiative on
Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT)24,50,51, and the PI’s
previous research in a similar population.19,38,42 All primary and secondary outcome measures
were administered at each assessment time point: prior to treatment (at baseline), after 5
weeks (midpoint), 10 weeks (postintervention, preidentified primary end point), and 6 months
following the 10-week intervention period (postintervention follow-up). Midpoint (5 weeks)
assessments were collected for future examination of treatment mechanisms and were not
used in the analyses reported here.
Sociodemographic and pain information was obtained at baseline in addition to primary
literacy (Wide Range Achievement Test-4: Word Reading subtest52). Cognitive variables
assessed were of exploratory interest to the investigators given the nature of the population,
but they were not a focus of the study. Other measures recording changes in quality of life,
affective mood states, and cognitive distress also provided valuable information for patients,
providers, and researchers, but they were not the main focus of this study. All measures except
the reading fluency measure were verbally administered to participants to reduce literacy
demands.51
Primary outcome was identified a priori to be pain intensity or severity and assessed by
the 4-item Brief Pain Inventory-Short Form (BPI-SF) Subscale for Pain Intensity (BPI-Intensity),
which uses a 10-point numeric rating scale with anchors “no pain” at 0 and “pain as bad as you
can imagine” at 10. The BPI has been validated in those with low literacy and has demonstrated
reliability, validity, and sensitivity to change.54
Secondary outcomes (identified a priori) included the following: pain interference in
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daily activities was measured by the BPI-SF Subscale for Pain Interference (BPI-Interference;
range 0-10), which contains 7 items (general activity, mood, walking ability, normal work,
relations with other people, sleep, and enjoyment of life) on a 10-point scale (0 = does not
interfere to 10 = completely interferes).54 Depressive symptoms were assessed using the
Patient Health Questionnaire-9 (PHQ-9), containing each of the 9 diagnostic criteria from the
DSM-IV.55 Numerous studies have confirmed the reliability and validity of the PHQ-9 in many
different populations, including those with low literacy, and it is brief enough to use in clinical
settings.
Data Collection/Sources/Follow-up
Following initial screenings, participants were contacted by patient coordinators to
schedule a baseline assessment. Following baseline assessment, treatment conditions were
randomly assigned and stratified by site (with intentional weighting toward the highest volume
service site); participants were randomized within these strata in cohorts of 7 to 9. An
allocation table based on a random number sequence was generated using statistical software
stratifying assignment by site (n = 4) and balanced by condition (n = 3). The allocation table was
held by the statistical consultant, who unblinded allocation to the PI only after all
preassessments for each cohort were completed. Follow-up contacts with each participant
were scheduled via telephone contacts from the patient coordinator. Outcome measures were
obtained by interviews and questionnaires prior to treatment, after 5 weeks (midpoint), after
10 weeks (postintervention), and 6 months following the 10-week treatment period
(postintervention follow-up). Participants were reimbursed $45 for each assessment, $20 to
defray the cost of transportation and $25 for time and effort expended. Those in the treatment
allocation arms also received $20 per session to defray travel expenses resulting from
participation in treatment groups, with no additional compensation for attending group
sessions.
Participants assigned to intervention groups participated in 10 weekly sessions (1.5
hours each) of group therapy with brief weekly assessments by group leaders to assess pain
intensity and pain interference (via Brief Pain Inventory), as well as to determine patients’
19
understanding of the material presented (via post-session process checks) and self-reported
likelihood of returning for the next session (via an intent-to-attend measure). Although some
degree of participant dropout was unavoidable, we took steps to reduce the negative impact of
participant discontinuation on the study. Participants who dropped out of treatment groups
were contacted to verify their desire to discontinue treatment, and information was collected
to understand (1) their reason for discontinuation, (2) who decided that the participant would
discontinue, and (3) whether discontinuation involved some or all types of participation.
Participants who dropped out of treatment groups were asked to complete all major
assessments as planned unless they expressed a wish to discontinue all participation. To avoid
attrition due to changes in contact information, participants were asked for 3 alternative
methods of contacting them if contact could not otherwise be made.
Analytic and Statistical Approaches
Using piecewise linear mixed models,56 we examined changes from pretreatment to
posttreatment, from posttreatment to 6 months follow-up, and for differences between study
arms. In piecewise linear mixed models, the different periods are hypothesized to have
different growth patterns for individuals in the sample. In the current study, change coefficients
for 2 different periods (i.e., pretreatment to posttreatment, posttreatment to 6 months follow-
up) have been estimated and tested for differences across 3 treatment groups (i.e., CBT, EDU,
and TAU) in the primary outcome (BPI-Intensity) and secondary outcomes (BPI-Interference and
PHQ-9).56 We conducted 3-level analyses (repeated measures at level 1 nested within
participants at level 2, and participants nested within group cohorts of the 7 to 9 individuals
randomized together at level 3). To compute effect sizes for the piecewise linear growth
models, we calculated Hedge’s δT for each effect estimate (δ𝑇𝑇 = γ00
��σ𝐵𝐵2 + σ𝑊𝑊
2 �), which is the
quotient of the estimate of the fixed effect divided by the square root of the total error
variance (which is the sum of the within- and between-person random-effects estimates). We
interpreted effect sizes using Cohen57 (small [0.2], medium [0.5], and large [0.8]). This means,
for example, that if 2 treatment arms’ means do not differ by 0.2 standard deviations or more,
the difference is not clinically meaningful even if it is statistically significant. The baseline
20
unconditional model for these comparisons was the intercept-only model.58,59 For secondary
outcomes, we employed a Benjamini-Hochberg corrected α to prevent false-positive
interpretation of differences due to multiple comparisons60 (i.e., the smaller P value within the
family of related tests was compared to a stricter α of .05/2 = .025, and the largest P value was
compared to α = .050).
Additional analyses utilized logistic regression models to examine the effect of
treatments on the binary outcome of clinically meaningful improvements (CMIs), defined as ≥
30% improvement on each continuous variable24; categorical variables were established as 0 for
improvement of < 30% and 1 for improvement of ≥30%. We used odds ratios (ORs) and
confidence intervals (CIs) to report the likelihood of CMIs for the treatment conditions
compared with usual care condition. We also compared the change estimates for pain intensity
(BPI-Intensity) and pain interference (BPI-Interference) to minimally important change criteria
established by IMMPACT criteria for each allocation arm.24 Finally, we compared the numbers
and percentages of the sample (by allocation arm) with PHQ-9 scores above the “probable
depression” cutoff (≥ 10) at baseline, posttreatment, and 6 months follow-up.
Analyses included all randomly assigned participants and used all data available for each
participant. We used the full information maximum likelihood estimation method to account
for possible nonresponse bias. Linear mixed models and logistic models were adjusted for sex,
minority status, years of education, and pain duration. Inferential tests were 2-tailed. We used
Mplus version 7.438 for analyzing linear mixed models, computing odds ratios, and calculating
confidence intervals.61 We conducted sensitivity analyses for the primary and secondary
outcomes using a pattern mixture model approach to assess possible departures from the
missing-at-random assumption for the linear mixed models.
Exploratory Heterogeneity of Treatment Effects (HTE) Analyses. Consistent with PCORI
Methodology Standards, we conducted exploratory analyses to attempt to describe potential
HTE due to subgroups within the sample and potential moderators of treatment effects.
Although the current study was not sufficiently powered for confirming these potential sources
of HTE, it was considered sufficient to allow tentative descriptive patterns to be presented. We
did not prespecify the possible distinguishing variables. The method for assessing HTE was the
21
exploratory interaction effects described by Kraemer et al.62,63 We included HTE variables of
interest in regression analyses using PROCESS64 for the primary outcome variable (pain
intensity), with preintervention scores included as covariates. We conducted regressions in 3
series of group comparisons (UC–EDU, UC–CBT, and EDU–CBT) to identify HTE for each
treatment and then potential differences between treatments due to HTE variables. For each
HTE variable, the interaction analysis P value and measure of effect size is reported.
Conduct of the Study/Protocol
The previously published65 Learning About My Pain trial protocol is attached to this
report. The trial protocol was approved by the University of Alabama Institutional Review Board
(IRB). All participants provided written informed consent for trial participation. The IRB did not
require any protocol modifications and was appropriately notified of personnel changes and
safety alerts or adverse events. Minor modifications throughout the project period (eg,
personnel changes, addition of study sites) were approved by the IRB via its protocol
modification procedure.
Results The flow of all 290 participants through the study is reported in Figure 1. Among 824
patients contacted or expressing interest, 485 patients were screened for eligibility and 290
were enrolled and randomized. The main reasons for exclusion were inability to attend
treatment sessions or related reasons for declining (96), unable to contact after initial screening
(82), and did not meet entry criteria (17).
There were 167 (87%) participants randomized to receive CBT or EDU who attended at
least 1 session, and 68 (71.6%) in the CBT group and 55 (56.7%) in the EDU group who attended
at least 8 sessions. The average number of sessions attended for the CBT condition was 7.5/10
(SD = 3.2) and for the EDU condition was 6.2/10 (SD = 4.0). Of those who attended at least 1
treatment session (treatment initiators), average attendance rates were 8/10 sessions. Overall
study completion rate (defined as participation in the posttreatment assessment, which was
our primary end point) was 83% (87% in CBT, 82% in EDU, and 80% in UC). Further, follow-up
assessment completion rates were 72% (74% in CBT, 70% in EDU, and 72% in UC). Overall, 241
22
(83.1%) participants completed at least 3 assessments, and 185 (63.6%) participants completed
all 4 assessments. Of the 192 participants in group treatment, 74.7% in CBT and 61.9% in EDU
received an adequate treatment dosage (operationally defined > 6 sessions, or attendance of at
least 70% of the sessions). We chose this definition based on a similar descriptive delimiter
cited in Cherkin et al.66 Because of this discrepancy, sensitivity analysis of primary and
secondary outcomes was undertaken (see Statistical Analysis section) and showed that
modeling dropout was not significantly related to outcomes at any time point, nor did dropout
affect any inference of the original growth model parameters, indicating that the missing-at-
random (MAR) assumption was not unreasonable with the data. Hence, we report the
parameter estimates of the MAR models in this report. Table 3 provides a comparison of the
original model results and the results using the sensitivity analyses.
23
Table 3. Comparison of Estimated Effects from Original Analyses to Results of Sensitivity Analyses Using Pattern Mixture Analysis.
Original Analyses Sensitivity Analyses
Baseline to Posttreatment Difference Versus Usual Care (95% CI)
P Value
Posttreatment to 6-month Difference Versus Usual Care
(95% CI) P
Value
Baseline to Posttreatment Difference Versus Usual Care (95% CI)
P Value
Posttreatment to 6-month Difference Versus Usual Care
(95% CI) P
Value
Pain Intensity Score (BPI-Intensity)
CBT –0.80 (–1.48 to –0.11) .022 0.60 (.06-1.13) .028
–0.80 (–1.49 to –0.12) .021 0.60 (0.06-1.13) .028
EDU –0.57(–1.04 to –0.10) .018 0.38 (–0.11-.87) .124
–0.57 (–1.04 to –0.10) .017 0.38 (–0.10-0.87) .121
Physical Function (BPI-Interference)
CBT –1.36 (–2.11 to –0.61) <
.001 0.36 (–0.27-0.99) .261
–1.38 (–2.12 to –0.63) <
.001 0.36 (–0.27-0.99) .262
EDU –0.70 (–1.31 to –0.09) .024 0.07 (–0.55-0.68) .831
–0.72 (–1.32 to –0.11) .021 0.07 (–0.55-0.68) .829
Depression (PHQ-9)
CBT –1.33 (–3.02-0.35) .120 0.85 (–0.69-2.38) .280
–1.31 (–2.99-0.38) .128 0.85 (–0.67-2.38) .279
EDU –1.15 (–2.71-0.41) .147 0.67 (–0.18-1.53) .123 –1.14 (–2.85-0.57) .191 0.68 (–0.75-2.10) .352
24
a. Participants declined further participation in the study. b. Participants expressed interest in continuing with the study but were not able to make further scheduled
assessments or groups (e.g., no ride). c. Participant was administratively removed from study for psychiatric reasons. d. Fifteen participants dropped out of the study between baseline assessment and posttreatment assessment. e. Patient coordinators were not able to reach 66 participants to schedule their follow-up assessments or to
reschedule a missed appointment; the 15 dropoutsd also contributed to the total missing data at follow-up.
Table 4 shows missing data by assessment point, as well as dropouts and reason for
dropout. As can be seen, only 14 of 290 participants dropped out of the study (i.e., notified us
that they were no longer participating at any level), either because they were no longer
Table 4. Description of Missing Data at Posttreatment Assessment (10 Weeks) and Follow-up Assessment (6 Months) per Group Condition Reasons for Missing Data Group Posttreatment
(10 Weeks) Follow-up (6 Months)
Dropped out—not interesteda CBT 1 0 EDU 2 0
TAU 3 0 Dropped out—interested but unable to scheduleb
CBT 0 0 EDU 4 0 TAU 4 0
Removed by researchersc
CBT 0 0 EDU 0 0 TAU 1 0
Cumulative Total of Dropouts
15d 0
Did not drop out, but unable to contact CBT
EDU TAU
2 2 3
14 15 9
Did not drop out, but unable to schedule CBT EDU TAU
9 9 9
10 8
10
Total Missing Data by Condition CBT 12 25 EDU 17 29 TAU 20 27
Total Missing Data by Time Point 49 81e
25
interested (n = 6) or because they were unable to continue attending (n = 8). One additional
participant was administratively removed. Most other missing data points occurred because the
participant was no longer reachable at his or her contact number or the patient coordinators
were not able to finalize an assessment appointment with the participant or to reschedule a
missed appointment.
Tables 5 and 6 show baseline differences in participants who completed versus did not
complete the posttreatment assessment. As can be seen, there were no significant differences
in dropout at posttreatment, based on treatment condition (CBT, EDU, UC). Further, there was
no significant difference at baseline for people who did versus did not complete posttreatment
assessment on pain intensity or depression. However, there was a significant baseline
difference on pain interference (p = .014), with people who completed the posttreatment
assessment scoring significantly lower on baseline pain interference (ie, less interference with
activities due to pain; M = 6.49; SD = 2.04) than those who did not complete the posttreatment
assessment (M = 7.27; SD = 1.85). The magnitude of the mean difference (0.78) is small, which
suggests that it is not a clinically meaningful difference; however, if this finding were to be
replicated, it may indicate that individuals who experience greater interference in daily
activities due to pain are less likely to attend assessment sessions, which may not be thought to
be as personally useful as group treatment sessions.
Table 5. Description of Baseline Continuous Variables Among Completers and Noncompleters of the 10-week Posttreatment Assessment
Baseline Postassessment M (SD) T Value P Value
Age Not completed 49.92 (9.54) –.59 .56 Completed 50.73 (8.73)
Pain duration (years) Not completed 17.88 (11.49) .83 .41 Completed 16.29 (12.38)
BPI—Intensity Not completed 6.74 (1.50) 1.03 .31 Completed 6.48 (1.66)
BPI—Interference Not completed 7.27 (1.85) 2.47 .01 Completed 6.49 (2.04)
PHQ-9 Not completed 12.45 (6.15) .39 .70 Completed 12.05 (6.48)
26
Table 6. Description of Baseline Categorical Variables Among Completers and Noncompleters of the 10-week Posttreatment Assessment Post-assessment Pearson χ2 P Value Gender
Male Female Total .83
.36 Not completed 17 32 49
Completed 68 173 241
Minority Status Nonminority Minority Total
3.78
.052 Not completed 20 29 49 Completed 65 176 241
Group Allocation TAU CBT EDU Total
2.12
.35 Not completed 20 12 17 49 Completed 78 83 80 241
Table 7 provides mean (SD) baseline characteristics for demographics and pain-related
variables. Participants were 290 patients with a mean age of 50.6 (SD = 8.9). Participants were
mostly female (n = 205; 71%), African American (n = 194; 67%), and with income below the
poverty threshold (n = 209; 72%). The mean reading grade level was 7.5 (SD = 3.6), and 192
participants (68%) had a high school degree, a GED, or no diploma. At baseline, treatment
groups were similar in sociodemographic and pain characteristics except that there were
significantly more African Americans in CBT (chi-square p = .002), and on pain type, the CBT
condition had significantly lower numbers of those with nerve pain (chi-square p = .007). Effects
size analyses using Cramer’s V (.179 for race differences in CBT condition; .161 for nerve pain
differences in CBT condition) indicated a small effect, and therefore we concluded there were
no clinically meaningful imbalances among allocation arms. Mean duration of pain was 16.5
years (range 5 months to 67 years). The mean BPI-Intensity score (6.52; SD = 1.63) indicated
moderate levels of intensity, and the mean BPI-Interference score (6.6; SD = 2.0) indicated
27
moderate levels of interference in daily activities due to pain. Of participants, 179 (61.7%) had
at least moderate levels of depressive symptoms (PHQ-9 scores ≥ 10).
Table 7. Baseline Characteristics of Study Participants by Treatment Group No. (%)
All (n = 290) UC (n = 98) CBT (n = 95) EDU (n = 97) Sociodemographic Characteristics Age, mean (SD) 50.6 (8.9) 49.7 (8.7) 52.2 (8.5) 49.9 (9.2) Women 205 (70.7) 69 (70.4) 67 (70.5) 69 (71.1) Education
No degree 85 (29.3) 27 (27.6) 29 (30.5) 29 (29.9) High school graduate/GED 112 (38.6) 36 (36.7) 36 (37.9) 40 (41.2) Some college or vocational school 49 (16.9) 19 (19.4) 17 (17.9) 13 (13.4) College graduatea 44 (15.2) 16 (16.3) 13 (13.7) 15 (15.5)
Raceb White/Caucasianb 96 (33.1) 38 (38.8) 20 (21.1)* 38 (39.2) Black/African Americanc 194 (66.9) 60 (61.2) 75 (78.9)* 59 (60.8)
Marital status Single 71 (24.5) 27 (27.6) 24 (25.3) 20 (20.6) Married or in a relationship for > 2
years 100 (34.5) 36 (36.7) 27 (28.4) 37 (38.1)
Divorced, separated, widowed 119 (41.0) 35 (35.7) 44 (46.3) 40 (41.2) Poverty statusd
Below poverty status 210 (72.4) 74 (75.5) 65 (68.4) 71 (73.2) Above poverty status 70 (24.1) 20 (20.4) 25 (26.3) 25 (25.8)
Employede 39 (13.4) 15 (15.3) 9 (9.5) 15 (15.5) Insurance status
Private health insurance 23 (7.9) 4 (4.1) 11 (11.6) 8 (8.2) Medicaid 68 (23.4) 28 (28.6) 21 (22.1) 19 (19.6) Medicare 42 (14.5) 14 (14.3) 13 (13.7) 15 (15.5) Combinationf 33 (11.4) 7 (7.1) 15 (15.8) 11 (11.3) No insurance 124 (42.8) 45 (45.9) 35 (36.8) 44 (45.4)
Disability status On disability 137 (47.2) 44 (44.9) 49 (51.6) 44 (45.4) Seeking disability 103 (35.5) 38 (38.8) 30 (31.6) 35 (36.1) Not on/not seeking 50 (17.2) 16 (16.3) 16 (16.8) 18 (18.6)
WRAT GLE, mean (SD) 7.4 (3.6) 8.2 (3.5) 6.7 (3.7) 7.3 (3.6) Chronic Pain History Pain duration (years), mean (SD) 16.6 (12.2) 18.1 (13.1) 15.0 (10.6) 16.7 (12.8) Primary pain site
Lower back 144 (49.7) 55 (56.1) 44 (46.3) 45 (46.4) Knee 37 (12.8) 11 (11.2) 19 (20.0) 7 (7.2) Neck 23 (7.9) 5 (5.1) 5 (5.3) 13 (13.4) Otherg 86 (29.7) 27 (27.6) 27 (28.4) 32 (33.0)
Number of reported pain sites, mean (SD) 6.2 (3.1) 6.1 (3.1) 6.3 (3.2) 6.4 (3.1) Type of pain
28
Musculoskeletalh 258 (89.0) 87 (88.8) 82 (86.3) 89 (91.8) Arthritisi 220 (75.9) 67 (68.4) 80 (84.2) 73 (75.3) Headachej 135 (46.6) 53 (54.1) 39 (41.1) 43 (44.3) Pelvic pain 96 (33.1) 36 (36.7) 33 (34.7) 27 (27.8) Nerve paink 92 (31.7) 37 (37.8) 20 (21.1)* 35 (36.1) IBSl or abdominal pain 58 (20.0) 24 (24.5) 12 (12.6) 22 (22.7) Chronic fatigue 41 (14.1) 13 (13.3) 15 (15.8) 13 (13.4) Fibromyalgia 34 (11.7) 7 (7.1) 15 (15.8) 12 (12.4)
Number of reported pain types, mean (SD)
4.7 (2.7) 4.8 (2.9) 4.6 (2.6) 4.7 (2.7)
Baseline Measures of Primary Outcomes
BPI-Intensity, mean (SD) 6.5 (1.6) 6.5 (1.6) 6.5 (1.8) 6.5 (1.5) Baseline Measures of Secondary Outcome
BPI-Interference, mean (SD) 6.6 (2.0) 6.6 (2.1) 6.7 (2.1) 6.6 (1.9) PHQ-9, mean (SD) 12.1 (6.4) 12.8 (6.4) 11.7 (6.1) 11.9 (6.8)
a Education subcategory “College graduate” indicates 2-year/technical graduate [n = 33] and 4-year/college graduate [n = 11]. b Race subcategory “White/Caucasian” indicates white [n = 84] and white/Caucasian and Native American [n = 12]. c Race subcategory “Black/African American” indicates black/African American [n = 191] and black/African American and Native American [n = 3]. d Poverty status category is missing data from 10 participants; TAU [n = 4], CBT [n = 5], and EDU [n = 1]. e Employed indicates full-time employment, part-time employment, and homemaker. f Insurance status subcategory of “Combination” indicates private Health Insurance (HI) and Medicaid [n = 1]; private HI and Medicare [n = 5]; Medicaid and Medicare [n = 25]; and private HI, Medicaid, and Medicare [n = 2]. g Primary pain site subcategory “Other” indicates shoulders [n = 13], upper leg [n = 12], pelvis [n = 11], hands [n = 11], feet [n = 9], head [n = 9], lower leg/ankle [n = 6], upper back [n = 6], unspecified [n = 6], arms [n = 2], and abdomen [n = 1]. h Type of pain subcategory “Musculoskeletal” indicates low back pain [n = 246], neck pain [n = 158], soft tissue or muscle pain [n = 145], and spinal cord injury pain [n = 24]. i Type of pain subcategory “Arthritis” indicates osteoarthritis [n = 141], rheumatoid arthritis [n = 56], and mixed arthritis [n = 48]. j Type of pain subcategory “Headache” indicates to tension headache [n = 81], migraine pain [n = 77], mixed headache [n = 26], and cluster headache [n = 12]. k Type of pain subcategory “Nerve pain” indicates neuropathic [n = 86] and chronic regional pain syndrome [n = 10]. l Type of pain subcategory “IBS” refers to irritable bowel syndrome. * Indicates a significant (p < 0.01) difference between observed and expected proportions (χ2test followed by post hoc standardized residual analysis). Effects size analyses using Cramer’s V (.179 for race differences in CBT condition, .161 for nerve pain differences in CBT condition) indicated a small effect, and therefore we concluded there were no clinically meaningful imbalances among conditions.
29
Table 8. Three-level Piecewise Linear Growth Model Estimates of Change and Between-condition Differences on Continuous Primary and Secondary Outcome Variables
Pain Intensity (BPI-Intensity) Pain Interference (BPI-Interference) Depression (PHQ-9)
Estimate (95% CI) p
Hedges’s δT (95% CI)
Estimate (95% CI) p
Hedges’s δT
(95% CI) Estimate (95%
CI) p Hedges’s δT
(95% CI)
Within-condition Change Estimates (Slopes) TREATMENT EFFECT: Pretreatment to posttreatment
UC –0.26 (–0.61-
0.08) .139 –0.13 (–0.30-
0.04) –0.30 (–0.77-
0.17) .208 –0.12 (–0.31-
0.07) –1.10 (–2.10 to –
0.09) .032 –0.17 (–0.33 to
–0.02)
CBT –1.06 (–1.65 to
–0.47) < .001* –0.53 (–0.82
to –0.24) –1.66 (–2.24 to –
1.07) < .001* –0.66 (–0.89 to
–0.43) –2.43 (–3.68 to –
1.19) < .001* –0.38 (–0.58 to
–0.19)
EDU –0.83 (–1.14 to
–0.41) < .001* –0.41 (–0.57
to –0.21) –1.00 (–1.39 to –
0.62) < .001* –0.40 (–0.55 to
–0.25) –2.24 (–3.51 to –
0.98) .001* –0.35 (–0.55 to
–0.15) MAINTENANCE: Posttreatment to 6 months follow-up
UC –0.24 (–0.60-
0.11) .173 –0.12 (–0.30-
0.05) 0.18 (–0.25-0.62) .407 0.07 (–0.10-
0.25) –0.24 (–0.83-0.35) .428 –0.04 (–0.13-
0.06)
CBT 0.35 (–0.05-
0.76) .085 0.18 (–0.02-
0.38) 0.54 (0.09 -1.00) .020* 0.22 (0.04-
0.40) 0.61 (–0.49-1.70) .279 0.10 (–0.08-
0.27)
EDU 0.14 (–0.20-
0.59) .422 0.07 (–0.10-
0.29) 0.25 (–0.19-0.69) .261 0.10 (–0.07-
0.27) 0.43 (–0.43-1.29) .326 0.07 (–0.07-
0.20)
Between-condition Differences in Change Estimates (Adjusted Slopes)
Pretreatment to posttreatment CBT versus
UC –0.80 (–1.48 to
–0.11) .022* –0.40 (–0.74
to –0.06) –1.36 (–2.11 to –
0.61) < .001* –0.54 (–0.84 to
–0.24) –1.33 (–3.02-0.35) .120 –0.21 (–0.48-
0.06) EDU versus
UC –0.57 (–1.04 to
–0.10) .018* –0.28 (–0.52
to –0.05) –0.70 (–1.31 to –
0.09) .024* –0.28 (–0.52 to
–0.04) –1.15 (–2.71-0.41) .147 –0.18 (–0.43-
0.06) CBT versus
EDU –0.23 (–0.90-
0.64) .497 –0.12 (–0.45-
0.32) –0.66 (–1.36-
0.05) .067 –0.26 (–0.54-
0.02) –0.20 (–1.98-1.59) .829 –0.03 (–0.31-
0.25) Posttreatment to 6 months follow-up
CBT versus UC
0.60 (0.06-1.13) .028*
0.30 (0.03-0.57) 0.36 (–0.27-0.99) .261
0.14 (–0.11-0.39) 0.85 (–0.69-2.38) .028*
0.13 (–0.11-0.37)
EDU versus UC
0.38 (–0.11-0.87) .124
0.19 (–0.05-0.44) 0.07 (–0.55-0.68) .831
0.03 (–0.22-0.27) 0.67 (–0.18-1.53) .007*
0.11 (–0.03-0.24)
30
CBT versus EDU
0.21 (–0.31-0.90) .421
0.11 (–0.15-0.45) 0.29 (–0.34-0.93) .367
0.12 (–0.14-0.37) 0.18 (–1.25-1.60) .805
0.03 (–0.20-0.25)
Note. Negative values (i.e., lower or decreased scores) indicate improvement or advantage on the specified variable. To control for multiple comparisons for the secondary outcomes (pain Interference, depression), the Benjamini-Hochberg correction method was used, whereby the smaller familywise P value was compared against α = .025 and the larger P value was compared against α = .050. Significance values on the primary outcome (pain intensity) were compared against α = .050. Asterisks (*) indicate estimate values that are significant when comparing the corresponding P value against the appropriate α level, as previously described. For the posttreatment-to-6-month comparisons, significant values indicate that treatment gains were no longer maintained. All analyses were adjusted to control for sex, minority status, years of education, and pain duration.
31
32
33
Figure 3. A cumulative proportion of responders analysis (CPRA) created with percent change in pain intensity (BPI-Intensity) scores per group condition from pre-to post-treatment.
32
Primary Outcome (Pain Intensity)
Controlling for the covariates of participant sex, minority status, pain duration, and
years of education, pain intensity (BPI-Intensity) decreased significantly within groups from
pretreatment to posttreatment (the primary end point) for participants randomized to both
CBT (change estimate, –1.06; 95% CI, –1.65 to –0.47; p < .001) and EDU (change estimate, –
0.83; 95% CI, –1.14 to –0.41; p < .001). The effect sizes were medium for CBT (Hedge’s δT = –
.55) and EDU (Hedge’s δT = –.41). Those treatment gains were maintained at 6 months follow-
up for both treatment allocation arms. UC participants did not show significant change in pain
intensity scores across study time epochs (i.e., pretreatment to posttreatment, posttreatment
to follow-up).
Compared with UC, participants in the CBT and EDU conditions had larger reductions in
pain intensity between baseline and posttreatment (estimated differences: CBT –.80, 95% CI,
–1.48 to –0.11, p <.05; EDU –.57, 95% CI, –1.04 to –0.10, p < .05). At 6 months follow-up,
treatment gains were not maintained for CBT, but were for EDU. Table 8 shows the estimated
baseline to posttreatment and posttreatment to 6-month differences in change scores for CBT
and EDU versus UC and associated 95% CIs. Figure 2 illustrates the predicted mean pain
intensity (BPI-Intensity), pain interference (BPI-Interference), and depression scores (PHQ-9) by
treatment allocation arm, by time point, from the mixed linear models. Figure 3 illustrates the
cumulative proportion of responders for BPI-Intensity from pretreatment to posttreatment by
condition.
Table 9 shows odds ratios, confidence intervals, and P values for clinically meaningful
improvement (i.e., 30% or more decrease in scores) for pain intensity, pain interference, and
depression scores by condition. Compared with pretreatment, CBT participants were greater
than 3 times more likely to achieve clinically meaningful improvement on pain intensity than UC
participants at posttreatment (30.5% versus 11.5%; OR = 3.43; p < .001) and almost 3 times
more likely at 6 months follow-up (21.7% versus 8.5%; OR = 2.70; p = .001). Compared with
pretreatment, EDU participants were 2 times more likely to achieve clinically meaningful
improvement on pain intensity than UC participants at posttreatment (20.0% versus 11.5%; OR
33
= 2.01; p < .001), and 2.16 times more likely at 6 months follow-up (16.4% versus 8.5%; OR =
2.16; p < .001). Table 10 shows a comparison of change estimates for pain intensity (BPI-
Intensity) to minimally important change criteria.21 CBT and EDU exceeded the minimally
important change criterion of 10%21 at posttreatment and at 6 months, whereas UC did not.
34
Table 9. Binary Indexes of Clinically Meaningful Improvement by Treatment Condition and Odds Ratios Comparing Conditions
Number of Participants (%) With
Clinically Meaningful Improvement Odds Ratio (95% Confidence Interval)
Pretreatment to posttreatment
CBT EDU UC CBT Versus UC EDU Versus UC CBT Versus
EDU
n = 82 n = 80 n = 78
Pain intensity 25 (30.5) 16 (20.0) 9 (11.5) 3.43
(2.72-4.32)*** 2.00
(1.52-2.64)*** 1.69
(0.95-2.99)
Pain interference 33 (40.2) 23 (28.8) 14 (18.4) 3.34
(2.26-4.93)*** 2.01
(0.84-4.78) 1.71
(0.97-3.01)
Depression 32 (39.5) 34 (42.5) 22 (28.2) 1.76
(1.37-2.28)*** 1.91
(1.46-2.50)*** 0.91
(0.50-1.68)
Pretreatment to 6 months follow-up
n = 69 n = 68 n = 71
Pain intensity 15 (21.7) 11 (16.4) 6 (8.5) 2.70
(2.46-2.96)*** 2.16
(1.73-2.71)*** 1.21
(0.61-2.40)
Pain interference 24 (34.8) 14 (20.6) 11 (15.7) 3.15
(2.38-4.17)*** 1.23
(1.04-1.44)* 2.44
(0.85-7.07)
Depression 29 (42.6) 23 (33.8) 22 (31.0) 1.60
(1.41-1.82)*** 1.13
(0.96-1.33) 1.51
(0.65-3.51)
Note. Pain intensity measured by BPI-Intensity scale; pain interference measured by BPI-Interference scale; depression measured by PHQ-9 scale. Clinically meaningful improvement was defined as ≥ 30% improvement since pretreatment. To control for multiple comparisons for the secondary outcomes (pain interference, depression), the Benjamini-Hochberg correction method was used, whereby the smaller familywise P value was compared against α = .025 and the larger P value was compared against α = .050. Significance values on the primary outcome (pain intensity) were compared against α = .050. Asterisks (*) indicate estimate values that are significant when comparing the corresponding P value to the appropriate α level, as previously described. All analyses were adjusted to control for sex, minority status, years of education, and pain duration.
*p < .05; ** p < .01; *** p < .001. an = 83. bn = 68. cn = 67. dn = 69.
35
Secondary Outcomes (Pain Interference, Depression)
Using the same latent growth modeling approach as that for pain intensity, the
secondary outcomes of pain interference (BPI-Interference scores) and depressive symptoms
(PHQ-9 scores) were examined and showed similar patterns to that of the primary outcome.
See Table 8 for all relevant change estimates, standard errors, P values, and effect
sizes/Hedge’s δT.
Pain Interference
Pain interference (BPI-Interference) decreased significantly from pretreatment to
posttreatment for CBT (change estimate –1.66, 95% CI, –2.24 to –1.07, p < .001; Hedge’s δT = –
.66, medium-large effect) and EDU (change estimate – 1.00, 95% CI, –1.39 to –0.62, p < .001;
Hedge’s δT = –.40, medium effect). UC participants did not show significant change in pain
intensity scores across study time points (ie, pretreatment to posttreatment, posttreatment to
follow-up).
Treatment gains in the EDU condition were maintained at 6 months follow-up; however,
pain interference scores increased posttreatment to follow-up for CBT participants (p = .020).
Nonetheless, the difference between CBT and EDU on pain interference at 6 months still
trended toward favoring CBT (CBT versus EDU pre–post treatment comparisons of change
estimates; adjusted slopes, p = .067). UC participants did not change significantly on pain
interference across the study.
Compared with UC, participants in the CBT and EDU conditions had larger reductions in
pain interference between baseline and posttreatment (estimated differences: CBT –1.36, 95%
CI, –2.11 to –0.61, p <.001; EDU –.70, 95% CI, –1.31 to –0.09, p < .024). At 6 months follow-up,
treatment gains were maintained for both CBT and EDU. Table 8 shows the estimated baseline
to posttreatment and posttreatment to 6-month differences in change scores for CBT and EDU
versus UC and associated 95% CIs.
Relative to pretreatment levels of pain interference, CBT participants were more than 3
times more likely to achieve clinically meaningful improvement than UC participants at
posttreatment (40.2% versus 18.4%; OR = 3.34; p < .001) as well as at 6 months follow-up
36
(34.8% versus 15.7%; OR = 3.15; p < .001). EDU participants were not significantly more likely
than UC participants to achieve clinically meaningful improvement on pain interference at
posttreatment, but at follow-up they were 1.23 times more likely (20.6% versus 15.7%; p < .05);
see Table 9. Table 10 shows a comparison of change estimates for pain interference (BPI-
Intensity) to minimally important change criteria.24 CBT and EDU exceeded the minimally
important change criterion of 14%24 at posttreatment and at 6 months, whereas UC did not.
Table 10. Comparison of Change Estimates for Pain Intensity (BPI-Intensity) and Physical Function (BPI-Interference) to Minimally Important Change Criteria
BPI-Intensitya
UC CBT EDU
% change pre–post –4.00% –16.28%* –12.74%* % change pre–6 months –7.75% –10.83%* –10.58%*
BPI-Interferenceb
UC CBT EDU
% change pre–post –4.58% –24.75%* –15.18%* % change pre–6 month –1.80% –16.64%* –11.39%
Note: These percentages were calculated by dividing the within-condition change estimates by the baseline scores. For pre–6 month, the within-condition change estimates for piece 1 and piece 2 were added and divided by the baseline score. a. IMMPACT39 criteria for minimally important change for pain intensity (BPI-Intensity) > 10%. b. IMMPACT39 criteria for minimally important change for physical function (BPI-Interference) > 14%. * indicates scores that exceed guideline cutoffs.
Depression
Latent growth modeling revealed that depression (PHQ-9) decreased significantly from
pretreatment to posttreatment for both CBT and EDU participants (CBT change estimate –2.43,
95% CI, –3.68 to –1.19, p < .001; Hedge’s δT = –.38, approaching medium effect; EDU change
estimate –2.24, 95% CI, –3.51 to –0.98, p < .001, Hedge’s δT = –.35, approaching medium
effect). For both treatment allocation arms, gains were maintained 6 months after treatment
ended. Depression scores for UC participants did not change significantly from pretreatment to
posttreatment or from posttreatment to 6 months.
37
Compared with UC, neither the CBT and EDU conditions had larger reductions in
depression scores at posttreatment or follow-up. Table 8 shows the estimated baseline to
posttreatment and posttreatment to 6-month differences in change scores for CBT and EDU
versus UC and associated 95% CIs.
For depression, the proportion of participants with clinically meaningful improvement
was 39.5%, 42.5%, and 28.2% for CBT, EDU, and UC, respectively, with both CBT and EDU
showing significant differences from UC (CBT OR 1.76 [95% CI, 1.37-2.28]; p < .001; EDU OR 1.91
[95% CI, 1.46-2.50]; p < .001). At 6 months, only CBT differed from UC (OR 1.60 [95% CI, 1.41-
1.82]; p < .001; Table 9). Table 11 provides numbers/percentages of participants with
depression scores above/below the “probable depression” cutoff, compared across treatment
conditions.
Table 11. Numbers (Percentages) of Sample With PHQ-9 Scores Above the “Probable Depression” Cutoff (≥ 10) at Baseline, Posttreatment, and 6-month Follow-up, Compared Across Treatment Conditions
Cognitive Behavioral Therapy n (%)
Pain Education n (%)
Usual Care n (%)
Depression (PHQ-9)* Baselinea Scores below 10 36 (37.9) 41 (42.3) 34 (34.7) Scores at or above 10 59 (62.1) 56 (57.7) 64 (65.3)
Pre–post treatmentb
Scores below 10 24 (46.2) 24 (46.2) 11 (21.9) Scores at or above 10 28 (53.8) 28 (53.3) 41 (78.8) Pre–6-month follow-upc Scores below 10 22 (50) 13 (31.7) 13 (27.1) Scores at or above 10 22 (50) 28 (68.3) 35 (72.9) * A score of ≥10 to indicate the presence of probable depression.33
a. Number of participants who completed a baseline assessment (CBT = 95; EDU = 97; UC = 98). b. Available n at posttreatment assessment for pre–post comparison (CBT = 52; EDU = 45; UC = 52). c. Available n at 6-month follow-up assessment for change pre–6-month follow-up comparison (CBT =
44; EDU = 41; UC = 48).
38
Table 12. Results of Analysis of Exploratory Heterogeneity of Treatment Effects
Moderator Estimate 95% CI t p R2 Change
CBT Versus TAU (n = 160)
Sex –0.208 –1.289-0.873 –0.380 .705 .0005
Age –0.098 –0.172 to –0.024 –2.620 .010* .0371
Minority status –0.234 –1.344-0.876 –0.416 .678 .0006
Education (years) 0.131 –0.088-0.349 1.183 .239 .0040
Poverty status –0.759 –2.064 to –0.547 –1.149 .253 .0059
Literacy (WRAT GLE) 0.083 –0.062-0.228 1.129 .261 .0049
Working memory (digit span-backward) 0.246 0.018-0.509 1.841 .068 .0106
EDU Versus TAU (n = 158)
Sex 0.251 –0.843-1.346 0.454 .651 .0008
Age –0.026 –0.092-0.040 –0.782 .436 .0035
Minority status 0.202 –0.851-1.254 0.379 .705 .0006
Education (years) –0.161 –0.421-0.100 1.220 .224 .0074
Poverty status 0.850 –2.278-0.579 1.175 .242 .0084
Literacy (WRAT GLE) –0.111 –0.266-0.043 –1.424 .157 .0101
Working memory (digit span-backward) –0.030 –0.350-0.291 –0.182 .856 .0002
CBT Versus EDU (n = 162)
Sex –0.445 –1.652-0.762 –0.729 .467 .0022
Age –0.072 –0.151-0.006 –1.819 .071 .0194
Minority status –0.446 –1.611-0.719 –0.756 .451 .0019
Education (years) 0.298 0.009-0.587 2.038 .043* .0213
Poverty status 0.043 –1.412-1.497 0.058 .954 < .0001
Literacy (WRAT GLE) 0.196 0.044-0.348 2.550 .012* .0272
Working memory (digit span-backward) 0.493 –0.014-0.999 1.920 .057 .0184
39
Heterogeneity of Treatment Effects—Exploratory Analyses
Table 12 shows the change estimates, 95% CIs, T scores, P values, and R2 change
generated from the regression analyses for the primary outcome variable (pain intensity), with
preintervention scores included as covariates. It is important to note that these are exploratory
analyses and not part of the original proposal or planned analyses. These results are possibly
random findings that, while providing interesting ideas for future targeted research, need
replication prior to drawing any conclusions.
CBT–UC Effects
We found age to be a significant moderator (p = .010) of the difference in effect
between CBT and UC: Within CBT, older participants tended to have lower pain intensity scores
at posttreatment than did younger participants. Furthermore, within UC, older participants
tended to have higher pain intensity scores than did younger participants. Younger participants’
pain intensity scores were more similar across allocation arms than those of older participants,
who tended to have lower pain intensity scores in CBT than in UC. Thus, the treatment
advantage of CBT above UC seems to be observed primarily among older participants.
We found working memory to be a marginally significant moderator (p = .068) of the
difference in effect between CBT and UC. Within CBT, participants with lower working memory
(as measured by the Digit Span Backward test) tended to have lower pain intensity scores at
posttreatment than did participants with higher working memory scores. Within UC, however,
participants with lower working memory scores tended to report higher pain intensity scores at
posttreatment than did participants with higher working memory scores. Participants with
higher working memory scores were more similar across treatment allocation arms than
participants with lower working memory, who tended to have lower pain intensity scores in
CBT than in UC. Thus, the treatment advantage of CBT over UC seems to be observed primarily
among participants with lower working memory. This is likely a random effect and requires
replication prior to drawing any conclusions.
EDU–UC Effects
40
None of the tested moderators were significant for the difference in effect between
EDU and UC.
CBT–EDU Effects
We found age to be a marginally significant moderator (p = .071) of the difference in
effect between CBT and EDU. Within CBT, older participants tended to have lower pain
intensity scores at posttreatment than did younger participants. Within EDU, pain intensity
scores tended to be similar across the age range. Among younger participants, those
randomized to EDU tended to have lower pain intensity scores than those randomized to CBT,
whereas among older participants, those randomized to CBT tended to have lower pain
intensity scores than those randomized to EDU.
We found years of education to be a significant moderator (p = .043) of the difference in
effect between CBT and EDU. Within CBT, participants with fewer years of education tended to
have lower pain intensity scores at posttreatment than did participants with more years of
education. However, within EDU, participants with more years of education tended to have
lower pain intensity scores than did participants with fewer years of education. Among
participants with fewer years of education, those randomized to CBT tended to have lower pain
intensity scores than those randomized to EDU, but among participants with more years of
education, those randomized to EDU tended to have lower pain intensity scores than those
randomized to CBT.
We found literacy (WRAT GLE) to be a significant moderator (p = .012) of the difference
in effect between CBT and EDU. Within CBT, participants with lower literacy scores tended to
have lower pain intensity scores at posttreatment; however, within EDU, participants with
higher literacy scores tended to have lower pain intensity scores at posttreatment than did
participants with lower literacy scores. Among participants with lower literacy scores, those
randomized to CBT tended to have lower pain intensity scores at posttreatment; however,
among participants with higher literacy scores, those randomized to EDU tended to have lower
pain intensity scores at posttreatment than did those randomized to CBT.
41
We found working memory (Digit Span-Backward) to be a marginally significant
moderator (p = .057) of the difference in effect between CBT and EDU. Within CBT, participants
with lower working memory scores tended to have lower pain intensity scores at posttreatment
than did participants with higher working memory scores; however, within EDU, participants
with higher working memory scores tended to have lower pain intensity scores at
posttreatment. Among participants with lower working memory scores, those randomized to
CBT tended to have lower pain intensity scores at posttreatment than those randomized to
EDU; however, among participants with higher working memory scores, those randomized to
EDU tended to have lower posttreatment pain intensity scores than those randomized to
CBT. This is likely a random effect and requires replication prior to drawing any conclusions.
Adverse Events
During the trial, 9 of 95 (9.4%) CBT, 16 of 97 (16.5%) EDU, and 18 of 98 (18.4%) UC
participants reported seeking treatment at an emergency department (mostly temporary pain
exacerbations, with a smaller number of adverse events reported due to infections or injuries).
None of the reported adverse events were because of participation in the trial. Six participants
were hospitalized overnight for reasons unrelated to the study (e.g., asthma exacerbation): 3 in
UC, 2 in EDU, and 1 in CBT.
Discussion
Study Results in Context/Addressing Methodological Gaps
Chronic pain treatment of individuals receiving care in low-income clinics carries a wide
range of challenges, from limited treatment options to patient nonadherence. Thus, although
the potential impact of adapted treatments is large, the task of delivering treatment is difficult.
It is important to emphasize that our study tested literacy-adapted CBT and EDU in a unique
population: patients who typically do not receive any psychosocial treatment for pain
management. Most do not even receive appropriately adapted education about what chronic
pain is and how it is treated differently than acute pain. Many researchers and practitioners
have questioned the feasibility of an approach such as CBT for low-SES people facing the
challenges of limited resources, logistics, and low literacy skills. CBT requires a certain amount
42
of abstract thinking and problem solving; utilizes written workbooks, handouts, and
worksheets; and assigns homework, thus requiring more patient effort than taking analgesic
medication or receiving biomedical interventions. Even group pain education employs written
workbooks and requires patient time and effort during classes. The results of this study call into
question the validity of those biases.
This study produced evidence supporting the effectiveness and acceptability of 2
psychosocial group treatments suitable for serving as primary or adjunctive care options, with a
small tendency toward an outcome advantage of CBT over EDU but beneficial effects of EDU
nonetheless. Among adults attending low-income clinics in Alabama, both literacy-adapted CBT
and EDU resulted in significant within-subjects improvement in pain intensity, interference, and
depressive symptoms from pretreatment to posttreatment—gains that were largely maintained
at 6 months follow-up; UC, representing standard care, did not produce these significant
changes. Furthermore, a greater number of CBT participants than EDU participants achieved
clinically meaningful improvements in pain intensity and interference, and both treatment
allocation arms achieved greater numbers of CMIs than UC. Effect sizes for CBT were medium
to large, and EDU effect sizes were medium. These effect sizes were similar to those obtained
using nonadapted evidence-based treatments for chronic pain in less disadvantaged
populations.66-68
The findings of this study are partially consistent with those of an earlier pilot study with
a smaller number of participants but with similar demographics.19 The earlier study found that
both CBT and EDU showed significant improvement in pain intensity and interference from
pretreatment to posttreatment, effects that were maintained at follow-up. Other studies have
used pain education as an attention-control condition. Our adaptations of group pain education
included a focus on enhancing motivation for pain self-management, emphasizing therapeutic
alliance and group cohesion, and giving relevant information that participants could discuss and
potentially use—without providing actual skills training. Thus, both CBT and EDU interventions
offer a rich arsenal of information (and skills, in the case of CBT) based on the biopsychosocial
model and promote pain self-management. The fact that EDU produced significant changes in
outcomes speaks to the utility of providing groups treatments based on the biopsychosocial
43
model to help arm patients with usable information and prepare them to engage in pain self-
management. The fact that beneficial outcomes were accrued beyond pain intensity per se (i.e.,
improving both depressive symptoms and interference in daily activities due to pain) supports
the argument that both CBT and EDU interventions can improve patients’ lives in multiple ways
that are meaningful to them. Past findings combined with the present results strongly support
the utility and acceptability of a competently executed psychosocial intervention based on the
biopsychosocial model.
Decisional Context
We designed the current study to correct large, persistent disparities experienced by a
hard-to-reach population of multiply disadvantaged individuals with chronic pain. With few
financial resources (72.4% of the participants were at or below the poverty threshold for
household size), these individuals experience significantly worse health outcomes, suffer from
many untreated negative sequelae of their pain conditions, and have access to few treatment
options—and those treatments often have little to no empirical support in the population.
While the inaccessibility of psychosocial treatment for this population is not in doubt, the
suitability of existing treatments is questionable at best. Nonadapted psychosocial treatments
that often rely on written homework, complex terminology, and abstract concepts have little
potential for success in a population expressing pronounced health literacy deficits and low
educational achievement. According to the demographics of our current sample, approximately
30% reported no degree, with an additional 39% reporting only a GED or a high school diploma.
The National Assessment of Adult Literacy in 2003 reported that 15% of adults in the general
population did not graduate from high school,69 demonstrating substantially lower levels of
education in our sample. Further, on average, our sample read at the seventh-grade level,
suggesting potential difficulties for a considerable portion of our participants in comprehending
various sources of medical information. These statistics serve to emphasize the challenges
facing this population in obtaining adequate medical care (including psychosocial care),
especially given their impoverishment, cumulative health information deficits, and multiple life
stressors associated with low educational attainment and low income.
Responding to a clear need for appropriately adapted patient materials and approaches
44
for the treatment of a serious public health concern (chronic pain), the PI developed
population-adapted interventions to provide these individuals with EDU and CBT pain
management classes that show promise for bridging these gaps in accessibility and suitability.
Developed in collaboration with experts as well as patient stakeholders, the interventions are
specifically designed for individuals who experience chronic pain and who are financially
disadvantaged, typically with low educational attainment and low health literacy. It is critical to
understand that, unlike a surgery that may work roughly the same across groups, psychosocial
treatments usually require adaptation for disadvantaged populations if active treatment
mechanisms are to be elicited. As such, rather than generating treatment algorithms, the
proposed study sought to provide compelling evidence for the efficacy of treatments
recommended and widely available for more advantaged individuals but unavailable to a
population badly in need of them. A comparative efficacy trial of these interventions compared
with usual medical care was a critical empirical step needed to demonstrate the effectiveness
of these adaptations at providing this population access to vital but currently inaccessible
psychosocial treatment. Indeed, the success of both CBT and EDU relative to their baseline
scores in the current and previous study19 demonstrates the stark need in this population for
appropriately adapted and skillfully delivered psychosocial treatments.
As an intervention involving less expense, time, and effort on the part of patients and
staff, EDU may represent a viable alternative to CBT in low-income clinics with staff who may
not be trained, or have access to training, in CBT—particularly if the only alternative is usual
medical care alone. It is important to note, however, that our results point to benefits
associated with a very carefully executed literacy-adapted group pain education treatment—
one that is focused on the biopsychosocial model and pays careful attention to therapeutic
alliance and group cohesion.
In terms of durability of treatment effect, although within-condition outcomes remained
significant for CBT and EDU groups at the 6-month follow-up point, and although slope
comparisons between CBT and UC showed a significant advantage of CBT over UC at our
primary end point (posttreatment), this comparative advantage was no longer significant at 6
months follow-up. Clearly, future research efforts need to focus on enhancing durability of
45
treatment, (e.g., whether “booster” or drop-in groups following treatment enhance long-term
outcome), and sustainability (e.g., identifying and facilitating reliable mechanisms for
reimbursement). Because the retention rate for the follow-up assessments was relatively low
(72%), this also suggests that further efforts need to be made to enhance continued access and
continued care. The nature of the population is such that transportation difficulties, changes in
residency and contact information, family health issues, and other exigencies made
participation and follow-up all the more challenging.
Implementation of Study Results
This project provides 3 avenues for facilitating patient response to treatment and
reducing health outcome disparities: intervention level, provider level, and systems level. We
focused our adaptations of these treatments largely at the intervention level to reduce health
outcome disparities, but this is not simply a matter of reducing the literacy level of patient
materials: Health literacy adaptations for psychosocial treatments must adapt the process of
treatment as well. Furthermore, making usable, adapted, treatment materials readily accessible
to clinicians via manuals and patient workbooks offers a provider-level intervention pathway
that is currently not available. Relatedly, use of adapted materials also reminds the provider of
the importance of considering culture and health literacy in every patient–provider interaction.
Further, meeting the psychosocial needs of patients may provide a time and cost savings to
medical professionals and improve their efficiency, thus supplying a systems-level intervention.
Finally, offering options for treatment other than expensive, invasive treatments—and readily
providing the treatment materials—increases feasibility for implementation into a resources-
strapped health care system.
The successful implementation of these group interventions in typical low-income care
settings is not without its challenges. Relatively few behavioral health specialists employed in
community health clinics have the necessary skill sets in CBT, and—with the possible exception
of substance abuse treatment—group psychosocial interventions are less common than
individual interventions. Further, traditionally, behavioral health interventions have been
almost exclusively used for treatment of individuals with mental illness, rather than weaving
46
behavioral health into the larger fabric of primary medicine. Although there is some promise
that behavioral health integrated into primary care is slowly emerging in the health care
system, it has faced substantial challenges even with the health care reforms that have taken
place in the past decade.
It is clear from our study that implementation of such programs takes both
administrative and medical provider/medical staff champions. We were fortunate to partner
with a community health center based on an established working relationship. The staff here
were key champions for the project. The dilemma for wider implementation of these
interventions is to promote them in such a way that both decision makers and medical
providers understand their advantage. Faced with their own (growing) burdens of caring for
patients with low incomes, administrators and providers are unlikely to proactively search out
new opportunities requiring additional staff and training, unless they are convinced that these
treatments effectively reduce their care burden while improving key patient outcomes. One
challenge will be to appropriately and effectively promote our results to these key
stakeholders. Further, financially strapped and understaffed community health centers need
patient and interventionist materials that can be readily implemented. Another challenge will
be to ensure that our interventionist materials (created for licensed psychologists and graduate
students in clinical psychology doctoral programs) are appropriate and immediately usable for
behavioral health providers with less training and to ensure that our patient materials are
readily accessible for distribution to patients. The patient workbooks and therapist
supplements are copyrighted but freely available at pmt.ua.edu/publications.html.
Furthermore, we intend to be available to provide training as interested organizations approach
us. We have already done such trainings (in Gadsden, Alabama; Mobile, Alabama; and Phoenix,
Arizona) at organizations that were not community partners in the treatment study.
Another issue regarding implementation of programs such as this involves the economic
feasibility of providing behavioral health services. Billing via appropriate procedural
terminology coding provides economic value to any clinical service. Under the Current
Procedural Terminology coding system, which provides reimbursement codes for mental health
practitioners, Health and Behavior (H&B) codes provide the means for behavioral health
47
practitioners to work with patients who have physical health problems but may not have
mental illness diagnoses. These codes provide for assessment and intervention activities,
including cognitive, behavioral, social, and psychophysiological procedures used for preventing,
treating, or managing health problems. Medicare, Medicaid, and most private insurers now
reimburse for H&B codes, although at a lower rate per hour than the more “traditional” billing
from mental health practitioners for patients with psychiatric codes.
A final issue associated with implementation involves providing appropriate access and
incentives for participation to the patients themselves. In our study, we were able to provide
patient participants with money to defer their travel expenses (and in the case of the
assessments, we provided funds to compensate patients for their time and effort). It is highly
unlikely that most community health centers will be able to provide such funds to patients.
What, then, would be an appropriate noncoercive incentive? It is possible that linking patients’
primary medical treatment for chronic pain to their participation in a psychosocial pain
management treatment would (1) increase efficiency in terms of patient travel burden and wait
time, and (2) underscore the importance to patients (and providers) of the inseparability
between behavioral and primary medical care.
Generalizability/Subpopulation Considerations
As can be seen from Table 7 and earlier in the Results section, our sample was mostly
African Americans with incomes below the poverty threshold. The mean reading grade level
was 7.5, with more than 25% of participants having no educational degree and another 40%
having only a high school diploma or a GED. Thus, our study sample reflected a multiply
disadvantaged population in which health and treatment disparities are prominent. Previous
studies suggest that this hard-to-reach population presents unique challenges for addressing
disparities.38 Ethnic minority status and other chronic pain risk factors (e.g., low health literacy,
education, and income) were greatly overrepresented in this population. As such, these
individuals are likely to be only representative of other ethnic minorities with chronic pain who
are carrying significant risk factors. Given the demographics of the sample, our success in
recruiting and retaining the participants is remarkable, with overall completion rates at the
primary end point of 83% and 6-month follow-up completion rations of 72%.
48
Study participants were enrolled in a single health care system and recruitment,
enrollment, and retention were carefully monitored and nurtured by patient coordinators
employed as part of the study. The generalizability to other health care settings with fewer
resources for patient coordination is not known. Further, assessment questionnaires were read
aloud to participants, with assessors available for clarification, which limits the feasibility of use
of non-literacy-adapted questionnaires in clinical settings.
As can be seen from Table 12, exploratory HTE analyses offered interesting but very
tentative patterns to consider in future research. In general, participants within the CBT
condition with lower literacy and working memory and less educational attainment had greater
pain intensity reductions relative to those in the CBT condition with higher scores in these
domains. One might speculate that this finding could suggest that our literacy adaptations and
reductions of cognitive demands of the treatment were successful, particularly for the more
disadvantaged of our sample. Similarly, when comparing CBT against EDU, those with lower
literacy and working memory and less educational attainment had greater pain intensity
reductions in CBT relative to EDU, and those with higher literacy and working memory and
greater educational attainment had greater pain intensity reductions in EDU relative to CBT.
Given these results, it may be that a more action-oriented treatment (e.g., weekly relaxation
compact discs and audio suggestions for trying out new skills in CBT) is more effective for those
with the fewest educational/literacy/working memory advantages, whereas a more “fact-
oriented” treatment (e.g., presentation of pain facts and related discussion) is more effective
for those with the greater number of educational/literacy/working memory advantages. It is
important to note that our entire participant sample was multiply disadvantaged relative to
national normative samples. Furthermore, these HTE analyses were only exploratory and did
not involve any a priori hypotheses—and thus should be interpreted with extreme caution.
Because HTE effects may have occurred via chance, replication is necessary.
In our sample, the mean duration of pain was > 16 years, with BPI pain intensity scores
and BPI pain interference scores (mean 6.52 and 6.6, respectively) indicating moderate levels of
intensity and interference in daily activities due to pain. It is unclear whether those with very
severe pain would differentially benefit from either treatment; future subgroup analyses with
49
our data may shed light on this question. On average, most of our sample (62%) had at least
moderate levels of depressive symptoms (PHQ-9 scores ≥ 10). This is not unusual in patients
with chronic pain, and thus we expect our results would generalize to other patients with pain
who experience at least moderate levels of depression.
Regarding application to broader populations, these treatment adaptations are
expected to be largely replicable to other similarly challenged individuals. Using published
guidelines, applied theory (cognitive load), expert opinion, and patient feedback, the PI reduced
the reading level and cognitive investment necessary to engage in these treatments.38 There is
no reason to believe that these changes would not improve most pain patients’ response to
these interventions, but particularly for the more complex CBT pain management group, these
were crucial adaptations. With small adaptations for culture, these interventions could be
quickly adaptable to other populations expressing low health literacy, such as those with
limited English ability (e.g., ESL individuals), those with cognitive impairment (e.g., individuals
with brain injuries), or children and young adults with chronic pain. Furthermore, the chosen
delivery mechanism of group treatment provides fewer cost barriers to wide implementation.
Consequently, this study offers empirical support for an innovative and greatly needed pair of
health literacy–adapted psychosocial interventions for chronic pain. This can provide a pathway
for broader applications to many individuals who have chronic pain accompanied by health
disparities.
Study Limitations
Limitations include the following: (1) Study participants were enrolled in a single health
care system, and recruitment, enrollment, and retention were carefully monitored and
nurtured by patient coordinators employed as part of the study. (2) Patients randomized to
treatment groups were provided with travel funds to enable them to attend each weekly
session. Because most patients would have been unable to attend the treatment sessions
without travel money, this was an unavoidable limitation; thus, providing travel money likely
influenced the attendance rate. The generalizability to other health care settings with fewer
resources for patient coordination and without the capacity to provide travel funds or
transportation is not known. (3) Our use of the same therapists for both treatment groups
50
provided an avenue for contamination across allocation arms. This bias was balanced against
the possibility that therapist effects may drive between-group treatment differences (e.g.,
proficiency bias due to experience, charisma, etc.). Ultimately, we felt that the small number of
therapists led to an increased risk for therapist effects. We decided to vary and track therapists
across treatment allocation arms (potentially controlling for therapist effects) and rely on
therapist training and fidelity procedures to reduce the possibility of contamination between
treatment allocation arm. (4) Patient self-report may have been subject to patient biases (e.g.,
attention bias), particularly if patients felt engaged with a treatment (e.g., demand
characteristics). (5) Withdrawal bias may have also been a limitation in the study. Previous
research suggested that the CBT condition could lead to greater dropout.19 In anticipation of
this potential problem, the current CBT intervention included a number of changes to increase
its acceptability (e.g., completing skills practice exercises in-session with interactive teaching,
including audio summaries of each session and the skills taught rather than relying on the
written workbook summary, removing the requirement that patients do written homework on
worksheets and turn them in), and CBT completion rate (defined as participation in the
posttreatment assessment) was not different between CBT and EDU. However, about 10%
fewer participants randomized to EDU attended at least 1 session compared with CBT, and a
smaller number of EDU participants (61.9%) received an adequate treatment dosage (> 6
sessions) compared with CBT (74.7%). Subsequent sensitivity analysis of primary and secondary
outcomes showed that dropout was not significantly related to outcomes at any time point, nor
did dropout affect any inference of the original model estimates, indicating that the missing-at-
random assumption was an appropriate approach for analyzing these data. Hence, the
sensitivity analyses provided an analysis that supported the MAR assumption. Further, we used
an intent-to-treat analysis in our data plan to reduce the negative impact of possible differential
dropout between allocation arms.
Future Research
Future research should investigate the processes involved in treatment efficacy to
determine the active treatment mechanisms involved in these group interventions. For
example, potential mechanisms include the provision of biopsychosocial pain information,
51
group intervention modality and group cohesion, therapeutic alliance, and/or specific pain
management skills training. Future ancillary analyses of the current data set may provide some
hypotheses to be examined in subsequent studies. Further, the literacy-adapted treatments
should be tested on other disadvantaged populations (e.g., patients with English as a second
language), as well as in non-disadvantaged populations, to determine whether the treatments
are generalizable beyond the population studied in the current work. Research enhancing
external validity and facilitating implementation of these results into financially strapped health
care facilities will allow for greater uptake of these effective treatments for disadvantaged
patients with chronic pain. Finally, given the fragility of the population studied, more research
needs to be focused on the durability of treatment effects over time, perhaps exploring the use
of ongoing or booster groups for patients.
Conclusions Among adults attending low-income community health clinics, 2 10-week group
psychosocial treatment programs (cognitive-behavioral therapy and pain education) adapted to
reduce literacy and cognitive demands resulted in significant improvement in pain intensity,
interference, and depression from pretreatment to posttreatment and at 6 months, whereas
usual medical care did not. Small differential treatment benefits of CBT over EDU for pain
intensity, interference, and depression suggest that CBT may have a slight advantage, but both
CBT and EDU were clearly superior to UC alone.
The social importance of providing the underserved with equal access to health care
cannot be understated. Ultimately, given its potential translational impact and the striking
national need for health literacy–adapted treatments, the current project represents a crucial
empirical step toward the goal of reducing health-related disparities and increasing quality of
life in low-literacy, low-SES individuals with chronic pain.
Difficulties associated with implementation of psychosocial treatments into financially
strapped community health clinics may preclude the adoption of CBT in cases in which
behavioral health clinicians are not trained in CBT or are unable to receive such training. In
these cases, we argue that group EDU, as implemented in the current study, is a potentially
52
viable treatment approach. The group educational treatment included a biopsychosocial focus
on enhancing motivation for pain self-management, emphasizing therapeutic alliance and
group cohesion and giving participants relevant information to discuss and use, but without
explicit skills training such as those employed in CBT. Thus, while educative in nature, EDU
provided information promoting pain self-management that was delivered in an interactive
group format and that emphasized therapeutic alliance and group cohesion.
As an intervention involving less expense, time, and effort on the part of patients and
staff, EDU may represent a viable alternative to CBT in low-income clinics—particularly if the
only alternative is usual medical care alone. It is important to note, however, that our results
point to benefits associated with interventions based on very carefully executed literacy-
adapted group pain psychosocial treatments that focused on the biopsychosocial model and
paid careful attention to therapeutic alliance and group cohesion.
Study strengths include a large sample with adequate statistical power to detect
clinically meaningful effects, close matching of the CBT and EDU interventions in format, and
recruitment/retention of a difficult-to-reach population that suffers many inequalities in health
care options. Participants in our sample were disadvantaged, often representing a triple
disparity of low income, low primary literacy, and minority status (African American). Thus, the
reported benefits in the current trial are noteworthy given both the nature of the population
studied and the careful implementation of appropriately adapted patient materials and
approaches to reduce literacy and cognitive demands of the treatment. As such, our results
have important public health implications. Future research facilitating implementation of these
results into financially strapped health care facilities will allow for greater uptake of these
effective treatments for disadvantaged patients with chronic pain.
53
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Copyright© 2019. University of Alabama-Tuscaloosa. All Rights Reserved.
Disclaimer:
The [views, statements, opinions] presented in this report are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors or Methodology Committee.
Acknowledgement:
Research reported in this report was [partially] funded through a Patient-Centered Outcomes Research Institute® (PCORI®) Award (#941) Further information available at: https://www.pcori.org/research-results/2012/treating-chronic-pain-using-approaches-adapted-patients-limited-reading-skills