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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