Key Points
Question
Do older adults with chronic pain benefit from psychological therapies?
Findings
In this systematic review and meta-analysis including 22 studies with 2608 participants, psychological interventions that used cognitive behavioral therapy modalities were associated with statistically significant benefits in terms of reduced pain and catastrophizing beliefs as well as improved self-efficacy for managing pain. Benefits were small and documented at the time of treatment completion; with the exception of pain reduction, evidence is lacking for the persistence of observed benefits in other assessments conducted up to 6 months later.
Meaning
Among older adults with chronic pain, psychological therapies have a small, but statistically significant, benefit for reducing pain and catastrophizing beliefs and improving self-efficacy for managing pain.
Abstract
Importance
Chronic noncancer pain (hereafter referred to as chronic pain) is common among older adults and managed frequently with pharmacotherapies that produce suboptimal outcomes. Psychological treatments are recommended, but little information is available regarding their efficacy in older adults.
Objective
To determine the efficacy of psychological interventions in older adults with chronic pain and whether treatment effects vary by participant, intervention, and study characteristics.
Data Sources
MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from inception to March 29, 2017.
Study Selection
Analysis included studies that (1) used a randomized trial design, (2) evaluated a psychological intervention that used cognitive behavioral modalities alone or in combination with another strategy, (3) enrolled individuals with chronic pain (pain ≥3 months) with a sample mean age of 60 years or older, and (4) reported preintervention and postintervention quantitative data.
Data Extraction and Synthesis
Two of the authors independently extracted data. A mixed-model meta-analysis tested the effects of treatment on outcomes. Analyses were performed to investigate the association between participant (eg, age), intervention (eg, treatment mode delivery), and study (eg, methodologic quality) characteristics with outcomes.
Main Outcomes and Measures
Pain intensity was the primary outcome; secondary outcomes included pain interference, depressive symptoms, anxiety, catastrophizing beliefs, self-efficacy for managing pain, physical function, and physical health.
Results
Twenty-two studies with 2608 participants (1799 [69.0%] women) were analyzed. Participants’ mean (SD) age was 71.9 (7.1) years. Differences of standardized mean differences (dD) at posttreatment were pain intensity (dD = −0.181, P = .006), pain interference (dD = −0.133, P = .12), depressive symptoms (dD = −0.128, P = .14), anxiety (dD = −0.205, P = .09), catastrophizing beliefs (dD = −0.184, P = .046), self-efficacy (dD = 0.193, P = .02), physical function (dD = 0.006, P = .96), and physical health (dD = 0.160, P = .24). There was evidence of effects persisting beyond the posttreatment assessment only for pain (dD = −0.251, P = .002). In moderator analyses, only mode of therapy (group vs individual) demonstrated a consistent effect in favor of group-based therapy.
Conclusions and Relevance
Psychological interventions for the treatment of chronic pain in older adults have small benefits, including reducing pain and catastrophizing beliefs and improving pain self-efficacy for managing pain. These results were strongest when delivered using group-based approaches. Research is needed to develop and test strategies that enhance the efficacy of psychological approaches and sustainability of treatment effects among older adults with chronic pain.
This systematic review and meta-analysis evaluates the use of psychological interventions for older adults with chronic pain.
Introduction
Chronic noncancer pain (hereafter referred to as chronic pain) is one of the most common conditions encountered by health care professionals.1 Chronic pain is particularly common among individuals aged 60 years or older and is associated with substantial disability and health care costs.1,2,3,4,5 Among older adults, management of chronic pain is complicated by age-related physiologic changes, competing comorbidities that limit treatment options, patient barriers (eg, fear of deleterious adverse effects from medications),6 health care professional barriers (eg, lack of knowledge),7 large adverse effect profiles of commonly administered pharmacologic therapies,8 and a limited evidence base to guide treatment.5
Given these limitations and concerns, as well as the ongoing opioid epidemic,9 nonpharmacologic therapies that use cognitive behavioral therapy (CBT) approaches, including cognitive and behavioral coping skills training, cognitive restructuring, and behavioral activation techniques, have received increased attention as treatments for individuals with chronic pain.10,11,12,13,14,15,16,17,18,19 Cognitive behaviorally based approaches have been shown to have small but statistically significant associations with pain, mood, and disability in nonelderly adults with chronic pain.10 In recent years, the number of studies investigating nonpharmacologic approaches for the treatment of chronic pain in older populations is expanding. One quantitative review examined the effectiveness of psychological approaches for chronic pain in older adults in studies published between January 1975 and March 2008.11 This review, which included 12 clinical trials and 5 uncontrolled pilot studies, found that psychological approaches were moderately effective in reducing pain but did not have a significant effect on depressive symptoms, physical functioning, or pain medication use.11
Given the increasing interest in nonpharmacologic modalities and the expanding number of published studies in this area over the past decade, we conducted a comprehensive systematic review and meta-analysis to evaluate the efficacy of CBT-based approaches for chronic pain among older adults. As a secondary aim, we conducted preplanned analyses to determine whether specific participant (eg, pain type), intervention (eg, mode of therapy delivery), and study (eg, methodologic quality score) characteristics moderated treatment outcomes.
Methods
Literature Search
This systematic review and meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement.20 Comprehensive searches of MEDLINE (Ovid), Embase (Ovid), PsycINFO (EBSCOhost), and the Cochrane Library (Wiley) were performed to identify clinical trials that evaluated 1 or more psychological intervention for the treatment of chronic pain in older adults published from database inception through June 28, 2016. An updated search was performed (from June 29, 2016, through March 29, 2017) to identify new publications. Subject headings and keywords included chronic pain, noncancer pain, musculoskeletal pain, osteoarthritis, arthritis, rheumatoid, back pain, mindfulness, cognitive therapy, behavioral therapy, cognitive-behavioral, CBT, older adults, and elderly. The BMJ Clinical Evidence Randomized Controlled Trial Strategy filter21 was applied to the MEDLINE and Embase searches. We used a combination of keywords and subject headings representing trials in the PsycINFO and Cochrane searches. Additional studies were identified by reference searching in Scopus using the “cited by” and “view references” features. The MEDLINE search strategy is provided in eTable 1 in the Supplement.
Eligibility Criteria and Study Selection
We included studies if they (1) used a randomized clinical trial design; (2) evaluated CBT techniques (see Table 1 for details) as a stand-alone treatment or in combination with another strategy (eg, exercise); (3) enrolled participants with chronic pain, defined as pain lasting 3 months or longer at the time of enrollment; (4) focused on older individuals as reflected by a sample mean age of 60 years or older; and (5) reported preintervention and postintervention quantitative data (ie, means and SDs or SEs) for each group for each assessment (or data for baseline and change scores). We excluded studies that targeted patients with pain due to cancer or chronic headache to be consistent with a Cochrane review on this topic,10 did not report full quantitative results on outcomes and were not willing or able to share their data upon request, were published in languages other than English, or were not published in a peer-reviewed journal.
Table 1. Psychological Modalities Used in Analyzed Studies.
| Method | Specific Technique |
|---|---|
| Behavioral coping skills training | Muscle relaxation Activity-rest cycling Meditation Mindfulness exercises |
| Cognitive coping skills training | Visualization/guided imagery Counting backward |
| Cognitive restructuring | Self-monitoring of thoughts Identifying irrational thoughts related to pain and developing alternative thoughts |
| Behavioral activation | Goal setting Pleasant activity scheduling |
| Acceptance | Practice awareness of avoidance behaviors that aim to control pain Practice strategies to minimize reactivity to pain sensations |
After duplicates were removed, 2 of us (B.N., R.B.) screened titles and abstracts of the identified searches independently followed by a full-text inspection of potentially eligible articles to determine eligibility, with disagreements resolved by consensus. The study selection process appears in eFigure 1 in the Supplement.
Accounting for Studies With Multiple Arms
Five studies used 3 arms.22,23,24,25,26 To ensure comparability across all studies, we included 1 intervention and 1 control group from these 5 studies. Two of the studies used 2 control groups.22,23 We included the active control group in both studies. One study evaluated 2 intervention modalities (ie, a physical therapist delivered pain-coping skills training vs physical therapist delivered pain-coping skills training along with an exercise training component) and 1 control group.24 We pooled the data from the 2 intervention groups. One study reported 2 intervention groups, including a group-based intervention and an individual-based intervention; posttreatment outcomes were reported as pooled data from the 2 intervention groups.25 Finally, 1 study used 2 intervention groups: 1 delivered CBT for pain and insomnia and the other delivered CBT for pain only. We extracted data from the CBT for pain-only group.26
Outcomes
The research team extracted data on outcomes that prior research has shown to be positively affected by psychological therapies10,11,15,16,23 as well as outcomes that were assessed in a minimum of 4 studies in the sample. We abstracted data on 8 outcomes in 3 domains: pain (pain intensity, pain-related interference), psychological (depressive symptoms, anxiety, catastrophizing beliefs, and self-efficacy for managing pain), and functional (self-reported physical function and physical health). For studies that used more than 1 pain intensity measure (eg, current pain, average pain), we used the mean of the measures as the outcome. Finally, we extracted data on 2 additional outcomes given their importance—change in pain medication use and adverse events.27 Table 2 reports the outcomes assessed in each study.
Table 2. Characteristics of Included Studies.
| Source | Participant Age, Mean (SD); Women, % | Pain Type and Duration, Mean (SD) | Sample Size, Intervention/Control Groups, No.a | Intervention | Control | Follow-up Times | Intervention Duration | Mode of Therapy, Mode of Delivery | Outcome Measure (Scoring Instrument) |
|---|---|---|---|---|---|---|---|---|---|
| Alonso-Fernández et al,28 2016 | 83 (6.8) y (cutoff, ≥65 y); 78% women |
Musculoskeletal, 23.3 (20) y | 27/26 | ACT and SOC | Minimal support (2-h educational group session) | Posttreatment | 9 wk | Group, in person | Pain intensity (VAS), pain interference (VAS), depression (GDS), anxiety (PASS20), catastrophizing (PCS) |
| Andersson et al,29 2012 | 72 (4.6) y (cutoff, ≥65 y); 76% women |
Back and/or neck, 15.8 (14.5) y | 11/10 | CBT | Waiting list | Posttreatment | 6 wk | Group, in person | Pain intensity (MPI), pain interference (MPI), depression (HADS), anxiety (HADS), catastrophizing (CSQ), physical function (MPI) |
| Appelbaum et al,30 1988 | 62 (9) y (cutoff, NR); 11% women |
Rheumatoid arthritis, 15 (9.6) y | 9/9 | CBT | Symptom monitoring only | Posttreatment | 6 wk | Individual, in person | Pain intensity (pain index), physical function (DAQ) |
| Bennell et al,24 2016 | 63.4 (8.0) y (cutoff, ≥50 y); 60% women |
Knee osteoarthritis, 5.7 (NR) | 134/67 | (1) PCST and exercise, (2) PCST | Exercise | Posttreatment, 32 and 52 wk | 12 wk | Individual, in person | Pain intensity (VAS), depression (DASS21), anxiety (DASS21), catastrophizing (PCS), self-efficacy (ASES), physical function (WOMAC-function), adverse events |
| Berman et al,31 2009 | 65.8 (NR) y (cutoff, ≥50 y); 68 (87%) women | Mixed chronic, NR | 41/37 | Mind-body self-care, pain management | Waiting list | Posttreatment | 6 wk | Individual, internet | Pain intensity (NRS), pain interference (BPI), depression (CES-D), anxiety (STAI-6), self-efficacy (PSEQ) |
| Carmody et al,32 2013 | 67.5 (9.5) y (cutoff, ≥55 y); 3% women |
Mixed chronic, 17.5 (16.5) y | 37/33 | Telephone delivered, CBT | Pain education, telephone sessions | Posttreatment, 3 and 6 mo | 20 wk | Individual, over the phone | Pain intensity (NRS), depression (BDI), catastrophizing (CSQ), physical health (SF-12) |
| Cederbom et al,33 2017 | 84 (5.8) y (cutoff, ≥65 y); 100% women |
Musculoskeletal, 27.4 (22) y | 10/7 | Integrated behavioral medicine in physical therapy | Received advice regarding physical activity | Posttreatment, 3 mo | 12 wk | Individual, in person | Pain intensity (NRS), catastrophizing (CAT), self-efficacy (CSQ), physical function (NRS) |
| Cook,34 1998 | 77.5 (8.3) y (cutoff, ≥60 y); 62% women |
Mixed chronic, 25 (NR) y | 11/10 | CBT | Education, attention support | Posttreatment, 4 mo | 10 wk | Group, in person | Pain intensity (NRS), pain interference (RMDQ), depression (GDS), change in pain medication use |
| Ersek et al,35 2003 | 81.9 (5.8) y (cutoff, ≥65 y); 87% women |
Mixed chronic, NR | 17/23 | Pain self-management | Educational booklet | Posttreatment, 3 mo | 8 wk | Group, in person | Pain intensity (GCP), pain interference (GCP), depression (GDS), physical health (SF-36), change in pain medication use |
| Ersek et al,36 2008 | 82 (6.5) y (cutoff, ≥65 y); 85% women |
Musculoskeletal, NR | 114/103 | Pain self-management training | Education only (books) | Posttreatment, 6 and 12 mo | 7 wk | Group, in person | Pain intensity (BPI), pain interference (BPI), depression (GDS), catastrophizing (CSQ), self-efficacy (ASES), change in pain medication use |
| Haas et al,37 2005 | 77.2 (7.7) y (cutoff, ≥60 y); 84% women |
Low back, NR | 54/47 | Stanford’s chronic disease self-management program | Waiting list | 6 mo | 6 wk | Group, in person | Pain intensity (MVK), pain interference (Von Korff scale), self-efficacy (ASES), change in pain medication use |
| Hurley et al,25 2007 | 67 (NR) y (cutoff, ≥65 y); 70% women |
Knee, NR | 127/238 | Rehabilitation program integrating exercise, self-management, and active coping strategies delivered in 2 groups: (1) individual rehabilitation, (2) group rehabilitation | Usual primary care | Posttreatment, 6 mo | 6 wk | Individual or group, in person | Pain intensity (WOMAC-pain), depression (HADS), anxiety (HADS), physical function (WOMAC-function) |
| Hunt et al,38 2013 | 63 (4.3) y (cutoff, ≥50 y); 60% women |
Knee osteoarthritis, NR | 9/10 | PCST and exercise | Exercise with nondirective counseling | Posttreatment | 10 wk | Individual, in person | Pain intensity (NRS), self-efficacy (ASES), physical function (WOMAC-function), adverse events |
| Keefe et al,22 1990 | 64 (11.4) y (cutoff, NR); 73% women |
Knee osteoarthritis, 12 (10.2) y | 32/36 | Pain-coping skills training | (1) Arthritis education, (2) standard care | Posttreatment | 10 wk | Group, in person | Pain intensity (NRS), pain interference (AIMS), depression (AIMS), change in pain medication use |
| Kwok et al,39 2016 | 71.5 (NR) y (cutoff, ≥60 y); NR |
Knee, NR | 19/27 | Arthritis self-management program | Waiting list | Posttreatment, 1 mo | 6 wk | Group, in person | Self-efficacy (PSEQ-HK), physical function (SF-36PF) |
| Morone et al,40 2008 | 75 (5.5) y (cutoff, ≥65 y); 57% women |
Low back, NR | 13/17 | Mindfulness meditation | Waiting list | Posttreatment, 3 mo | 8 wk | Group, in person | Pain intensity (MPQ-SF), pain interference (RMDQ), physical health (SF-36), adverse events |
| Morone et al,41 2016 | 74.5 (6.6) y (cutoff, ≥65 y); 66.3% women |
Low back, 11.4 (13) y | 140/142 | Mindfulness-based stress reduction program | Health education program | Posttreatment, 6 mo | 34 wk | Group, in person | Pain intensity (NRS), pain interference (RMDQ), catastrophizing (PCS), self-efficacy (CPSES), physical health (PHC) |
| Nicholas et al,23,42 2013, 2017b | 73.9 (6.5) y (cutoff, ≥65 y); 68% women |
Musculoskeletal, 14.8 (17.3) y | 49/53 | Cognitive-behaviorally based pain self-management program | (1) Exercise-attention control, (2) waiting list |
Posttreatment, 1 and 6 mo, 1 y | 4 wk | Group, in person | Pain intensity (NRS), pain interference (RMDQ), depression (DASS-21), catastrophizing (PRSS), self-efficacy (PSEQ) |
| Rini et al,43 2012 | 67.5 (9.3) y (cutoff, ≥18 y); 80% women |
Osteoarthritis, NR | 57/52 | Pain-coping skills training | Assessment only | Posttreatment | 8 wk | Individual, internet | Pain intensity (AIMS2), pain interference (AIMS2), depression (PANAS), anxiety (PASS20), self-efficacy (ASES) |
| Tse et al,44 2011 | 72 (9) y (cutoff, ≥55 y); 84% women |
Musculoskeletal, NR | 39/43 | Multisensory stimulation exercise therapy | Multisensory stimulation coping therapy | Posttreatment | 6 wk | Group, in person | Pain intensity (NRS), depression (GDS), anxiety (AIS), physical function (EMS), change in pain medication use |
| Vitiello et al,26 2013 | 73 (8.2) y (cutoff, ≥60 y); 78% women |
Osteoarthritis, NR | (1) 117/122, (2) 113/122 |
(1) CBT for pain, (2) CBT for pain and insomnia | Education only | Posttreatment, 9 mo | 6 wk | Group, in person | Pain intensity (NRS) |
| Yip et al,45 2007 | 64.8 (1.0) y (cutoff, ≥50 y); 84% women |
Knee osteoarthritis, 8.0 (0.7) y | 94/88 | Arthritis self-management and exercise | Usual care | Posttreatment, 4 mo | 6 wk | Group, in person | Pain intensity (VAS), physical function (HAQ) |
Abbreviations: ACT, acceptance and commitment therapy; AIMS, Arthritis Impact Measurement Scale; AIMS2, Arthritis Impact Measurement Scale 2; AIS, Anxiety Inventory Scale; ASES, Arthritis Self-Efficacy Scale; BDI, Beck Depression Index; BPI, Brief Pain Inventory; CAT, catastrophizing thoughts; CBT, cognitive-behavioral therapy; CES-D, Center for Epidemiologic Studies Short Depression Scale; CPSES, Chronic Pain Self-Efficacy Scale; CSQ, Coping Strategies Questionnaire; DAQ, Daily Activities Questionnaire; DASS-21 Depression, Anxiety Stress Scales in 21 items; EMS, Elderly Mobility Scale; GCP, Graded Chronic Pain; GDS, Geriatric Depression Scale; HADS, Hospital Anxiety and Depression Scale; HAQ, Health Assessment Questionnaire; MPI, Multidimensional Pain Inventory; MPQ-SF, McGill Pain Questionnaire–Short Form; MVK, Modified Von Korff; NR, not reported; NRS, numerical rating scale; PANAS, Positive and Negative Affect Scale; PASS20, Pain Anxiety Symptoms Scale; PCS, Pain Catastrophizing Scale; PCST, pain coping skills training; PHC, Physical Health Composite; PRSS, Pain-Related Self-Statements Scale; PSEQ, Pain Self-Efficacy Questionnaire; PSEQ-HK, Chinese Version of Pain Self-Efficacy Questionnaire; RMDQ, Roland Morris Disability Questionnaire; SF-12, Short Form-12; SF-36, Short Form-36; SF-36 PF, SF-36 Physical Function; STAI-6, 6-item State-Trait Anxiety Inventory; SOC, selective optimization with compensation; VAS, visual analog scale; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.
Number of participants assessed or analyzed at posttreatment assessment.
Nicholas et al42 reported the long-term outcomes of their study.
For each outcome, mean and SD data were extracted for intervention and control groups at pretreatment and posttreatment, as well as for all other follow-up assessments. We categorized any assessment that took place less than 12 weeks after the completion of treatment as posttreatment. Due to study differences in the follow-up assessments, we operationalized any assessment occurring between 12 or more weeks to 24 or fewer weeks after treatment completion as a mid-term outcome, while those taking place longer than 24 weeks after treatment completion were considered long-term outcomes.
Data Extraction
Data extraction included bibliographic information, demographic characteristics of the sample and clinical characteristics when present, and data on the intervention, as well as outcome data. Two of us (B.N., R.B.) performed double data entry independently, and the resulting databases were then compared with each other. Discrepancies were resolved through consensus.
Quality Assessment and Risk of Bias
To judge the methodologic quality of the retained articles, we used the quality rating scale developed by Yates et al,46 a valid and reliable instrument designed to evaluate the quality of randomized clinical trials examining psychological interventions in individuals with chronic pain. Total scores range from 0 to 35, with higher scores indicating better methodologic quality.46 Two of us (B.N., E.K.) performed this assessment independently; discrepancies were resolved through discussion. We did not exclude any study from the analysis based on quality score but examined in moderator analyses whether the quality score affected treatment outcomes. We also assessed the risk of methodologic bias (appropriateness of randomization, allocation bias, and measurement bias) using the Yates tool.
Statistical Analysis
Meta-analyses were carried out in statistical mixed models. The dependent variables were the standardized mean differences over time for control and intervention (outcome mean differences divided by the SD of the difference). The primary model included treatment (control vs intervention), time of assessment (a repeated measure: baseline, first follow-up [treatment completion], mid-term follow-up, and long-term follow-up) as fixed classification factors, the interaction between these factors, and studies as levels of a random classification factor. An unstructured error was specified. Random effects take into account heterogeneity among studies.
The effect of the intervention on study outcomes was examined by the treatment × time interaction in this model and the treatment effect specific to each of 3 time contrasts: baseline to first follow-up (treatment completion), baseline to mid-term follow-up, and baseline to long-term follow-up. The baseline vs first follow-up contrast was the primary outcome of interest because all studies reported outcomes at this assessment. We carried out further examination of effects at the later time points by models that looked at the baseline vs first follow-up limited to the studies that provided data at later assessments.
Results are reported in terms of differences of standardized mean differences (dD) because of the numerous measurement instruments and scale ranges used by the studies for each outcome. As a guide to the magnitude of the treatment effects, we show what dD represents for several outcome scales.
Additional independent variables were examined, including study characteristics (study quality [high vs low], year of publication, and pilot study vs larger-scale randomized clinical trial), intervention characteristics (mode of treatment delivery [group vs individual]), level of therapist training (evidence that therapists had appropriate training in intervention components prior to the trial: adequate vs inadequate), treatment fidelity (adherence to the therapist manual: adequate or inadequate, mode of therapy [group vs individual], and duration of the intervention phase in weeks), and participant characteristics (pain type [musculoskeletal vs other], proportion of women in the sample, mean age of sample, and pain duration in years). Each of these variables was added to the primary model (as a fixed classification factor for categorical variables and as a covariate for quantitative variables; separate models for each variable) as well as its interaction with treatment and time. To examine whether, for example, specific study-level methodologic characteristics moderated treatment effects—whether effects were stronger for or limited to certain levels of these characteristics—the focus was on the interaction with treatment (overall and for specific time contrasts), including examination of homogeneity of regressions for the covariates.47
In this type of meta-analysis, it is clear that an assumption of studies as fixed (a single true effect size for all studies) is inappropriate. True effect sizes will vary by studies not just owing to sampling error but also to differences in sample composition (eg, age, ethnicity, and educational level), methods of assessment and study protocol, variable definitions, overall study quality, and numerous other factors. We used mixed models in which studies are assumed to be random (sampled from a population of studies). Effect sizes are assumed to differ by studies.
For the sake of completeness, we computed the Cochran Q statistic and Higgins-Thompson H2 and I2 values to examine heterogeneity across studies.48 We examined the question of publication bias by constructing a funnel plot with 1/(SE), a measure of sample size, plotted against effect size.49
Results
The database searches identified 2391 articles; 238 were selected based on title and abstract for full-text review to determine eligibility. We included 22 studies (23 publications) with a total of 2608 participants (mean [SD] age was 71.9 [7.1] years and 1799 [69.0%] were women) in the final sample (Table 2).22,23,24,25,26,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45
Participant Characteristics
Table 2 shows studies that evaluated participants with various types of chronic pain, including back pain, pain due to osteoarthritis or rheumatoid arthritis, and mixed pain types. We categorized types of chronic pain into 2 groups: musculoskeletal (17 studies) and other (5 studies). The other category included patients with rheumatoid arthritis (n = 1) and mixed pain types (n = 4). The mean (SD) pain duration was 16.1 (13.9) years.
Study Characteristics
The mean (range) length of the intervention period was 9.4 (4-35) weeks. The mean (range) number of treatment sessions was 8.4 (6-14). Fifteen studies delivered an intervention using a group-based approach, and the most common mode of treatment delivery was in person, which was used by 19 studies (Table 2).
Quality Assessment, Risk of Bias, and Heterogeneity Appraisals
eTable 2 in the Supplement presents the Yates quality scores for all 22 studies. The mean (range) quality score was 24.5 (13-33). In the Yates et al46 study, articles with a score or 22.7 or greater were deemed to have excellent methodologic quality. Twelve (55%) studies met the criterion for taking steps to minimize the possibility of measurement bias, while 10 (45%) were judged to be at low risk for allocation bias (eTable 2 in the Supplement). The funnel plot showed no clustering of studies in the lower right of the funnel that would indicate lack of publication of smaller or nonsignificant studies (eFigure 2A, B, and C in the Supplement).
The Cochran Q and I2 scores for the key variable—pain intensity—were 25.9% and 27.6%, which did not indicate a high degree of heterogeneity. Other outcomes showed similarly modest heterogeneity.
Benefits of Therapy
Six studies assessed for change in pain medication use but used different scales that precluded generation of a summary effect size.22,34,35,36,37,44 None of the studies reported any treatment-related reduction in pain medication use, including opioid use. The results of the meta-analyses appear in Table 3. Differences of standardized mean differences (dD) and corresponding P values for the outcomes at posttreatment are pain intensity (dD = −0.181, P = .006), pain interference (dD = −0.133, P = .12), depressive symptoms (dD = −0.128, P = .14), anxiety (dD = −0.205, P = .09), catastrophizing beliefs (dD = −0.184, P = .046), self-efficacy for managing pain (dD = 0.193, P = .02), physical function (dD = 0.006, P = .96), and physical health (dD = 0.160, P = .24). The dD terms reported above (for pain, catastrophizing, and self-efficacy) correspond to a baseline to posttreatment reduction in pain intensity on a 0 to 10 scale of 0.49, in catastrophizing on a 0 to 6 scale of 0.32, and an improvement in self-efficacy on a 0 to 60 scale of 4.11 points.
Table 3. Effects of Psychological Therapies on Short-, Intermediate-, and Long-term Outcomes.
| Outcome Measure | Studies Providing Results at Each Follow-up, No. | Participants, No.a | Posttreatment | Mid-term Follow-up | Long-term Follow-up | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Posttreatmentb | Follow-up | IG | CG | Effect Sizee | P Value | Effect Size | P Value | Effect Size | P Value | ||
| Mid-termc | Long-termd | ||||||||||
| Pain intensity | 21 | 12 | 4 | 1043 | 955 | −0.181 | .006 | −0.259 | .002 | 0.023 | .84 |
| Pain interference | 12 | 6 | 2 | 565 | 546 | −0.133 | .12 | −0.137 | .25 | −0.075 | .64 |
| Depressive symptoms | 12 | 6 | 3 | 565 | 482 | −0.128 | .14 | −0.087 | .46 | −0.014 | .92 |
| Anxiety | 6 | 2 | 0 | 309 | 234 | −0.205 | .09 | −0.221 | .12 | ||
| Catastrophizing | 8 | 5 | 3 | 518 | 430 | −0.184 | .046 | −0.106 | .38 | 0.070 | .63 |
| Pain self-efficacy | 10 | 4 | 2 | 626 | 534 | 0.193 | .02 | 0.170 | .19 | 0.008 | .96 |
| Physical function | 9 | 4 | 0 | 548 | 369 | 0.006 | .96 | −0.072 | .57 | ||
| Physical health | 4 | 4 | 1 | 204 | 215 | 0.160 | .24 | −0.047 | .73 | −0.250 | .45 |
Abbreviations: CG, control group; IG, intervention group.
Number of participants analyzed at treatment completion assessment.
Assessment conducted at the time of treatment completion.
Mid-term follow-up assessments occurring 12 weeks or more but 24 weeks or less following treatment completion.
Long-term follow-up assessments occurring more than 24 weeks following treatment completion.
Effect size is dD, which is the difference of standardized mean differences for treatment and control. These dD in terms of differences of standardized mean differences correspond to a baseline to posttreatment reduction for pain intensity on a 0- to 10-point scale of 0.49, a change in catastrophizing on a 0- to 6-point scale of 0.32, and a an improvement in self-efficacy on a 0- to 60-point scale of 4.11.
The treatment result for pain intensity persists up to 6 months after treatment completion (dD = −0.251, P = .002). There is no evidence of treatment results persisting in assessments conducted greater than 24 weeks after treatment completion, but this evaluation is confounded by the small number of studies with data at that assessment and the mixed results of models using only those studies in baseline vs posttreatment comparisons.
The Figure displays a forest plot showing the effect size for each study and corresponding weight given to each for pain intensity at posttreatment, the key contrast of this study. The pooled analysis indicates a significant benefit in favor of treatment relative to controls.
Figure. Examination of Effect Size for Pain Intensity: Baseline to Posttreatment Analysis.
Studies not shown are Kwok et al,39 which did not report pain intensity, and Nicholas et al,42 which reported long-term outcomes. dd indicates effect size (standardized mean differences); LCL, lower confidence limit; and UCL, upper confidence limit.
Harms of Therapy
Only 3 studies assessed for adverse events.24,25,40 Two found transient increases in pain associated with an exercise and behavioral skills training protocol,24,25 while the third reported no serious adverse events associated with a mindfulness meditation-based intervention.40
Moderator Analyses
To determine whether treatment effects differed by level of the potentially moderating variables, we examined 11 independent variables, 1 at a time, as additions to the primary model, including their interactions with treatment and time of assessment. These variables were conceptualized in 3 areas: participant characteristics, intervention characteristics, and study characteristics. Across all outcomes and possible moderators, only mode of therapy showed a coherent pattern of results. Other moderators were nonsignificant, and there were no indications of negative results for any subgroup. For the majority of outcomes, including pain intensity, treatment differences were stronger for or limited to group therapy for the baseline to postintervention comparison (for pain intensity, dD = −0.202, P = .008 for group therapy; dD = −0.120, P = .38 for individual therapy). However, this interaction was not significant for pain intensity at mid-term follow-up (P = .01 for group, P = .07 for individual). Too few studies conducted long-term follow-ups for a meaningful examination of moderation at this time point.
Discussion
Psychological therapies for individuals with chronic pain have received increased attention in the wake of the ongoing opioid epidemic in the United States.9,50 Various initiatives have been launched to address the opioid crisis, including the release of the Centers for Disease Control and Prevention opioid guidelines for patients with chronic pain.51 The Centers for Disease Control and Prevention guidelines encourage clinicians to prescribe nonpharmacologic therapies, such as CBT, for patients with chronic pain. Our results are relevant to the management of chronic pain in older adults by demonstrating that psychological interventions have salutary, albeit small, benefits for treatment of pain, catastrophizing beliefs, and self-efficacy. Mean treatment results demonstrated in the present study obscure variations at the individual patient level. Some older patients with chronic pain may receive substantial benefit through psychological therapy, while others may not benefit. There is no evidence that the beneficial results identified at the completion of treatment persisted up to 6 months for outcomes other than pain reduction. There were too few studies reporting long-term outcomes to determine completely whether this finding was due to decreased power or to a tapering of treatment benefits over time.
The observed benefits were strongest when delivered using group-based approaches. Potential mechanisms that could account for this finding include access to peer support, social facilitation of target behaviors, and public commitment to therapy goals.52 No other results of participant, intervention, or study characteristics were found. Treatment benefits were equally likely to occur in older men and women irrespective of age and duration of chronic pain.
Our results add to the existing literature by demonstrating that older adults—an understudied population with respect to the benefits of psychological therapies for chronic pain15,16—can benefit from these treatment approaches. Our findings are similar to those reported in the Cochrane review,10 which demonstrated that, among nonelderly adults with chronic pain, CBT has a small effect on pain at posttreatment. Unlike the present study, the effect documented in the Cochrane review did not persist at 6 months. Our findings of a small benefit with respect to pain mitigation are also similar to those of a recent report evaluating psychological therapies for nonelderly adults with low back pain.53
Limitations
Our study has several limitations that warrant consideration. Our search was limited to English-language studies, which may have eliminated otherwise eligible trials. In addition, trials with negative results may fail to report full outcome data but report only that there was no significant difference in outcomes analyzed. However, only 1 study was excluded from our sample for this reason. Other factors limiting the generalizability of our findings include a lack of diversity in study populations (eg, focus on white individuals and young-old populations). Furthermore, the intensity of the interventions did not vary greatly, making it difficult to discern whether differences in treatment dose affect outcomes. Finally, few studies evaluated outcomes more than 6 months after treatment completion, so the long-term effects of these approaches remain poorly understood.
Implications for Practice
Our findings support guideline recommendations54,55 that encourage clinicians to consider psychological treatments in the care of older patients with chronic pain, particularly those delivered using a group-based approach. Clinicians should learn and share with patients basic information about psychological approaches to managing pain. Inquiring about patients’ treatment expectations, including perceived benefits and potential harms, is also important.1 Leveraging social supports to encourage patients’ continued use of psychological techniques (eg, distraction, relaxation techniques) over time is also warranted.1 Finally, management of chronic pain in older adults should be multimodal, including use of both pharmacologic and nonpharmacologic approaches.54,55,56,57 Physical treatments in the form of exercise and other movement-based approaches have demonstrated benefits in the form of reduced pain and improved functioning, are safe to use in older adults, and should also be considered.54,55,56,57,58,59,60
Implications for Research
Research is needed to better understand the mechanisms responsible for the effects of psychological therapies on chronic pain and ways to augment these effects. Although our results indicate that group-based vs individually delivered approaches produce superior outcomes, we still do not know which components of psychological therapies are most efficacious and in which subgroups of older adults. Research is also needed to determine what influences these approaches have on older adults’ use of pain medications, particularly opioids, and to ascertain any harms associated with their use. In addition, research is necessary to ascertain whether factors such as degree of cognitive impairment, race/ethnicity status, and level of support to adopt and use psychological techniques moderate treatment outcomes and, if so, to what degree. Further research should also explore whether treatment effects can be enhanced and sustained by leveraging research findings in the areas of temporal horizons61 and age-related changes in emotional and cognitive processing.62,63 Prior findings indicate that older adults prioritize well-being in the present moment,64 which may make them reluctant to engage in long-term treatment programs, and they are more likely to process information if it is presented in a positive frame.65 These insights could be leveraged by emphasizing the immediate benefits of an intervention (eg, social engagement in a group setting) and crafting positively framed feedback messages to promote long-term adherence.66 Finally, more research is needed regarding the role of mobile health technologies as tools to help deliver treatments and whether these devices can enhance adherence to the psychological techniques over time.67
Conclusions
Psychological interventions for the treatment of chronic pain in older adults have beneficial, albeit small, associations with pain and catastrophizing as well as self-efficacy for managing pain. These benefits, documented at the completion of treatment, were found to persist up to 6 months later only for pain intensity reduction. Efforts are therefore needed to develop and test psychological interventions that generate more robust treatment effects that are sustainable in this growing population of patients.
eTable 1. Search Strategies For Ovid MEDLINE in-Process & Other Non-Indexed Citations and Ovid MEDLINE
eTable 2. Yates Quality Rating Scale of Analyzed Studies
eFigure 1. Flow Diagram of the Study Selection Process
eFigure 2A. Forest Plot for Pain Intensity
eFigure 2B. Forest Plot for Catastrophizing
eFigure 2C. Forest Plot for Pain Self-Efficacy
References
- 1.Makris UE, Abrams RC, Gurland B, Reid MC. Management of persistent pain in the older patient: a clinical review. JAMA. 2014;312(8):825-836. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Patel KV, Guralnik JM, Dansie EJ, Turk DC. Prevalence and impact of pain among older adults in the United States: findings from the 2011 National Health and Aging Trends Study. Pain. 2013;154(12):2649-2657. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain. 2012;13(8):715-724. [DOI] [PubMed] [Google Scholar]
- 4.Savvas SM, Gibson SJ. Overview of pain management in older adults. Clin Geriatr Med. 2016;32(4):635-650. [DOI] [PubMed] [Google Scholar]
- 5.Reid MC, Eccleston C, Pillemer K. Management of chronic pain in older adults. BMJ. 2015;350:h532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Rastogi R, Meek BD. Management of chronic pain in elderly, frail patients: finding a suitable, personalized method of control. Clin Interv Aging. 2013;8:37-46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Spitz A, Moore AA, Papaleontiou M, Granieri E, Turner BJ, Reid MC. Primary care providers’ perspective on prescribing opioids to older adults with chronic non-cancer pain: a qualitative study. BMC Geriatr. 2011;11:35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.O’Neil CK, Hanlon JT, Marcum ZA. Adverse effects of analgesics commonly used by older adults with osteoarthritis: focus on non-opioid and opioid analgesics. Am J Geriatr Pharmacother. 2012;10(6):331-342. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Nelson LS, Juurlink DN, Perrone J. Addressing the opioid epidemic. JAMA. 2015;314(14):1453-1454. [DOI] [PubMed] [Google Scholar]
- 10.Williams AC, Eccleston C, Morley S. Psychological therapies for the management of chronic pain (excluding headache) in adults. Cochrane Database Syst Rev. 2012;11(11):CD007407. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lunde LH, Nordhus IH, Pallesen S. The effectiveness of cognitive and behavioural treatment of chronic pain in the elderly: a quantitative review. J Clin Psychol Med Settings. 2009;16(3):254-262. [DOI] [PubMed] [Google Scholar]
- 12.Committee on Advancing Pain Research Care and Education Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research. 2nd ed. Washington, DC: National Academies Press; 2011. [PubMed] [Google Scholar]
- 13.Schneiderhan J, Clauw D, Schwenk TL. Primary care of patients with chronic pain. JAMA. 2017;317(23):2367-2368. [DOI] [PubMed] [Google Scholar]
- 14.Kerns RD, Sellinger J, Goodin BR. Psychological treatment of chronic pain. Annu Rev Clin Psychol. 2011;7:411-434. [DOI] [PubMed] [Google Scholar]
- 15.McGuire BE, Nicholas MK, Asghari A, Wood BM, Main CJ. The effectiveness of psychological treatments for chronic pain in older adults: cautious optimism and an agenda for research. Curr Opin Psychiatry. 2014;27(5):380-384. [DOI] [PubMed] [Google Scholar]
- 16.Ehde DM, Dillworth TM, Turner JA. Cognitive-behavioral therapy for individuals with chronic pain: efficacy, innovations, and directions for research. Am Psychol. 2014;69(2):153-166. [DOI] [PubMed] [Google Scholar]
- 17.Sturgeon JA. Psychological therapies for the management of chronic pain. Psychol Res Behav Manag. 2014;7:115-124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hofmann SG, Sawyer AT, Fang A. The empirical status of the “new wave” of cognitive behavioral therapy. Psychiatr Clin North Am. 2010;33(3):701-710. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Yu L, McCracken LM. Model and processes of acceptance and commitment therapy (ACT) for chronic pain including a closer look at the self. Curr Pain Headache Rep. 2016;20(2):12. [DOI] [PubMed] [Google Scholar]
- 20.Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6(7):e1000100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.BMJ Clinical Evidence Study design search filters. http://clinicalevidence.bmj.com/x/set/static/ebm/learn/665076.html. Updated September 20, 2012. Accessed August 23, 2017.
- 22.Keefe FJ, Caldwell DS, Williams DA, et al. Pain coping skills training in the management of osteoarthritic knee pain: a comparative study. Behav Ther. 1990;21:49-62. [Google Scholar]
- 23.Nicholas MK, Asghari A, Blyth FM, et al. Self-management intervention for chronic pain in older adults: a randomised controlled trial. Pain. 2013;154(6):824-835. [DOI] [PubMed] [Google Scholar]
- 24.Bennell KL, Ahamed Y, Jull G, et al. Physical therapist–delivered pain coping skills training and exercise for knee osteoarthritis: randomized controlled trial. Arthritis Care Res (Hoboken). 2016;68(5):590-602. [DOI] [PubMed] [Google Scholar]
- 25.Hurley MV, Walsh NE, Mitchell HL, et al. Clinical effectiveness of a rehabilitation program integrating exercise, self-management, and active coping strategies for chronic knee pain: a cluster randomized trial. Arthritis Rheum. 2007;57(7):1211-1219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Vitiello MV, McCurry SM, Shortreed SM, et al. Cognitive-behavioral treatment for comorbid insomnia and osteoarthritis pain in primary care: the lifestyles randomized controlled trial. J Am Geriatr Soc. 2013;61(6):947-956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Dworkin RH, Turk DC, Farrar JT, et al. ; IMMPACT . Core outcome measures for chronic pain clinical trials: IMMPACT recommendations. Pain. 2005;113(1-2):9-19. [DOI] [PubMed] [Google Scholar]
- 28.Alonso-Fernández M, López-López A, Losada A, González JL, Wetherell JL. Acceptance and commitment therapy and selective optimization with compensation for Institutionalized older people with chronic pain. Pain Med. 2016;17(2):264-277. [DOI] [PubMed] [Google Scholar]
- 29.Andersson G, Johansson C, Nordlander A, Asmundson GJ. Chronic pain in older adults: a controlled pilot trial of a brief cognitive-behavioural group treatment. Behav Cogn Psychother. 2012;40(2):239-244. [DOI] [PubMed] [Google Scholar]
- 30.Appelbaum KA, Blanchard EB, Hickling EJ, Alfonso M. Cognitive behavioral treatment of a veteran population with moderate to severe rheumatoid arthritis. Behav Ther. 1988;19(4):489-502. [Google Scholar]
- 31.Berman RL, Iris MA, Bode R, Drengenberg C. The effectiveness of an online mind-body intervention for older adults with chronic pain. J Pain. 2009;10(1):68-79. [DOI] [PubMed] [Google Scholar]
- 32.Carmody TP, Duncan CL, Huggins J, et al. Telephone-delivered cognitive-behavioral therapy for pain management among older military veterans: a randomized trial. Psychol Serv. 2013;10(3):265-275. [DOI] [PubMed] [Google Scholar]
- 33.Cederbom S, Denison E, Bergland A. A behavioral medicine intervention for community-dwelling older adults with chronic musculoskeletal pain: protocol for a randomized controlled trial. J Pain Res. 2017;10:845-853. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Cook AJ. Cognitive-behavioral pain management for elderly nursing home residents. J Gerontol B Psychol Sci Soc Sci. 1998;53(1):51-59. [DOI] [PubMed] [Google Scholar]
- 35.Ersek M, Turner JA, McCurry SM, Gibbons L, Kraybill BM. Efficacy of a self-management group intervention for elderly persons with chronic pain. Clin J Pain. 2003;19(3):156-167. [DOI] [PubMed] [Google Scholar]
- 36.Ersek M, Turner JA, Cain KC, Kemp CA. Results of a randomized controlled trial to examine the efficacy of a chronic pain self-management group for older adults [ISRCTN11899548]. Pain. 2008;138(1):29-40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Haas M, Groupp E, Muench J, et al. Chronic disease self-management program for low back pain in the elderly. J Manipulative Physiol Ther. 2005;28(4):228-237. [DOI] [PubMed] [Google Scholar]
- 38.Hunt MA, Keefe FJ, Bryant C, et al. A physiotherapist-delivered, combined exercise and pain coping skills training intervention for individuals with knee osteoarthritis: a pilot study. Knee. 2013;20(2):106-112. [DOI] [PubMed] [Google Scholar]
- 39.Kwok EYT, Au RKC, Li-Tsang CWP. The effect of a self-management program on the quality-of-life of community-dwelling older adults with chronic musculoskeletal knee pain: a pilot randomized controlled trial. Clin Gerontol. 2016;39(5):428-448. [DOI] [PubMed] [Google Scholar]
- 40.Morone NE, Greco CM, Weiner DK. Mindfulness meditation for the treatment of chronic low back pain in older adults: a randomized controlled pilot study. Pain. 2008;134(3):310-319. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Morone NE, Greco CM, Moore CG, et al. A mind-body program for older adults with chronic low back pain: a randomized clinical trial. JAMA Intern Med. 2016;176(3):329-337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Nicholas MK, Asghari A, Blyth FM, et al. Long-term outcomes from training in self-management of chronic pain in an elderly population: a randomized controlled trial. Pain. 2017;158(1):86-95. [DOI] [PubMed] [Google Scholar]
- 43.Rini C, Williams DA, Broderick JE, Keefe FJ. Meeting them where they are: using the internet to deliver behavioral medicine interventions for pain. Transl Behav Med. 2012;2(1):82-92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Tse MM, Au EYM, Wong AMH. Total pain concept: multisensory stimulation, exercise therapy and coping skill training for community-dwelling older persons with chronic pain. J Pain Manage. 2011;4(4):403-416.23279630 [Google Scholar]
- 45.Yip YB, Sit JW, Fung KK, et al. Impact of an Arthritis Self-Management Programme with an added exercise component for osteoarthritic knee sufferers on improving pain, functional outcomes, and use of health care services: an experimental study. Patient Educ Couns. 2007;65(1):113-121. [DOI] [PubMed] [Google Scholar]
- 46.Yates SL, Morley S, Eccleston C, de C Williams AC. A scale for rating the quality of psychological trials for pain. Pain. 2005;117(3):314-325. [DOI] [PubMed] [Google Scholar]
- 47.Henderson CR., Jr Analysis of covariance in the mixed model: higher-level, nonhomogeneous, and random regressions. Biometrics. 1982;38(3):623-640. [PubMed] [Google Scholar]
- 48.DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177-188. [DOI] [PubMed] [Google Scholar]
- 49.Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629-634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.National Academies of Sciences, Engineering, and Medicine. Pain Management and the Opioid Epidemic: Balancing Societal and Individual Benefits and Risks of Prescription Opioid Use. Washington, DC: National Academies Press; 2017. [PubMed] [Google Scholar]
- 51.Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain—United States, 2016. JAMA. 2016;315(15):1624-1645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Fraser SN, Spink KS. Examining the role of social support and group cohesion in exercise compliance. J Behav Med. 2002;25(3):233-249. [DOI] [PubMed] [Google Scholar]
- 53.Chou R, Deyo R, Friedly J, et al. Nonpharmacologic therapies for low back pain: a systematic review for an American College of Physicians clinical practice guideline. Ann Intern Med. 2017;166(7):493-505. [DOI] [PubMed] [Google Scholar]
- 54.American Geriatrics Society Panel on Pharmacological Management of Persistent Pain in Older Persons Pharmacological management of persistent pain in older persons. J Am Geriatr Soc. 2009;57(8):1331-1346. [DOI] [PubMed] [Google Scholar]
- 55.Abdulla A, Adams N, Bone M, et al. ; British Geriatric Society . Guidance on the management of pain in older people. Age Ageing. 2013;42(suppl 1):i1-i57. [DOI] [PubMed] [Google Scholar]
- 56.Bennell KL, Hinman RS. A review of the clinical evidence for exercise in osteoarthritis of the hip and knee. J Sci Med Sport. 2011;14(1):4-9. [DOI] [PubMed] [Google Scholar]
- 57.Becker WC, Dorflinger L, Edmond SN, Islam L, Heapy AA, Fraenkel L. Barriers and facilitators to use of non-pharmacological treatments in chronic pain. BMC Fam Pract. 2017;18(1):41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Tse MM, Wan VT, Ho SS. Physical exercise: does it help in relieving pain and increasing mobility among older adults with chronic pain? J Clin Nurs. 2011;20(5-6):635-644. [DOI] [PubMed] [Google Scholar]
- 59.Hall A, Copsey B, Richmond H, et al. Effectiveness of tai chi for chronic musculoskeletal pain conditions: updated systematic review and meta-analysis. Phys Ther. 2017;97(2):227-238. [DOI] [PubMed] [Google Scholar]
- 60.Cheung C, Wyman JF, Bronas U, McCarthy T, Rudser K, Mathiason MA. Managing knee osteoarthritis with yoga or aerobic/strengthening exercise programs in older adults: a pilot randomized controlled trial. Rheumatol Int. 2017;37(3):389-398. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Löckenhoff CE, Rutt JL. Age differences in self-continuity: converging evidence and directions for future research. Gerontologist. 2017;57(3):396-408. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Mikels JA, Reed AE, Hardy LN, Loeckenhoff CE. Positive emotions across the adult life span In: Tugade MM, Shiota MN, Kirby LD, eds. Handbook of Positive Emotions. New York: Guilford Press; 2014:256-272. [Google Scholar]
- 63.Salthouse TA. Theoretical Perspectives on Cognitive Aging. New York: Routledge; 1991. [Google Scholar]
- 64.Carstensen LL. The influence of a sense of time on human development. Science. 2006;312(5782):1913-1915. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Reed AE, Carstensen LL. The theory behind the age-related positivity effect. Front Psychol. 2012;3:339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Notthoff N, Carstensen LL. Positive messaging promotes walking in older adults. Psychol Aging. 2014;29(2):329-341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Parker SJ, Jessel S, Richardson JE, Reid MC. Older adults are mobile too! identifying the barriers and facilitators to older adults’ use of mHealth for pain management. BMC Geriatr. 2013;13(1):43. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. Search Strategies For Ovid MEDLINE in-Process & Other Non-Indexed Citations and Ovid MEDLINE
eTable 2. Yates Quality Rating Scale of Analyzed Studies
eFigure 1. Flow Diagram of the Study Selection Process
eFigure 2A. Forest Plot for Pain Intensity
eFigure 2B. Forest Plot for Catastrophizing
eFigure 2C. Forest Plot for Pain Self-Efficacy

