Internet‐Based Pain Self‐Management for Veterans: Feasibility and Preliminary Efficacy of the Pain EASE Program

ObjectiveTo develop and test the feasibility and preliminary efficacy of a cognitive behavioral therapy–based, internet‐delivered self‐management program for chronic low back pain (cLBP) in veterans.MethodsPhase I included program development, involving expert panel and participant feedback. Phase II was a single‐arm feasibility and preliminary efficacy study of the Pain e‐health for Activity, Skills, and Education (Pain EASE) program. Feasibility (ie, website use, treatment credibility, satisfaction) was measured using descriptive methods. Mixed models were used to assess mean within‐subject changes from baseline to 10 weeks post‐baseline in pain interference (primary outcome, West Haven‐Yale Multidimensional Pain Inventory, scale of 0 to 6), pain intensity, mood, fatigue, sleep, and depression.ResultsPhase I participants (n = 15) suggested modifications including style changes, content reduction, additional “Test Your Knowledge” quizzes, and cognitive behavioral therapy skill practice monitoring form revisions for enhanced usability. In Phase II, participants (n = 58) were mostly male (93%) and White (60%), and had an average age of 55 years (standard deviation [SD] = 12) and moderate pain (mean score 5.9/10); 41 (71%) completed the post‐baseline assessment. Participants (N = 58) logged on 6.1 (SD = 8.6) times over 10 weeks, and 85% reported being very or moderately satisfied with Pain EASE. Pain interference improved from a mean of 3.8 at baseline to 3.3 at 10 weeks (difference 0.5 [95% confidence interval 0.1 to 0.9], P = 0.008). Within‐subject improvement also occurred for some secondary outcomes, including mood and depression symptoms.DiscussionVeterans with cLBP may benefit from technology‐delivered interventions, which may also reduce pain interference. Overall, veterans found that Pain EASE, an internet‐based self‐management program, is feasible and satisfactory for cLBP.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154929/1/papr12861.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154929/2/papr12861_am.pd

Predictors of engagement in an internet-based cognitive behavioral therapy program for veterans with chronic low back pain

Internet-based interventions for chronic pain have demonstrated efficacy and may address access barriers to care. Participant characteristics have been shown to affect engagement with these programs; however, limited information is available about the relationship between participant characteristics and engagement with internet-based programs for self-management of chronic pain. The current study examined relationships between demographic and clinical characteristics and engagement with the Pain EASE program, a self-directed, internet-based cognitive behavioral therapy intervention for veterans with chronic low back pain (cLBP). Veterans with cLBP were enrolled in a 10 week trial of the Pain EASE program. Engagement measures included the number of logins, access to coping skill modules, and completed study staff-initiated weekly check-in calls. Regression analyses were conducted to identify significant predictors of engagement from hypothesized predictors (e.g., race/ethnicity, age, depressive symptom severity, and pain interference). Participants (N = 58) were 93% male, 60.3% identified as White, and had a mean age of 54.5 years. Participants logged into the program a median of 3.5 times, accessed a median of 2 skill modules, and attended a median of 6 check-in calls. Quantile regression revealed that, at the 50th percentile, non-White-identified participants accessed fewer modules than White-identified participants (p = .019). Increased age was associated with increased module use (p = .001). No clinical characteristics were significantly associated with engagement measures. White-identified race/ethnicity and increased age were associated with greater engagement with the Pain EASE program. Results highlight the importance of defining and increasing engagement in internet-delivered pain care