A mobile health + health coaching application for the management of chronic non-cancer pain in older adults: Results from a pilot randomized controlled study

Abstract

IntroductionThe rapid growth of mobile health (mHealth) devices holds substantial potential for improving care and care outcomes in aging adults with chronic non-cancer pain (CNCP), however, research evaluating these devices in older adults remains limited.ObjectiveTo ascertain the feasibility and preliminary efficacy of an mHealth intervention (Mymee) that combines symptom, diet, and behavior tracking via a smartphone application with data analytics to detect associations between symptoms and lifestyle factors along with weekly health coaching sessions to mitigate CNCP in adults 55 years of age and older.MethodsParticipants (N = 31) in this pilot study were recruited from one primary care practice in New York City and randomized to an intervention [app + up to 12 health coaching sessions (scheduled approximately once weekly) + usual care] or a control (app + usual care) arm. Feasibility measures included recruitment (proportion of eligible persons who enrolled) and retention rates (proportion of subjects completing a follow-up assessment) as well as adherence with the weekly coaching sessions and logging daily data on the app. Efficacy outcomes (e.g., pain intensity, self-efficacy, disability, anxiety) were assessed at baseline and follow-up (~16 weeks after baseline). Descriptive statistics were obtained and general linear mixed models used for primary analyses.ResultsParticipants had a mean (standard deviation) age of 67.32 (9.17) and were mostly female (61%). Feasibility outcomes were mixed as evidenced by recruitment and retention rates of 74% and 65%, respectively. The mean number of weekly coaching sessions attended by intervention participants was 6.05 (SD = 5.35), while the average number of days logging data on the app was 44.82 (34.02). We found a consistent trend in favor of the intervention, where pain intensity, affect, and quality of life measures improved considerably more among intervention (vs. control) participants. Finally, the proportion of participants with GAD-7 scores at follow up decreased by 0.35 to 0, whereas controls did not change, a significant effect in favor of the intervention (p = 0.02).ConclusionsThis study supports the need for future research that seeks to enhance feasibility outcomes and confirm the efficacy of the Mymee intervention among aging adults with CNCP.

Older Adults’ Pain Outcomes After mHealth Interventions: Scoping Review

“…In total, 4 of the selected studies were conducted in the United States, 1 study was conducted in Sweden, and 1 in the United Kingdom. The study designs varied; 2 studies were randomized controlled trials [ 48 , 49 ]. Other designs included a mixed methods exploratory within-subject pre- and posttest study [ 50 ], longitudinal cohort study [ 51 ], a phased randomized wait list control trial [ 52 ], and a randomized noninferiority comparative effectiveness trial [ 53 ].…”

“…The study participants’ clinical pain diagnoses included those commonly associated with chronic musculoskeletal pain. Pain and corresponding diagnoses included knee or hip pain from osteoarthritis [ 48 , 51 ], back pain [ 53 ], multiple pain locations [ 52 ], musculoskeletal and neurological pain [ 50 ], and chronic noncancer pain [ 49 ].…”

“…In 3 studies, a smartphone or tablet were used to deliver a downloaded software app or stream content as an mHealth intervention [ 48 , 49 , 51 ]. Another study incorporated a wrist-worn activity monitor with a software app delivered using a smartphone or tablet [ 52 ].…”

“…By contrast, in another study [ 52 ], an initial phase of the intervention included group sessions led by interventionists. In 4 studies, telephone access to an interventionist was offered [ 48 , 49 , 51 , 53 ].…”

“…Behavioral activities included the daily entry of pain symptoms, diet, and behavior tracking. Older adults received weekly health telecoaching sessions with tailoring of lifestyle adjustments to manage pain symptoms [ 49 ]. One study used cognitive behavioral therapy delivered by artificial intelligence, and the intervention incorporated daily interactive voice feedback [ 53 ].…”