(PS6-A19) Patient Engagement with a Mobile App for Chronic Pain

The COVID-19 pandemic and associated physical distancing mitigation measures have highlighted the need for mobile health technology in the treatment of chronic pain and other medical and mental health conditions. Using self-monitoring tools, self-care skill support, and pain education materials, mobile apps for the management of chronic pain have been associated with lower levels of pain, reduction in anxiety and pain catastrophizing, and high levels of patient satisfaction. However, it is unclear which factors predict engagement with and efficacy of pain apps. This study examined engagement with a smart-phone app for pain management developed at an academic medical center. The mobile-app includes a daily assessment feature (assessing pain levels, pain interference, depression, and anxiety), a self-management reminder feature (reminders for meals, exercise, sleep, medication), pain education resources, meditation and breathing audio recordings, and a two-way messaging system to connect with providers. Data were collected from three different studies which utilized the app between February 2015 and May 2018, and participants (N=319) included patients with non-cancer related chronic pain (72% female; Mean age= 51; SD= 13.67, 84% white identifying). Person-centered analyses were conducted to explore characteristics of individuals who utilized the pain app in relation to their engagement and to identify meaningful groups in the data. Engagement with the mobile app was operationalized via two indicators: 1) number of messages sent to a provider and 2) number of assessments completed via the daily assessment feature. A K-Means cluster analysis was utilized to classify the individuals based on these two engagement factors as well as age, duration of their pain problem, pain intensity, daily activity levels, and self-reported depression.  A two-cluster solution emerged from the data; Cluster 1 (n=248) constituted 78% of the sample while Cluster 2 (n=71) constituted 22% of the total sample. F statistics indicated that the number of daily assessment entries, duration of pain problem, and age were most important in determining cluster membership. Cluster 1 was found to have completed more daily assessment entries (i.e., greater app engagement; F=7.47, p< .05), and was found to be younger (F= .29, p< .01) and have a shorter duration of their pain as compared to Cluster 2 (F=708.94, p< .001). Chi-Square analyses indicated there was not systematic variation in cluster membership based on gender, ethnicity, or reported pain site. Findings suggest potential differences among individuals marked by higher levels of engagement with the pain app. Results contribute to a growing literature examining access and utilization of mobile health technology across clinical populations and may suggest additional intervention or engagement strategies are needed for older patients and those with longer duration of pain symptoms. The COVID-19 pandemic has highlighted the need to enhance our understanding of factors that predict engagement with remote health technologies to inform more effective telehealth approaches for the treatment of a range of mental health symptoms.