JMIR Publications

ABSTRACT

Background:

Digital tools for tracking health and health-related behaviours are increasingly available and helpful to individuals managing chronic conditions, including pain. Despite the growing use and observed benefits of mHealth, sustained engagement is an issue. Little is known about users of widely adopted apps such as ManageMyPain (MMP). User characteristics and engagement with MMP were assessed in 2017, however, improvements to the app and the broader digital health landscape warrant an updated investigation.

Objective:

To investigate the relationship between MMP app engagement and user characteristics including sociodemographic variables and pain-related factors to understand how reach and clinical impact can be maximized for individuals living with pain.

Methods:

Machine learning techniques were used to cluster MMP user profiles into 5 distinct engagement groups based on longevity, number of records, and frequency of app use. Differences among clusters were assessed using Chi-square tests, ANOVAs, and logistic regression as appropriate. Secondary analyses assessed interactions with gender for each cluster.

Results:

A total of N=86,429 app users consented to have their data used for research purposes. Gender differences for all engagement groups emerged (p<.001), with a higher proportion of male users in the most engaged group. Statistically significant differences emerged for all variables investigated including age, number of pain conditions, number of medications, average pain severity, daily reflection score, and pain volatility (all p<.001). Cluster membership significantly predicted cannabinoid use, with all other clusters having significantly lower odds of use than the high longevity, high engagement cluster (all p<.001). High longevity cluster membership predicted opioid medication use, with other clusters having significantly lower odds (all p<.001). Self-reported depression was more likely to be reported by users with higher longevity (all p≤.001), less likely to be reported by males (p=.024), and more likely reported by older app users (p<.001). Anxiety showed increased odds of being reported by higher longevity and higher engagement clusters (both p<.001), those who reported their gender as other (p<.001), those with higher pain severity (p<.001), and younger app users (p=.002), and had lower odds of being reported by males (p<.001). Comorbid depression and anxiety had reduced odds in the lower longevity clusters (all p≤.004), and for males (p<.001), and increased odds for those who reported their gender as other (p<.001) and those who reported higher mean pain severity (p<.001).

Conclusions:

Results demonstrate that different dimensions of engagement capture distinct aspects of the pain experience and may represent varied unmet needs. Our findings indicate potential opportunities to develop tailored digital interventions to support differing pain self-management needs and bolster engagement among those with lower involvement. Effective digital interventions could address some of the gaps in care that exist for individuals living with pain, improving access, communication, reducing inequities, and providing self-care support.