Qualitative Analysis of User Experiences of a mHealth Self-Care Intervention for Care Partners of Individuals with Traumatic Brain Injury.

OBJECTIVE

To identify challenges and solutions for conducting mobile health (mHealth) research in a rehabilitation care partner population that involved personalized self-care push notifications and self-monitoring data collection.

DESIGN

Qualitative semistructured debriefing interviews with participants who completed a 6-month app-based self-care intervention involving self-monitoring alone or self-monitoring plus personalized push notifications. Interviews were guided by a data-prompted approach to aid participants' recall.

SETTING

Two academic medical centers.

PARTICIPANTS

Thirty-six care partners (N=36) of individuals with complicated mild to severe traumatic brain injury requiring assistance with daily activities.

INTERVENTIONS: The CareQOL app is a mHealth intervention that delivers personalized self-care push notifications based on daily self-monitoring data, including self-reported caregiver strain, depression, and anxiety, plus Fitbit-tracked sleep and step data.

MAIN OUTCOME MEASURES: Qualitative interview data about participants' experiences with, impressions of, and suggestions for the CareQOL app: (1) self-monitoring components (ie, daily questions, health data dashboard); (2) personalized self-care notifications, including overall experience and perceptions of selected messages.

RESULTS

Deductive thematic analysis was used to uncover participants' experiences with the CareQOL app and identify considerations across intervention and study design. Intervention-wise, push notifications personalized solely based on passive sensing and self-report can be misaligned with participants' needs, reducing support relevance; limited contextual cues in dashboard displays constrained meaningful self-reflection. Study-wise, technical breakdowns disrupted engagement during the extended study duration; data-prompted interviews effectively supported recall, with participant preferences informing methodological considerations.

CONCLUSIONS

Findings identified critical considerations and practical recommendations for designing personalized mHealth interventions for self-care and evaluating them in longitudinal randomized controlled trials.