Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews

Ashley Polhemus; Sara Simblett; Erin Dawe-Lane; Gina Gilpin; Benjamin Elliott; Sagar Jilka; Jan Novak; Raluca Ileana Nica; Gergely Temesi; Til Wykes

doi:10.2196/40133

Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews

JMIR Hum Factors. 2022 Nov 23;9(4):e40133. doi: 10.2196/40133.

Authors

Ashley Polhemus^{1

2}, Sara Simblett³, Erin Dawe-Lane³, Gina Gilpin³, Benjamin Elliott³, Sagar Jilka^{3

4}, Jan Novak¹, Raluca Ileana Nica⁵, Gergely Temesi¹, Til Wykes^{3

6}

Affiliations

¹ Merck Research Labs Information Technology, Merck, Sharpe, & Dohme, Zurich, Switzerland.
² Epidemiology Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
³ Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
⁴ Division of Mental Health & Wellbeing, Warwick Medical School, University of Warwick, Coventry, United Kingdom.
⁵ RADAR-CNS Patient Advisory Board, King's College London, London, United Kingdom.
⁶ South London and Maudsley NHS Foundation Trust, London, United Kingdom.

PMID: 36416875
PMCID: PMC9730209
DOI: 10.2196/40133

Abstract

Background: Tracking and visualizing health data using mobile apps can be an effective self-management strategy for mental health conditions. However, little evidence is available to guide the design of mental health-tracking mechanisms.

Objective: The aim of this study was to analyze the content of user reviews of depression self-management apps to guide the design of data tracking and visualization mechanisms for future apps.

Methods: We systematically reviewed depression self-management apps on Google Play and iOS App stores. English-language reviews of eligible apps published between January 1, 2018, and December 31, 2021, were extracted from the app stores. Reviews that referenced health tracking and data visualization were included in sentiment and qualitative framework analyses.

Results: The search identified 130 unique apps, 26 (20%) of which were eligible for inclusion. We included 783 reviews in the framework analysis, revealing 3 themes. Impact of app-based mental health tracking described how apps increased reviewers' self-awareness and ultimately enabled condition self-management. The theme designing impactful mental health-tracking apps described reviewers' feedback and requests for app features during data reporting, review, and visualization. It also described the desire for customization and contexts that moderated reviewer preference. Finally, implementing impactful mental health-tracking apps described considerations for integrating apps into a larger health ecosystem, as well as the influence of paywalls and technical issues on mental health tracking.

Conclusions: App-based mental health tracking supports depression self-management when features align with users' individual needs and goals. Heterogeneous needs and preferences raise the need for flexibility in app design, posing challenges for app developers. Further research should prioritize the features based on their importance and impact on users.

Keywords: data visualization; depression; health tracking; mental health; mobile phone; self-management.

©Ashley Polhemus, Sara Simblett, Erin Dawe-Lane, Gina Gilpin, Benjamin Elliott, Sagar Jilka, Jan Novak, Raluca Ileana Nica, Gergely Temesi, Til Wykes. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 23.11.2022.