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

TY - JOUR

T1 - Health Tracking via Mobile Apps for Depression Self-management

T2 - Qualitative Content Analysis of User Reviews

AU - Polhemus, Ashley

AU - Simblett, Sara

AU - Dawe-Lane, Erin

AU - Gilpin, Gina

AU - Elliott, Benjamin

AU - Jilka, Sagar

AU - Novak, Jan

AU - Nica, Raluca Ileana

AU - Temesi, Gergely

AU - Wykes, Til

N1 - Funding Information: This study was written in support of the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program, a collaborative research effort focusing on the development of remote monitoring technology for monitoring central nervous system disease progression. We acknowledge all partners in the RADAR-CNS consortium [66] for their input and support in this work. The RADAR-CNS project received funding from the Innovative Medicines Initiative 2 Joint Undertaking [67] under grant agreement 115902. This joint undertaking receives support from the European Union’s Horizon 2020 Research and Innovation Program and European Federation of Pharmaceutical Industries and Associations [67]. This communication reflects the views of the RADAR-CNS consortium, and neither the Innovative Medicines Initiative nor the European Union and European Federation of Pharmaceutical Industries and Associations are liable for any use that may be made of the information contained herein. This paper represents an independent research funded by the National Institute for Health Research Biomedical Research Centre in South London and Maudsley National Health Services Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the National Health Services, National Institute for Health Research, or Department of Health and Social Care. TW is a National Institute of Health Research senior investigator. Publisher Copyright: ©Ashley Polhemus, Sara Simblett, Erin Dawe-Lane, Gina Gilpin, Benjamin Elliott, Sagar Jilka, Jan Novak, Raluca Ileana Nica, Gergely Temesi, Til Wykes.

PY - 2022/10

Y1 - 2022/10

N2 - 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.

AB - 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.

KW - data visualization

KW - depression

KW - health tracking

KW - mental health

KW - mobile phone

KW - self-management

UR - http://www.scopus.com/inward/record.url?scp=85144074340&partnerID=8YFLogxK

U2 - 10.2196/40133

DO - 10.2196/40133

M3 - Article

AN - SCOPUS:85144074340

SN - 2292-9495

VL - 9

JO - JMIR Human Factors

JF - JMIR Human Factors

IS - 4

M1 - e40133

ER -