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User Perspectives of Mood-Monitoring Apps Available to Young People: Qualitative Content Analysis

Research output: Contribution to journalArticle

Original languageEnglish
Article numbere18140
Pages (from-to)e18140
JournalJMIR mHealth and uHealth
Volume8
Issue number10
DOIs
Published10 Oct 2020

Bibliographical note

©Emily Widnall, Claire Ellen Grant, Tao Wang, Lauren Cross, Sumithra Velupillai, Angus Roberts, Robert Stewart, Emily Simonoff, Johnny Downs. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 10.10.2020.

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King's Authors

Abstract

BACKGROUND: Mobile health apps are increasingly available and used in a clinical context to monitor young people's mood and mental health. Despite the benefits of accessibility and cost-effectiveness, consumer engagement remains a hurdle for uptake and continued use. Hundreds of mood-monitoring apps are publicly available to young people on app stores; however, few studies have examined consumer perspectives. App store reviews held on Google and Apple platforms provide a large, rich source of naturally generated, publicly available user reviews. Although commercial developers use these data to modify and improve their apps, to date, there has been very little in-depth evaluation of app store user reviews within scientific research, and our current understanding of what makes apps engaging and valuable to young people is limited.

OBJECTIVE: This study aims to gain a better understanding of what app users consider useful to encourage frequent and prolonged use of mood-monitoring apps appropriate for young people.

METHODS: A systematic approach was applied to the selection of apps and reviews. We identified mood-monitoring apps (n=53) by a combination of automated application programming interface (API) methods. We only included apps appropriate for young people based on app store age categories (apps available to those younger than 18 years). We subsequently downloaded all available user reviews via API data scraping methods and selected a representative subsample of reviews (n=1803) for manual qualitative content analysis.

RESULTS: The qualitative content analysis revealed 8 main themes: accessibility (34%), flexibility (21%), recording and representation of mood (18%), user requests (17%), reflecting on mood (16%), technical features (16%), design (13%), and health promotion (11%). A total of 6 minor themes were also identified: notification and reminders; recommendation; privacy, security, and transparency; developer; adverts; and social/community.

CONCLUSIONS: Users value mood-monitoring apps that can be personalized to their needs, have a simple and intuitive design, and allow accurate representation and review of complex and fluctuating moods. App store reviews are a valuable repository of user engagement feedback and provide a wealth of information about what users value in an app and what user needs are not being met. Users perceive mood-monitoring apps positively, but over 20% of reviews identified the need for improvement.

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