Users’ adoption of mental health apps: Examining the impact of information cues

Hsiao Ying Huang, Masooda Bashir

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Numerous mental health apps have been developed and made available to users on the current app market. Users may find it difficult and overwhelming to select apps from the hundreds of choices that are available in the app marketplace. Clarifying what information cues may impact a user’s selection and adoption of mental health apps is now a critical and pressing issue. Objective: The aim of this study was to investigate the impact of information cues on users’ adoption of anxiety apps using observational data from the Android app market. Methods: A systematic search of anxiety apps was conducted on the Android app store by using keywords search. The title and metadata information of a total of 274 apps that met our criteria were collected and analyzed. Three trained researchers recorded the app rankings from the search results page on different dates and Web browsers. Results: Our results show that ratings (r=.56, P<.001) and reviews (r=.39, P<.001) have significant positive correlations with the number of installs, and app prices have significant negative correlations with installs (r=−.36). The results also reveal that lower-priced apps have higher ratings (r=−.23, P<.001) and a greater number of app permission requests (r=.18, P=.002) from the device. For app titles, we found that apps with titles related to symptoms have significantly lower installs than apps with titles that are not related to symptoms (P<.001). Conclusions: This study revealed a relationship between information cues and users’ adoption of mental health apps by analyzing observational data. As the first of its kind, we found impactful indicators for mental health app adoptions. We also discovered a labeling effect of app titles that could hinder mental health app adoptions and which may provide insight for future designs of mental health apps and their search mechanisms.

Original languageEnglish (US)
Article numbere83
JournalJMIR mHealth and uHealth
Volume5
Issue number6
DOIs
StatePublished - Jun 2017

Keywords

  • Anxiety
  • Mental health
  • Mobile app search
  • Recommendation system
  • User interaction design

ASJC Scopus subject areas

  • Health Informatics

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