Accepted for/Published in: JMIR Mental Health
Date Submitted: Mar 4, 2019
Open Peer Review Period: Mar 4, 2019 - Mar 19, 2019
Date Accepted: Apr 28, 2019
(closed for review but you can still tweet)
Exploring user needs and preferences for mobile apps for sleep disturbance: A mixed-methods study
ABSTRACT
Background:
Mobile health (mHealth) apps demonstrate promise in delivering sleep therapy on a large scale however user engagement remains a challenge for sustained usage.
Objective:
The aim of this study was to assess the needs and preferences of those with poor sleep and insomnia to inform the development of a sleep app.
Methods:
A mixed-method triangulation approach included qualitative (focus groups, app reviews) and quantitative (online survey) data collection. Two focus groups were conducted (N=10). An online survey tested themes identified from the focus groups against a larger population (N=167). In addition, we analysed 434 user reviews of 6 smartphone apps available on the app store.
Results:
From the focus groups, common themes included the need to account for the diversity of subjective sleep experiences with an adaptive program, app features such as alarms and sleep diaries, the complex yet condescending nature of existing resources, providing rationale for information requested and cost as a motivator. Survey participants (156/167, 93%) would be likely, or very likely, to try a proven app for sleep. The most important app features reported were sleep diary and tracking (148/167, 88%), sharing sleep data with a doctor (116/167, 70%), and tracking of lifestyle factors (107/167, 64%). App reviews highlighted the alarm as the most salient app feature (43/122, 35%) and data-synchronisation with a wearable device (WD) as the most commonly mentioned functionality (40/135, 30%).
Conclusions:
As suggested by the design literature, we followed a design process involving end-users. Improving user engagement for sleep apps requires a focus on app content and functionality. Our triangulated user research provided a wealth of insights for developing an engaging mhealth app that ensures therapeutic exposure.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.