Framework for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance: systematic review

Background: Mobile health (mHealth) apps offer a scalable option for treating sleep disturbance at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based apps.

Objective: The aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance.

Methods: A systematic search of studies published from inception of databases through to February 2020 was conducted using 5 databases (MEDLINE, EMBASE, Cochrane Library, PsycInfo and CINAHL).

Results: A total of 6,015 papers were found using the search strategy. After screening, 15 papers were identified which examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. The majority of these apps delivered CBT-I (n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only three papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only one app had available evidence assessing all four implementation metrics. Most apps were prototype versions (n=5), with few matured apps. Six apps had papers which provided a quantitative evaluation of clinical outcomes, but only one app had a supporting adequately-powered RCT.

Conclusions: This is the first systematic review to synthesise and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardisation and consistency in use of best-practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we have developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation.