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Edwards, E A; Lumsden, J; Rivas, C; Steed, L; Edwards, L A; Thiyagarajan, A; Sohanpal, R; Caton, H; Griffiths, C J; Munafò, M R; Taylor, S; Walton, R T (2016)
Publisher: B M J Group
Languages: English
Types: Article
Subjects: alliedhealth, computer, /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Health Informatics, Journal Article, 1506, Science & Technology, Life Sciences & Biomedicine, Medicine, General & Internal, General & Internal Medicine, Physical-Activity Interventions, Smoking-Cessation, Mobile Apps, Taxonomy V1, Video Game, Adults, Management, Consumers, Features, Trial, Research, PUBLIC HEALTH, 1702, 1724
Objective: Smartphone games that aim to alter health behaviours are common, but there is uncertainty about how to achieve this. We systematically reviewed health apps containing gaming elements analysing their embedded behaviour change techniques.

Methods: Two trained researchers independently coded apps for behaviour change techniques using a standard taxonomy. We explored associations with user ratings and price.

Data sources: We screened the National Health Service (NHS) Health Apps Library and all top-rated medical, health and wellness and health and fitness apps (defined by Apple and Google Play stores based on revenue and downloads). We included free and paid English language apps using ‘gamification’ (rewards, prizes, avatars, badges, leaderboards, competitions, levelling-up or health-related challenges). We excluded apps targeting health professionals.

Results: 64 of 1680 (4%) health apps included gamification and met inclusion criteria; only 3 of these were in the NHS Library. Behaviour change categories used were: feedback and monitoring (n=60, 94% of apps), reward and threat (n=52, 81%), and goals and planning (n=52, 81%). Individual techniques were: self-monitoring of behaviour (n=55, 86%), non-specific reward (n=49, 82%), social support unspecified (n=48, 75%), non-specific incentive (n=49, 82%) and focus on past success (n=47, 73%). Median number of techniques per app was 14 (range: 5–22). Common combinations were: goal setting, self-monitoring, non-specific reward and non-specific incentive (n=35, 55%); goal setting, self-monitoring and focus on past success (n=33, 52%). There was no correlation between number of techniques and user ratings (p=0.07; rs=0.23) or price (p=0.45; rs=0.10).

Conclusions: Few health apps currently employ gamification and there is a wide variation in the use of behaviour change techniques, which may limit potential to improve health outcomes. We found no correlation between user rating (a possible proxy for health benefits) and game content or price. Further research is required to evaluate effective behaviour change techniques and to assess clinical outcomes.

Trial registration number: CRD42015029841.
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