Interactive technologies to promote physical activity and sedentary behaviour change

Abstract

Background: Insufficient physical activity (PA) and high levels of sedentary behaviour (SB) are two distinct behaviours adversely associated with cardiometabolic risk factors for many non-communicable diseases. Given the global prevalence of insufficient PA and increased SB, interventions targeting these behaviours are public health priorities. Effective PA/SB interventions typically involve human interaction, are resource intensive, and have limited reach. The current unparalleled adoption of emerging technologies, such as smartphones, presents an ideal opportunity to investigate how these can be used to promote PA/SB change. Aim: To 1) identify emerging available technologies for PA/SB change, 2) test these technologies, and 3) develop and test an intervention building on understanding from 1 and 2. Methods: Four phases of research were undertaken: A systematic review and meta-analysis assessed current evidence of mobile health (mHealth)-based PA/SB interventions and a review identified off-the-shelf commercially available smartphone apps. Findings from the two reviews motivated the subsequent experimental studies. A pragmatic randomised controlled trial compared the effectiveness of two commercially available apps with usual care. A single group 8-week prospective study evaluated the feasibility and acceptability of a bespoke app. Results: Based on the reviews, current mHealth interventions have small to moderate effects on PA/SB outcomes, and top downloaded PA apps incorporate few behaviour change techniques. Findings from the RCT showed that off-the-shelf PA apps were not effective at promoting PA levels or fitness. Guided by a conceptual and a technological framework, a fully automated theory-based proof-of-concept adaptive smartphone-delivered intervention was developed to deliver behaviour change-content aimed at PA/SB change. Feasibility, acceptability, and shortcomings were identified that require optimisation in future iterations. Conclusion: An mHealth low-burden and easily scalable approach can contribute to promote behaviour change at population levels, but at present, mHealth-based interventions as a standalone for promoting PA and SB have either no or small sized effects on increasing PA and decreasing SB in the short term. Understanding how to best harness mHealth technologies to maximise their potential will require interdisciplinary collaboration among behavioural, computer and engineer scientists.