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mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials

Direito, A; Carraça, E; Rawstorn, J; Whittaker, R; Maddison, R; (2016) mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials. Annals of Behavioral Medicine , 51 (2) pp. 226-239. 10.1007/s12160-016-9846-0. Green open access

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Abstract

Background: mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals. Purpose: To (1) compare the effectiveness of mHealth interventions to promote physical activity (PA) and reduce sedentary behavior (SB) in free-living young people and adults with a comparator exposed to usual care/minimal intervention; (2) determine whether, and to what extent, such interventions affect PA and SB levels and (3) use the taxonomy of behavior change techniques (BCTs) to describe intervention characteristics. Methods: A systematic review and meta-analysis following PRISMA guidelines was undertaken to identify randomized controlled trials (RCTs) comparing mHealth interventions with usual or minimal care among individuals free from conditions that could limit PA. Total PA, moderate-to-vigorous intensity physical activity (MVPA), walking and SB outcomes were extracted. Intervention content was independently coded following the 93-item taxonomy of BCTs. Results: Twenty-one RCTs (1701 participants—700 with objectively measured PA) met eligibility criteria. SB decreased more following mHealth interventions than after usual care (standardised mean difference (SMD) −0.26 , 95 % confidence interval (CI) −0.53 to −0.00). Summary effects across studies were small to moderate and non-significant for total PA (SMD 0.14, 95 % CI −0.12 to 0.41); MVPA (SMD 0.37, 95 % CI −0.03 to 0.77); and walking (SMD 0.14, 95 % CI −0.01 to 0.29). BCTs were employed more frequently in intervention (mean = 6.9, range 2 to 12) than in comparator conditions (mean = 3.1, range 0 to 10). Of all BCTs, only 31 were employed in intervention conditions. Conclusions: Current mHealth interventions have small effects on PA/SB. Technological advancements will enable more comprehensive, interactive and responsive intervention delivery. Future mHealth PA studies should ensure that all the active ingredients of the intervention are reported in sufficient detail.

Type: Article
Title: mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s12160-016-9846-0
Publisher version: http://doi.org/10.1007/s12160-016-9846-0
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Mobile health, Behavior change techniques, Physical activity, Sedentary behavior, Meta-analysis
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1558223
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