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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, Artur, Carraça, Eliana, Rawstorn, Jonathan, Whittaker, Robyn and Maddison, Ralph 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, In Press, pp. 1-14, doi: 10.1007/s12160-016-9846-0.

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Title mHealth technologies to influence physical activity and sedentary behaviors: behavior change techniques, systematic review and meta-analysis of randomized controlled trials
Author(s) Direito, Artur
Carraça, Eliana
Rawstorn, Jonathan
Whittaker, Robyn
Maddison, Ralph
Journal name Annals of behavioral medicine
Season In Press
Start page 1
End page 14
Total pages 14
Publisher Springer
Place of publication New York, N.Y.
Publication date 2016-10-18
ISSN 0883-6612
1532-4796
Keyword(s) mobile health
behavior change techniques
physical activity
sedentary behavior
meta-analysis
Summary 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.
Language eng
DOI 10.1007/s12160-016-9846-0
Field of Research 110699 Human Movement and Sports Science not elsewhere classified
Socio Economic Objective 920401 Behaviour and Health
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Society of Behavioral Medicine
Persistent URL http://hdl.handle.net/10536/DRO/DU:30088372

Document type: Journal Article
Collection: School of Exercise and Nutrition Sciences
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Created: Mon, 31 Oct 2016, 15:37:23 EST

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