title: mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials.
abstract: BACKGROUND
  mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals.
  
  
  OBJECTIVE
  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.
authors.affiliation: National Institute for Health Innovation, School of Population Health, The University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand. a.direito@auckland.ac.nz.
authors.forename: Artur
authors.identifier: http://orcid.org/0000-0002-2236-8506
authors.initials: A
authors.lastname: Direito
authors.affiliation: Exercise and Health Laboratory, Faculty of Human Kinetics, Technical University of Lisbon, Lisbon, Portugal.
authors.forename: Eliana
authors.initials: E
authors.lastname: Carraça
authors.affiliation: National Institute for Health Innovation, The University of Auckland, Auckland, New Zealand.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Rawstorn
authors.affiliation: National Institute for Health Innovation, The University of Auckland, Auckland, New Zealand.
authors.forename: Robyn
authors.initials: R
authors.lastname: Whittaker
authors.affiliation: National Institute for Health Innovation, The University of Auckland, Auckland, New Zealand.
authors.forename: Ralph
authors.initials: R
authors.lastname: Maddison
mesh_terms: D001521:Behavior Therapy / Q000379:methods*; D015444:Exercise / Q000523:psychology*; D006801:Humans; D016032:Randomized Controlled Trials as Topic; D057185:Sedentary Behavior; D017216:Telemedicine
keywords: Behavior change techniques; Meta-analysis; Mobile health; Physical activity; Sedentary behavior