Direito Artur, Carraça Eliana, Rawstorn Jonathan, Whittaker Robyn, Maddison Ralph
National Institute for Health Innovation, School of Population Health, The University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand.
Exercise and Health Laboratory, Faculty of Human Kinetics, Technical University of Lisbon, Lisbon, Portugal.
Ann Behav Med. 2017 Apr;51(2):226-239. doi: 10.1007/s12160-016-9846-0.
mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals.
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.
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.
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.
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.
移动健康项目为切实且经济高效地提供能惠及众多个体的干预措施提供了可能。
（1）比较移动健康干预措施与接受常规护理/最低限度干预的对照措施在促进自由生活的年轻人和成年人身体活动（PA）及减少久坐行为（SB）方面的效果；（2）确定此类干预措施是否以及在何种程度上影响PA和SB水平；（3）使用行为改变技术分类法（BCTs）描述干预措施的特征。
按照PRISMA指南进行系统综述和荟萃分析，以识别将移动健康干预措施与常规护理或最低限度护理进行比较的随机对照试验（RCTs），研究对象为无可能限制PA的疾病的个体。提取总PA、中度至剧烈强度身体活动（MVPA）、步行和SB的结果。干预内容按照93项BCTs分类法进行独立编码。
21项RCTs（1701名参与者 - 700名有客观测量PA的参与者）符合纳入标准。与常规护理相比，移动健康干预后SB的减少幅度更大（标准化均值差（SMD）-0.26，95%置信区间（CI）-0.53至-0.00）。各项研究的汇总效应对于总PA（SMD 0.14，95% CI -0.12至0.41）、MVPA（SMD 0.37，95% CI -0.03至0.77）和步行（SMD 0.14，95% CI -0.01至0.29）而言较小至中等且无统计学意义。干预措施中使用BCTs的频率（均值 = 6.9，范围2至12）高于对照措施（均值 = 3.1，范围0至10）。在所有BCTs中，只有31项被用于干预措施中。
当前的移动健康干预措施对PA/SB的影响较小。技术进步将使干预措施的提供更加全面、互动和具有响应性。未来的移动健康PA研究应确保充分详细地报告干预措施的所有有效成分。
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