Leeds Institute of Health Sciences, University of Leeds, Worsley Building, Clarendon Way, Leeds, UK.
Health Intervention and Technology Assessment Program, Ministry of Public Health, Nonthaburi, Thailand.
Syst Rev. 2017 Oct 6;6(1):193. doi: 10.1186/s13643-017-0591-7.
Mobile health (mHealth) interventions for smoking cessation have been shown to be associated with an increase in effectiveness. However, interventions using mobile phones to change people's behaviour are often perceived as complex interventions, and the interactions between several components within them may affect the outcome. Therefore, it is important to understand how we can improve the design of mHealth interventions using mobile phones as a medium to deliver services.
Randomised controlled trials (RCTs) of mHealth interventions to support smoking cessation or uptake of smoking cessation services for smokers will be included in this systematic review. A search will be performed by searching MEDLINE, MEDLINE(R) In-Process & Other Non-Indexed Citations, EMBASE, PsycINFO, Web of Science, and CINAHL. A search for new publications will be conducted 3 months prior to submission for publication as mHealth is an emerging area of research. A random-effects meta-analysis model will be used to summarise the effectiveness of mHealth interventions. The risk ratio will be used for the primary outcome, self-reported or verified smoking abstinence, and any binary outcomes for uptake of smoking cessation services. The standardised mean difference using Hedges' g will be reported for continuous data. Heterogeneity will be assessed using I statistics. Where feasible, meta-regression analysis using random-effects multilevel modelling will be conducted to examine the association of pre-specified characteristics (covariates) at the study level with the effectiveness of interventions. Publication bias will be explored using Egger's test for continuous outcomes and Harbord and Peters tests for dichotomous outcomes. The funnel plot will be used to evaluate the presence of publication bias. The Cochrane Risk of Bias Tool will be used to assess differences in risks of bias.
The results of this systematic review will provide future research with a foundation for designing and evaluating complex interventions that use mobile phones as a platform to deliver behaviour change techniques.
PROSPERO CRD42016026918 .
已证实，利用移动健康（mHealth）干预来戒烟可提高干预效果。然而，利用手机来改变人们行为的干预措施通常被认为是复杂的干预措施，其中几个组成部分之间的相互作用可能会影响结果。因此，了解如何改进以手机作为媒介来提供服务的 mHealth 干预措施的设计非常重要。
本系统评价将纳入 mHealth 干预措施以支持戒烟或吸烟者接受戒烟服务的随机对照试验（RCT）。将通过检索 MEDLINE、MEDLINE（R）在处理中及其他非索引引文、EMBASE、PsycINFO、Web of Science 和 CINAHL 来进行搜索。由于 mHealth 是一个新兴的研究领域，因此将在提交出版前 3 个月搜索新出版物。将使用随机效应荟萃分析模型来总结 mHealth 干预措施的有效性。将使用风险比来报告主要结局（自我报告或验证的戒烟）和任何关于戒烟服务使用的二进制结局。将使用 Hedges'g 报告连续数据的标准化均数差。将使用 I 统计量评估异质性。如果可行，将使用随机效应多级建模的荟萃回归分析来检查研究水平上的预指定特征（协变量）与干预效果的相关性。将使用 Egger 检验连续结局和 Harbord 和 Peters 检验二项结局来探索发表偏倚。漏斗图将用于评估发表偏倚的存在。将使用 Cochrane 偏倚风险工具来评估研究之间的偏倚风险差异。
本系统评价的结果将为未来的研究提供设计和评估利用手机作为平台来提供行为改变技术的复杂干预措施的基础。
PROSPERO CRD42016026918。
