Ryan Kathleen, Dockray Samantha, Linehan Conor
School of Applied Psychology, University College Cork, Ireland.
Digit Health. 2019 Feb 5;5:2055207619826685. doi: 10.1177/2055207619826685. eCollection 2019 Jan-Dec.
The aim of this study is to review the evidence for tailored eHealth weight-loss interventions, describing in detail: 1. how tailoring was implemented in these studies and 2. whether these tailored approaches were effective in producing weight loss compared with generic or inactive controls.
A systematic review was carried out. Five databases were searched up until 15 March, 2018, including: EBSCO, Science Direct, Pubmed, EMBASE and Web of Science, using combinations of the concepts 'tailoring', 'eHealth' and 'overweight'.
Eight articles relating to six interventions were accepted. Tailoring was carried out in a number of ways, based on, for example, anthropometric data, health-related behaviours (e.g. dietary intake, physical activity), goals (e.g. weight goal), theoretical determinants (e.g. confidence/willingness to change behaviours), psychosocial factors (e.g. social support) and participant location. Systems acquired data using strategies that ranged from online questionnaire administration, to the dynamic gathering of data from web-based diaries, websites, mobile applications and SMS messaging. Tailored interventions were more effective in supporting weight loss than generic or waitlist controls in four of the six articles. Effect sizes were very small to moderate, with evidence for fluctuations in effect sizes and differences of effect between tailoring and non-tailoring interventions, and between tailoring types, over time.
We contribute an enhanced understanding of the variety of methods used for the tailoring of eHealth interventions for weight loss and propose a model for categorising tailoring approaches.
本研究旨在回顾针对特定人群的电子健康减肥干预措施的证据,详细描述:1. 这些研究中如何实施个性化定制;2. 与一般或无干预对照组相比,这些个性化方法在促进减肥方面是否有效。
进行了一项系统综述。截至2018年3月15日,检索了五个数据库,包括:EBSCO、科学Direct、Pubmed、EMBASE和科学网,使用了“个性化定制”、“电子健康”和“超重”等概念的组合。
接受了八篇与六项干预措施相关的文章。个性化定制通过多种方式进行,例如基于人体测量数据、与健康相关的行为(如饮食摄入、身体活动)、目标(如体重目标)、理论决定因素(如改变行为的信心/意愿)、心理社会因素(如社会支持)和参与者所在地。系统使用的获取数据的策略范围从在线问卷管理到从网络日记、网站、移动应用程序和短信中动态收集数据。在六篇文章中的四篇中,个性化干预在支持减肥方面比一般或等待名单对照组更有效。效应大小非常小到中等,有证据表明效应大小随时间波动,以及个性化和非个性化干预之间、不同类型的个性化干预之间存在效应差异。
我们增进了对用于电子健康减肥干预措施个性化定制的多种方法的理解,并提出了一种对个性化定制方法进行分类的模型。