Abstract

Many mobile health (mHealth) application interventions include virtual representations of the self in varying forms, such as agents, or avatars to initiate health behaviour change. This review aimed to determine: (i) which virtual representations are effective in mHealth application interventions, and (ii) whether any studies implemented specific mechanisms (the psychological causes of change) and behaviour change techniques (BCTs) to influence positive behaviour change. Following PRISMA guidelines, a narrative systematic review of empirical studies was conducted from ten different databases (ranging from MEDLINE to Cochrane Library) from inception to December 2021. This included articles reporting a virtual representation of mHealth application intervention, published in English from any time point, which addressed and reported a variety of outcome health behaviours. Information on sample characteristics, study conditions, mechanisms and BCTs, results, and conclusions were extracted. Quality and risk of bias were assessed using the Mixed Methods Appraisal and Cochrane Risk of Bias Tools. Out of the 2,579 original search results, five eligible studies (total participants = 509), with low to moderate quality were included. It was found that customisable virtual representation mHealth interventions were most effective in encouraging behaviour change and app adherence. These interventions included mechanisms such as motivation, feedback, self-image, and BCTs such as goal setting, and self-monitoring. The current evidence suggests that virtual representations in mHealth app interventions may positively influence health behaviour change. However, there is limited evidence available to determine to which these influences are a result of the virtual representations, or the intervention design.

摘要

许多移动健康 (mHealth) 应用程序干预包括以各种形式（例如代理或化身）来启动健康行为改变的自我虚拟表示。本综述旨在确定：(i) 哪些虚拟表征在 mHealth 应用干预中有效，以及 (ii) 是否有任何研究实施了特定机制（改变的心理原因）和行为改变技术 (BCT) 来影响积极的行为改变。遵循 PRISMA 指南，从成立到 2021 年 12 月，从十个不同的数据库（从 MEDLINE 到 Cochrane 图书馆）对实证研究进行了叙述性系统评价。其中包括报告 mHealth 应用干预的虚拟表示的文章，从任何时间点以英文发表, 其中涉及并报告了各种结果健康行为。提取样本特征、研究条件、机制和BCT、结果和结论等信息。使用混合方法评估和 Cochrane 偏倚风险工具评估质量和偏倚风险。在 2,579 个原始搜索结果中，包括了 5 个符合条件的研究（参与者总数 = 509），质量为低到中等。结果发现，可定制的虚拟表示 mHealth 干预在鼓励行为改变和应用程序依从性方面最为有效。这些干预措施包括动机、反馈、自我形象等机制，以及目标设定和自我监控等 BCT。目前的证据表明，mHealth 应用干预中的虚拟表示可能会对健康行为的改变产生积极影响。然而，