In today's connected society, many people rely on mHealth and self-tracking (ST) technology to help them adopt healthier habits with a focus on breaking their sedentary lifestyle and staying fit. However, there is scarce evidence of such technological interventions' effectiveness, and there are no standardized methods to evaluate their impact on people's physical activity (PA) and health. This work aims to help ST practitioners and researchers by empowering them with systematic guidelines and a framework for designing and evaluating technological interventions to facilitate health behavior change (HBC) and user engagement (UE), focusing on increasing PA and decreasing sedentariness. To this end, we conduct a literature review of 129 papers between 2008 and 2022, which identifies the core ST HCI design methods and their efficacy, as well as the most comprehensive list to date of UE evaluation metrics for ST. Based on the review's findings, we propose PAST SELF, a framework to guide the design and evaluation of ST technology that has potential applications in industrial and scientific settings. Finally, to facilitate researchers and practitioners, we complement this paper with an open corpus and an online, adaptive exploration tool for the PAST SELF data.
翻译:在当今相互联系的社会中,许多人依靠健康和自我跟踪技术(ST)来帮助他们养活更健康的习惯,重点是打破其定居生活方式和保持适应性。然而,这种技术干预的有效性证据很少,而且没有标准化的方法来评价其对人的身体活动(PA)和健康的影响。这项工作的目的是帮助ST的从业人员和研究人员,赋予他们以系统的指导方针和框架来设计和评价技术干预措施,以促进健康行为的变化和用户的参与(UE),重点是增加PA和减少惯性。为此,我们从2008年至2022年对129份文件进行了文献审查,其中确定了ST HCI的核心设计方法及其效果,以及迄今为止最全面的STE评价指标清单。根据审查结果,我们建议PAST SELF作为指导设计和评价科技技术设计的框架,在工业和科学环境中可能应用。最后,为了便利研究人员和从业人员,我们用一个公开的软件和一个在线适应性探索工具来补充这份文件。