14 Years of Self-Tracking Technology for mHealth -- Literature Review: Lessons Learnt and the PAST SELF Framework
It addresses the problem for mHealth researchers and practitioners by providing systematic guidelines, though it is incremental as it builds on existing literature.
This paper tackles the lack of standardized methods for evaluating the effectiveness of self-tracking technology in mHealth by conducting a literature review of 129 papers from 2008 to 2022, resulting in the PAST SELF framework to guide design and evaluation, along with an open corpus and tool.
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.