Self-Tracking Technology for mHealth: A Systematic Review and the PAST SELF Framework
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In today's connected society, many people rely on mHealth and self-tracking (ST) technology to help them break their sedentary lifestyle and stay fit. However, there is scarce evidence of such technological interventions' effectiveness, and there are no standardized methods to evaluate the short- and long-term impact of such technologies on people's physical activity and health. This work aims to help ST and HCI practitioners and researchers by empowering them with systematic guidelines and an extensible framework for constructing such technological interventions. This survey and the proposed design and evaluation framework aim to contribute to health behavior change and user engagement sustainability. To this end, we conduct a literature review of 117 papers between 2008 and 2020, which identifies the core ST HCI design methods and their efficacy, as well as and the most comprehensive list to date of user engagement evaluation metrics for ST. Based on the review's findings, we propose the PAST SELF end-to-end framework to facilitate the classification, design, and evaluation of ST technology. PAST SELF systematically organizes common methods and guidelines from existing works in ubiquitous ST research. Hence, it has potential applications in industrial and scientific settings and can be utilized by practitioners and researchers alike.
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