Refining the Concepts of Self-quantification Needed for Health Self-management

Abstract

SummaryBackground: Questions like ‘How is your health? How are you feeling? How have you been?’ now can be answered in a different way due to innovative health self-quantification apps and devices. These apps and devices generate data that enable individuals to be informed and more responsible about their own health.Objectives: The aim of this paper is to review studies on health SQ, firstly, exploring the concepts that are associated with the users’ interaction with and around data for managing health; and secondly, the potential benefits and challenges that are associated with the use of such data to maintain or promote health, as well as their impact on the users’ certainty or confidence in taking effective actions upon such data.Methods: To answer these questions, we conducted a comprehensive literature review to build our study sample. We searched a number of electronic bibliographic databases including Scopus, Web of Science, Medline, and Google Scholar. Thematic analysis was conducted for each study to find all the themes that are related to our research aims.Results: In the reviewed literature, conceptualisation of health SQ is messy and inconsistent. Personal tracking, personal analytics, personal experimentation, and personal health activation are different concepts within the practice of health SQ; thus, a new definition and structure is proposed to set out boundaries between them. Using the data that are generated by SQS for managing health has many advantages but also poses many challenges.Conclusions: Inconsistency in conceptualisation of health SQ – as well as the challenges that users experience in health self-management – reveal the need for frameworks that can describe the users’ health SQ practice in a holistic and consistent manner. Our ongoing work toward developing these frameworks will help researchers in this domain to gain better understanding of this practice, and will enable more systematic investigations which are needed to improve the use of SQS and their data in health self-management.