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Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies

BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a for...

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Autores principales: Almalki, Manal, Gray, Kathleen, Martin-Sanchez, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909388/
https://www.ncbi.nlm.nih.gov/pubmed/27234343
http://dx.doi.org/10.2196/jmir.5000
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author Almalki, Manal
Gray, Kathleen
Martin-Sanchez, Fernando
author_facet Almalki, Manal
Gray, Kathleen
Martin-Sanchez, Fernando
author_sort Almalki, Manal
collection PubMed
description BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a formal framework for describing the self-quantifiers’ activities and their contextual components or constructs to pursue these health related goals. Establishing such framework is important because it is the first step to operationalize health SQ fully. This may in turn help to achieve the aims of health professionals and researchers who seek to make or study changes in the self-quantifiers’ health systematically. OBJECTIVE: The aim of this study was to review studies on health SQ in order to answer the following questions: What are the general features of the work and the particular activities that self-quantifiers perform to achieve their health objectives? What constructs of health SQ have been identified in the scientific literature? How have these studies described such constructs? How would it be possible to model these constructs theoretically to characterize the work of health SQ? METHODS: A systematic review of peer-reviewed literature was conducted. A total of 26 empirical studies were included. The content of these studies was thematically analyzed using Activity Theory as an organizing framework. RESULTS: The literature provided varying descriptions of health SQ as data-driven and objective-oriented work mediated by SQ tools. From the literature, we identified two types of SQ work: work on data (ie, data management activities) and work with data (ie, health management activities). Using Activity Theory, these activities could be characterized into 6 constructs: users, tracking tools, health objectives, division of work, community or group setting, and SQ plan and rules. We could not find a reference to any single study that accounted for all these activities and constructs of health SQ activity. CONCLUSIONS: A Health Self-Quantification Activity Framework is presented, which shows SQ tool use in context, in relation to the goals, plans, and competence of the user. This makes it easier to analyze issues affecting SQ activity, and thereby makes it more feasible to address them. This review makes two significant contributions to research in this field: it explores health SQ work and its constructs thoroughly and it adapts Activity Theory to describe health SQ activity systematically.
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spelling pubmed-49093882016-06-28 Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies Almalki, Manal Gray, Kathleen Martin-Sanchez, Fernando J Med Internet Res Original Paper BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a formal framework for describing the self-quantifiers’ activities and their contextual components or constructs to pursue these health related goals. Establishing such framework is important because it is the first step to operationalize health SQ fully. This may in turn help to achieve the aims of health professionals and researchers who seek to make or study changes in the self-quantifiers’ health systematically. OBJECTIVE: The aim of this study was to review studies on health SQ in order to answer the following questions: What are the general features of the work and the particular activities that self-quantifiers perform to achieve their health objectives? What constructs of health SQ have been identified in the scientific literature? How have these studies described such constructs? How would it be possible to model these constructs theoretically to characterize the work of health SQ? METHODS: A systematic review of peer-reviewed literature was conducted. A total of 26 empirical studies were included. The content of these studies was thematically analyzed using Activity Theory as an organizing framework. RESULTS: The literature provided varying descriptions of health SQ as data-driven and objective-oriented work mediated by SQ tools. From the literature, we identified two types of SQ work: work on data (ie, data management activities) and work with data (ie, health management activities). Using Activity Theory, these activities could be characterized into 6 constructs: users, tracking tools, health objectives, division of work, community or group setting, and SQ plan and rules. We could not find a reference to any single study that accounted for all these activities and constructs of health SQ activity. CONCLUSIONS: A Health Self-Quantification Activity Framework is presented, which shows SQ tool use in context, in relation to the goals, plans, and competence of the user. This makes it easier to analyze issues affecting SQ activity, and thereby makes it more feasible to address them. This review makes two significant contributions to research in this field: it explores health SQ work and its constructs thoroughly and it adapts Activity Theory to describe health SQ activity systematically. JMIR Publications 2016-05-27 /pmc/articles/PMC4909388/ /pubmed/27234343 http://dx.doi.org/10.2196/jmir.5000 Text en ©Manal Almalki, Kathleen Gray, Fernando Martin-Sanchez. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 27.05.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Almalki, Manal
Gray, Kathleen
Martin-Sanchez, Fernando
Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title_full Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title_fullStr Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title_full_unstemmed Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title_short Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies
title_sort activity theory as a theoretical framework for health self-quantification: a systematic review of empirical studies
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909388/
https://www.ncbi.nlm.nih.gov/pubmed/27234343
http://dx.doi.org/10.2196/jmir.5000
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