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Review
. 2017 Apr 27;19(4):e136.
doi: 10.2196/jmir.6731.

Social Health Inequalities and eHealth: A Literature Review With Qualitative Synthesis of Theoretical and Empirical Studies

Karine Latulippe  1 , Christine Hamel  1 , Dominique Giroux  2   3
Affiliations
Review

Social Health Inequalities and eHealth: A Literature Review With Qualitative Synthesis of Theoretical and Empirical Studies

Karine Latulippe et al. J Med Internet Res. .

Abstract

Background: eHealth is developing rapidly and brings with it a promise to reduce social health inequalities (SHIs). Yet, it appears that it also has the potential to increase them.

Objectives: The general objective of this review was to set out how to ensure that eHealth contributes to reducing SHIs rather than exacerbating them. This review has three objectives: (1) identifying characteristics of people at risk of experiencing social inequality in health; (2) determining the possibilities of developing eHealth tools that avoid increasing SHI; and (3) modeling the process of using an eHealth tool by people vulnerable to SHI.

Methods: Following the EPPI approach (Evidence for Policy and Practice of Information of the Institute of Education at the University of London), two databases were searched for the terms SHIs and eHealth and their derivatives in titles and abstracts. Qualitative, quantitative, and mixed articles were included and evaluated. The software NVivo (QSR International) was employed to extract the data and allow for a metasynthesis of the data.

Results: Of the 73 articles retained, 10 were theoretical, 7 were from reviews, and 56 were based on empirical studies. Of the latter, 40 used a quantitative approach, 8 used a qualitative approach, 4 used mixed methods approach, and only 4 were based on participatory research-action approach. The digital divide in eHealth is a serious barrier and contributes greatly to SHI. Ethnicity and low income are the most commonly used characteristics to identify people at risk of SHI. The most promising actions for reducing SHI via eHealth are to aim for universal access to the tool of eHealth, become aware of users' literacy level, create eHealth tools that respect the cultural attributes of future users, and encourage the participation of people at risk of SHI.

Conclusions: eHealth has the potential to widen the gulf between those at risk of SHI and the rest of the population. The widespread expansion of eHealth technologies calls for rigorous consideration of interventions, which are not likely to exacerbate SHI.

Keywords: Internet; healthcare disparities; social media; telemedecine.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
PRISMA flow diagram.
Figure 2
Figure 2
Process of using an eHealth tool.
See this image and copyright information in PMC

References

    1. Kohl LF, Crutzen R, de Vries NK. Online prevention aimed at lifestyle behaviors: a systematic review of reviews. J Med Internet Res. 2013;15(7):e146. doi: 10.2196/jmir.2665. http://www.jmir.org/2013/7/e146/ v15i7e146 - DOI - PMC - PubMed
    1. Ammann R, Vandelanotte C, de Vries H, Mummery WK. Can a website-delivered computer-tailored physical activity intervention be acceptable, usable, and effective for older people? Health Educ Behav. 2013 Apr;40(2):160–70. doi: 10.1177/1090198112461791.1090198112461791 - DOI - PubMed
    1. Hamel LM, Robbins LB. Computer- and web-based interventions to promote healthy eating among children and adolescents: a systematic review. J Adv Nurs. 2013 Jan;69(1):16–30. doi: 10.1111/j.1365-2648.2012.06086.x. - DOI - PubMed
    1. McClure JB, Shortreed SM, Bogart A, Derry H, Riggs K, St JJ, Nair V, An L. The effect of program design on engagement with an internet-based smoking intervention: randomized factorial trial. J Med Internet Res. 2013;15(3):e69. doi: 10.2196/jmir.2508. http://www.jmir.org/2013/3/e69/ v15i3e69 - DOI - PMC - PubMed
    1. de Josselin de Jong S, Candel M, Segaar D, Cremers H, de Vries H. Efficacy of a Web-based computer-tailored smoking prevention intervention for Dutch adolescents: randomized controlled trial. J Med Internet Res. 2014;16(3):e82. doi: 10.2196/jmir.2469. http://www.jmir.org/2014/3/e82/ v16i3e82 - DOI - PMC - PubMed

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