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Social inequality in the digital transformation: risks and potentials of mobile health technologies for social inequalities in health

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Authors and Corporations: Sawert, Tim (Author), Tuppat, Julia (Author)
Other Authors: Tuppat, Julia [Author]
Type of Resource: E-Book
Language: English
Berlin, Germany German Socio-Economic Panel (SOEP), DIW Berlin [2020]
Series: Deutsches Institut für Wirtschaftsforschung: SOEP papers on multidisciplinary panel data research ; 1079 (2020)
Source: Verbunddaten SWB
Lizenzfreie Online-Ressourcen
Summary: The paper addresses the impact of digital health technologies on social inequalities in health. We set focus on mobile health technologies (mHealth) and analyse whether (a) usage of such technologies differs by educational level and (b) whether their usage moderate social inequalities in health satisfaction. We first develop a theoretical model in order to establish potential associations between social inequality, mHealth usage and health satisfaction. Assuming that mHealth technologies might positively affect health behaviour, they might particularly benefit groups with low health literacy and thus, have the potential to decrease the social gap in health behaviours, that was consistently reported in previous research. On the other hand, drawing on theories in the field of the digital divide, mHealth technologies might in contrast even exacerbate existing inequalities, if groups with a higher socio-economic status use them more often (2nd level digital divide) and/or particularly benefit from using them (3rd level digital divide). Using data of the Innovation Sample of the Germany Socio-Economic Panel Study (N=5,075), we find evidence for a 2nd level digital divide in mHealth usage: Among smartphone users, higher educated respondents are more likely to use health/fitness apps. However, our results do not support the existence of a 3rd level divide: There is no difference in the benefit of usage on respondents' subjective health satisfaction by educational level. Further research is needed in order to analyse the proposed associations more in depth.
Physical Description: 1 Online-Ressource (circa 18 Seiten)