Lay Crowd-Sourced Expertise (LCE) and its Influence on the New Role Of Patients: Ethical and Societal Issues - Inserm - Institut national de la santé et de la recherche médicale Accéder directement au contenu
Chapitre D'ouvrage Année : 2016

Lay Crowd-Sourced Expertise (LCE) and its Influence on the New Role Of Patients: Ethical and Societal Issues

L'expertise profane multi-sources et son influence sur le nouveau rôle des patients : aspects éthiques et sociétaux

Résumé

The emergence of social media on the Internet allows patients to discuss about their chronic diseases within online communities sharing common interests. This allows patients to gather other patients' experience, and gain new knowledge that is usually not shared by healthcare professionals. In this context, further studies are required on the actual impact of the use of social networks on the quality of life of patients participating in these online communities, focusing on the evolving role and impact of Lay Crowdsourced expertise (LCE) in improving disease management and control. We present a study on a large number of posts from social networks of different online communities. This study allowed us to choose four pathologies, with distinctive characteristics relevant for our future analysis, and to define the themes that will be covered in future work by online questionnaires. The analysis of responses from patients, who volunteer to participate, will help us in exploring how interactions between patients, on these online communities, may help them to gain useful information for managing their conditions and improving their quality of life. Furthermore, we will identify new ethical issues that arise in the sharing of health data.
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Dates et versions

inserm-01592823 , version 1 (25-09-2017)

Identifiants

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Eugenia Lamas, Rodrigo Salinas, Marcela Ferrer, Cédric Bousquet, Dominique Vuillaume. Lay Crowd-Sourced Expertise (LCE) and its Influence on the New Role Of Patients: Ethical and Societal Issues. Exploring Complexity in Health: An Interdisciplinary Systems Approach, 228, pp.80-4, 2016, ⟨10.3233/978-1-61499-678-1-80⟩. ⟨inserm-01592823⟩
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