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Strategies for Assessing Health Information Credibility Among Older Social Media Users in China: A Qualitative Study.
Chang, Leanne; Li, Wenshu; Xin, Xin; Wang, Jingyuan.
  • Chang L; Department of Communication Studies, Hong Kong Baptist University.
  • Li W; Li Ka Shing Faculty of Medicine, The University of Hong Kong.
  • Xin X; Department of Communication Studies, Hong Kong Baptist University.
  • Wang J; Department of Communication Studies, Hong Kong Baptist University.
Health Commun ; : 1-12, 2023 Nov 28.
Article en En | MEDLINE | ID: mdl-38016925
ABSTRACT
The fact that social media gives users easy access to online health information raises the question of what information evaluation strategies older adults use to distinguish trustworthy from unreliable health information. Identifying how older adults assess the credibility of health information that they acquire on social media is an important step toward understanding and reducing their susceptibility to health misinformation. In this study, we investigated the credibility assessment strategies used by older WeChat users in China. Following a qualitative approach, we conducted in-depth interviews with 40 WeChat users 65-85 years old (M = 71.75, SD = 6.65) in China who had acquired health information on WeChat. Results of theoretical thematic analysis revealed five source-based and content-based evaluative strategies (1) determining the communicative orientation of the source, (2) assessing source reputation, (3) confirming content based on life experiences, (4) checking for exaggeration in claimed effects, and (5) assessing the consistency of content across sources. Older WeChat users' reliance on certain heuristic cues and their self-reliant approach to assessing information credibility provide contextual explanations for the link between heuristic processing and susceptibility to health misinformation. The findings have implications for anti-misinformation interventions targeting the older population in China and potentially beyond.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2023 Tipo del documento: Article