This paper is in the following e-collection/theme issue:

Peer-to-Peer Support and Online Communities (693) Infodemiology and Infoveillance (1429) Quality/Credibility of eHealth Information and Trust Issues (582) Information Seeking, Information Needs (515) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1743) Methods and New Tools in Mental Health Research (493) Information Quality in Digital Media (362) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1076)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44656, first published .
The “Loci” of Misinformation and Its Correction in Peer- and Expert-Led Online Communities for Mental Health: Content Analysis

The “Loci” of Misinformation and Its Correction in Peer- and Expert-Led Online Communities for Mental Health: Content Analysis

The “Loci” of Misinformation and Its Correction in Peer- and Expert-Led Online Communities for Mental Health: Content Analysis

Authors of this article:

Nicole Bizzotto1 Author Orcid Image ;   Peter Johannes Schulz1, 2, 3 Author Orcid Image ;   Gert-Jan de Bruijn4 Author Orcid Image
Article Authors Cited by (4) Tweetations (7) Metrics

Journals

  1. Bizzotto N, de Bruijn G, Schulz P. Buffering against exposure to mental health misinformation in online communities on Facebook: the interplay of depression literacy and expert moderation. BMC Public Health 2023;23(1) View
  2. Zhang S, Zhou H, Zhu Y. Why People Accept Mental Health-Related Misinformation: Role of Social Media Metrics in Users’ Information Processing. Social Science Computer Review 2024 View
  3. Bizzotto N, de Bruijn G, Schulz P. Clusters of Patient Empowerment and Mental Health Literacy Differentiate Professional Help‐Seeking Attitudes in Online Mental Health Communities Users. Health Expectations 2025;28(1) View
  4. Kuo H, Chen S. Predicting User Engagement in Health Misinformation Correction on Social Media Platforms in Taiwan: Content Analysis and Text Mining Study. Journal of Medical Internet Research 2025;27:e65631 View