ArticleDigital health
The quality of informational social support in online health communities: A content analysis of cancer-related discussions.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Oncofertility information interventions in patients with cancer: A systematic review and meta-analysis.Asia-Pacific journal of oncology nursing · 2026Review
- Patient narratives in an online hernia peer-support community: a qualitative netnographic analysis.Hernia : the journal of hernias and abdominal wall surgery · 2026Article
- Social Support Across the Cancer Care Continuum in Malawi: Narratives from Cancer Survivors.SSM. Qualitative research in health · 2026Article
- Where Can Artificial Intelligence Assist Cancer Care?: Examining Patient-Centered Communication Dimension Effects.Health services research · 2026Article
- Quality and Misinformation About Health Conditions in Online Peer Support Groups: Scoping Review.Journal of medical Internet research · 2025Article
- Automated Credibility Assessment of Web-Based Health Information Considering Health on the Net Foundation Code of Conduct (HONcode): Model Development and Validation Study.JMIR formative research · 2023Article
- 'In my experience …': The use of the wordDigital healthArticle
- Breast cancer prevention and treatment misinformation on Twitter: An analysis of two languages.Digital healthArticle
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums. Methods: A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS. Results: The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, Conclusions: This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors.
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