ArticleFrontiers in public health2025
Credibility of AI generated and human video doctors and the relationship to social media use.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Information Source-Message Effect on Consumers' Intentions to Adhere to Food Safety Practices When Handling and Preparing Raw Chicken.Foods (Basel, Switzerland) · 2026Article
- Multilayered Epistemic Disruption in AI-Driven Health Misinformation: Conceptual Framework and Viewpoint.JMIR infodemiology · 2026Article
- Governing Patient-Facing AI-Generated Video in Digital Health: A Risk-and-Ethics Matrix for Deployment, Monitoring, and Change Control.Journal of medical Internet research · 2026Article
- AI-generated videos in medical science popularization and education: a scoping review.Frontiers in public health · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: It's unclear if the age stereotype of young doctors also applies to artificial intelligence (AI) doctors. Although research shows social media can reduce discrimination, age stereotypes are still underexplored. This study is aimed to determine the relationship between social media use and age stereotypes among doctors in online health videos narrated by AI/human doctors. Methods: This is a cross-sectional study, divided into two phases and conducted from May 25 to June 19, 2024. Self-reported questionnaire was developed and collected by face-to-face interview. All individuals who are 18 years old or above with adequate reading comprehension skills are eligible. The credibility of doctors among participants in online health videos in AI and human conditions and their relationship with the intensity of social media use were investigated. Univariable and multivariable generalized linear models were used to explore the relationship between social media use and age stereotypes. Results: We obtained 294 and 300 valid questionnaires in phase I and phase II, respectively. In both AI and human conditions, there is a preference for health education conducted by older doctors. Older doctors were rated the most credible (median score 14·00, IQR [12·00, 15·00] in the condition of AI, median score 14·00, IQR [12·00, 15·00] in the condition of Human). Both univariable and multivariable generalized linear models revealed a significant negative association between social media use and age stereotypes, particularly between older and younger doctors ( Conclusion: The image of AI doctors can help patients avoid being influenced by age stereotypes, enabling them to evaluate doctors' medical expertise more objectively.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.