ORIGINAL RESEARCH article
Front. Public Health
Sec. Public Health Education and Promotion
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1559378
Credibility of AI generated and human video doctors and the relationship to social media use
Provisionally accepted
- 1Third Xiangya Hospital, Central South University, Changsha, China
- 2Changsha Medical University, Changsha, Hunan Province, China
- 3School of Journalism and Communication, Hunan University, Changsha, China
- 4School of Journalism and Information Communication, Huazhong University of Science and Technology, Wuhan, China
- 5Huazhong University of Science and Technology, Wuhan, Hubei Province, China
- 6Beijing University of Chinese Medicine, Beijing, Beijing Municipality, China
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AbstractObjective: 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. 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 indicate that revealed a significant negative association between social media use and age stereotypes, particularly between older and younger doctors (β = -0·34, P < 0·001) in the condition of AI. In the condition of human, the intensity of social media use is not related to participants’ age stereotypes. Conclusion: The image of AI doctors can help patients avoid being influenced by age stereotypes, enabling them to evaluate doctors’ medical expertise more objectively.
Keywords: social media use, artificial intelligence doctors, human doctors, online health video, age stereotype
Received: 12 Jan 2025; Accepted: 18 Jun 2025.
Copyright: © 2025 Liu, Wang, Pan and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Peijia Wang, School of Journalism and Communication, Hunan University, Changsha, China
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