Suppr超能文献

人工智能生成的视频医生和人类视频医生的可信度及其与社交媒体使用的关系。

Credibility of AI generated and human video doctors and the relationship to social media use.

作者信息

Liu Tao, Wang Peijia, Pan Deyin, Liu Ruixin

机构信息

Department of Cardiovascular Medicine, The Third Xiangya Hospital, Central South University, Changsha, China.

Faculty of Clinical Medicine, Changsha Medical University, Changsha, Hunan, China.

出版信息

Front Public Health. 2025 Jul 9;13:1559378. doi: 10.3389/fpubh.2025.1559378. eCollection 2025.

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 ( = -0·34,  < 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.

摘要

目的

年轻医生的年龄刻板印象是否也适用于人工智能(AI)医生尚不清楚。尽管研究表明社交媒体可以减少歧视,但年龄刻板印象仍未得到充分探索。本研究旨在确定在由AI/人类医生讲述的在线健康视频中,医生使用社交媒体与年龄刻板印象之间的关系。

方法

这是一项横断面研究,分为两个阶段,于2024年5月25日至6月19日进行。通过面对面访谈开发并收集自我报告问卷。所有18岁及以上且具备足够阅读理解能力的个体均符合条件。调查了AI和人类条件下在线健康视频参与者对医生的信任度及其与社交媒体使用强度的关系。使用单变量和多变量广义线性模型来探索社交媒体使用与年龄刻板印象之间的关系。

结果

我们在第一阶段和第二阶段分别获得了294份和300份有效问卷。在AI和人类条件下,患者都更倾向于由年长医生进行健康教育。年长医生被评为最可信(AI条件下中位数分数为14.00,四分位间距[12.00,15.00];人类条件下中位数分数为14.00,四分位间距[12.00,15.00])。单变量和多变量广义线性模型均显示社交媒体使用与年龄刻板印象之间存在显著负相关,尤其是在年长医生和年轻医生之间(β = -0.34,P < 0.001)。在AI条件下。在人类条件下,社交媒体使用强度与参与者的年龄刻板印象无关。

结论

AI医生的形象可以帮助患者避免受到年龄刻板印象的影响,使他们能够更客观地评估医生的医学专业知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1ab/12283982/51795f599885/fpubh-13-1559378-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验