The impact of doctors' facial attractiveness on users' choices in online health communities: A stereotype content and social role perspective

IF 6.7 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Decision Support Systems Pub Date : 2024-05-06 DOI:10.1016/j.dss.2024.114246

Xing Zhang , Yuanyuan Wang , Quan Xiao , Jingguo Wang

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Abstract

This study examines the impact of doctors' facial attractiveness on users' choices in online health communities (OHCs). We conducted a field study using a sample of 14,897 doctors registered on a Chinese OHC. The results indicate a significant negative relationship between the facial attractiveness of doctors and the number of visits to their homepage by users. However, this relationship only holds true for male surgeons and female internal medicine doctors, not for female surgeons or male internal medicine doctors. These findings suggest the possible presence of gender-specialty bias in the influence of facial attractiveness on patients' decision-making. To further investigate how facial attractiveness influences users' inclination to choose a particular doctor, we develop our research model drawing upon the stereotype content and social role perspective. Through a laboratory experiment, we found that OHC users' perceptions of doctors' warmth and competence act as mediating factors in the relationship between facial attractiveness and user choice. Additionally, this relationship is influenced by stereotypical gender-specialty fit.

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医生的面部吸引力对在线健康社区用户选择的影响：刻板印象内容和社会角色视角

本研究探讨了医生的面部吸引力对在线健康社区（OHC）用户选择的影响。我们以在中国某在线健康社区注册的 14,897 名医生为样本进行了实地研究。结果表明，医生的面部吸引力与用户访问其主页的次数之间存在明显的负相关关系。然而，这种关系只适用于男性外科医生和女性内科医生，而不适用于女性外科医生或男性内科医生。这些发现表明，面部吸引力对患者决策的影响可能存在性别-专业偏见。为了进一步研究面部吸引力如何影响用户选择特定医生的倾向，我们从刻板印象内容和社会角色的角度出发，建立了我们的研究模型。通过实验室实验，我们发现在面部吸引力与用户选择之间，OHC 用户对医生的热情和能力的感知是中介因素。此外，这种关系还受到性别-专业契合度刻板印象的影响。

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来源期刊

Decision Support Systems 工程技术-计算机：人工智能

CiteScore

14.70

自引率

6.70%

发文量

119

审稿时长

13 months

期刊介绍： The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).