The beauty premium: Physicians’ facial expressions and patients’ selection and evaluation behavior in online health communities

IF 3.4 3区 医学 Q1 HEALTH POLICY & SERVICES Health Policy and Technology Pub Date : 2024-08-13 DOI:10.1016/j.hlpt.2024.100895
Yanbin Yang, Chengyu Ma, Haopeng Liu
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Abstract

Background

With the development of information technology, online health communities (OHCs) are becoming an increasingly popular source of health information.

Objectives

While the impact of beauty has been extensively studied in various research fields, its role in OHCs has received little attention. This study aims to evaluate the effect of physicians’ appearance, smile, and positive emotions on patients’ selection and evaluation behavior in OHCs. Additionally, it explores the difference in the beauty premium among different types of physicians.

Methods

Over 13,000 images of physicians and their relevant information were collected from the Good Doctor website, which is now China's leading OHC. We identified facial features in physicians’ photos based on deep learning and used Ordinary Least Squares (OLS) regression models to estimate the relationship between physicians’ facial expressions and patients’ behavior. We used PSM to address endogeneity issues and test the robustness of the results.

Results

This study found that physicians’ appearance and smile positively impact patients’ selection and evaluation behavior, the results indicated that the beauty premium does exist in OHCs. In addition, heterogeneity analysis showed that the beauty of high titles, longer service duration of physicians has a greater influence on patients’ selection and evaluation behavior.

Conclusions

The beauty premium exists in OHCs. Therefore, this study provides new evidence on the impact of physicians’ facial attractiveness in OHCs and provides useful insights for patients, physicians, and platforms about the relationship between physician's structured or unstructured information and patients’ decision-making behaviors.

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美丽溢价:在线健康社区中医生的面部表情与患者的选择和评价行为
背景随着信息技术的发展,在线健康社区(OHCs)正成为越来越受欢迎的健康信息来源。研究目的虽然美貌的影响已在多个研究领域得到广泛研究,但其在 OHCs 中的作用却鲜有人关注。本研究旨在评估医生的外表、微笑和积极情绪对患者在 OHC 中的选择和评价行为的影响。方法:我们从中国领先的在线健康门户网站--好大夫网站上收集了超过 13,000 张医生照片及其相关信息。我们基于深度学习识别了医生照片中的面部特征,并使用普通最小二乘法(OLS)回归模型估计了医生面部表情与患者行为之间的关系。结果本研究发现,医生的外表和微笑对患者的选择和评价行为有积极影响,结果表明在 OHC 中确实存在美丽溢价。此外,异质性分析表明,职称越高、服务时间越长的美女医师对患者的选择和评价行为影响越大。因此,本研究为OHC中医生面部吸引力的影响提供了新的证据,并为患者、医生和平台了解医生的结构化或非结构化信息与患者决策行为之间的关系提供了有益的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Health Policy and Technology
Health Policy and Technology Medicine-Health Policy
CiteScore
9.20
自引率
3.30%
发文量
78
审稿时长
88 days
期刊介绍: Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics
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