In recent years, the number of online health communities (OHCs) has increased rapidly as more patients seek to access alternate sources of health information and connect with other patients who have similar health concerns. However, insufficient attention has been paid to investigating user identities in OHCs. To address this potential research gap, by elaborating on the communication theory of identity, this study presents a multi-layered framework to analyze the different layers of user identities that are portrayed in OHCs. Through coding analysis, we discovered that the personal-layer identities that appear in OHCs are patients, partners, offspring, parents, friends and relatives, and others. Moreover, a series of detection models for the personal-layer identities of users were developed, which incorporated content features into machine learning approaches, and they achieved F1-scores above 0.88. Furthermore, we analyzed the features of enactment-layer identities presented by users’ posting behavior and content and the impact of the personal-layer identities of users on the features of the enactment-layer identities. The findings suggested that the features of the enactment-layer identities differed significantly among users with diverse personal-layer identities in terms of both behaviors and communication needs. Users who were identified as patients served as both information seekers and providers, whereas users with the personal-layer identities of parents tended to engage in the community continuously. Our findings extend the understanding of user identities within the context of OHCs.

近年来，随着越来越多的患者寻求访问其他健康信息来源并与其他有类似健康问题的患者联系，在线健康社区 (OHC) 的数量迅速增加。然而，对调查 OHC 中的用户身份没有给予足够的重视。为了解决这一潜在的研究空白，本研究通过详细阐述身份的传播理论，提出了一个多层框架来分析 OHC 中描绘的不同层次的用户身份。通过编码分析，我们发现OHCs中出现的个人层身份有患者、伴侣、后代、父母、亲友等. 此外，还开发了一系列针对用户个人层身份的检测模型，将内容特征融入机器学习方法中，F1-scores 均在 0.88 以上。此外，我们分析了用户发布行为和内容所呈现的制定层身份特征以及用户个人层身份对制定层身份特征的影响。研究结果表明，在行为和沟通需求方面，具有不同个人层身份的用户的制定层身份特征存在显着差异。被确定为患者的用户既是信息寻求者又是提供者，而具有父母个人层身份的用户倾向于持续参与社区活动。