患者、医生和系统产生内容对患者择医行为的影响

Influence of Patient-Generated,Doctor-Generated,and SystemGenerated Content on Patients′ Behavior of Selecting Doctors

在线健康社区的发展为患者提供了改善医疗服务效率的机会,越来越多的患者通过在线健康社区进行在线咨询。由于医患之间存在信息不对称,患者如何确定医生质量并选择合适的医生进行在线咨询已成为重要的研究问题。已有研究探讨了参与者行为对患者择医行为的影响,但较少有研究同时考虑多元参与者产生的内容对患者择医行为的作用。基于信号理论、在线反馈机制和信任源理论,从患者、医生和平台管理者的视角,探讨患者产生内容(信息反馈和规范反馈)、医生产生内容(能力信任、善意信任和诚实信任)、系统产生内容(系统推荐)对患者择医行为的影响机制以及疾病风险的调节作用,在此基础上构建患者择医行为研究模型。选取20种疾病,将其分为高风险和低风险两种类型。从好大夫在线抓取6659名医生的相关信息作为研究数据,采用743498条在线评论的情感分析结果表示信息反馈,通过Spss 22.0的分层回归方法进行实证分析。研究结果表明,信息反馈、规范反馈、能力信任、善意信任、诚实信任和系统推荐对患者择医行为产生积极影响,患者可以依据参与者产生的内容选择医生。患者产生内容是强信号,并且与医生产生内容和系统产生内容存在替代关系。患有高风险疾病的患者在能力信任对患者择医行为的影响中有积极的调节作用,在信息反馈、规范反馈、善意信任、诚实信任和系统推荐对患者择医行为的影响中没有显著的调节作用。研究结果扩展了在线健康社区中患者择医行为影响机制的研究,考虑了多元参与者产生内容的替代关系以及疾病风险的调节作用,加深了对在线健康社区的理解,帮助患者选择合适的医生进行自我健康管理,并为在线健康社区的平台管理者完善网站设计等提供实践支持。

The development of the online health community provides patients with the opportunity to improve the efficiency of medical services with an increasing number of patients conduct online consultation through online health community.Due to the information asymmetry between doctors and patients,how patients determine the doctors′quality and choose the right doctors for online consultation has become an important research issue.Existing studies have explored the impact of participant behavior on patients′behavior of selecting doctors,yet few studies have considered simultaneously the content generated by multiple participants on patients′behavior of selecting doctors.Based on signal theory,online feedback mechanism,and trust source theory,we investigate the influencing mechanism of patient-generated content(information feedback,normative feedback),doctor-generated content(ability,goodwill,disclosure),and system-generated content(recommendation)on patients′behavior of selecting doctors,and the moderating effect of disease risk from the perspective of patients,doctors,and platform managers.This study puts forward research hypotheses and establishes a research model of patients′behavior of selecting doctors on this basis.Selecting 20 kinds of disease types which were divided into high-risk and low-risk types,we crawl 6659 doctors′relevant information of Good Doctor Online as the research data.The emotional analysis results of 743498 online comments are used to represent the information feedback.Then we use the hierarchical regression method of Spss 22.0 to run the empirical analysis.The results show that informational feedback,normative feedback,ability,goodwill,disclosure,and recommendation have a positive impact on patients′behavior of selecting doctors.Patients can choose doctors according to the contents generated by multiple participants.Patient-generated content is a strong signal,which has a substitute effect on doctor-generated content and system-generated content.Patients with high-risk diseases have a positive moderation relationship in the impact of ability on patients′behavior of selecting doctors,yet there is no significant moderation relationship in the impact of information feedback,normative feedback,goodwill,disclosure,and recommendation on patients′behavior of selecting doctors.The study expands the researches on the influencing mechanism of patients′behavior of selecting doctors in the online health community,considers the substitution relationship of multiple participants and the moderation effect of disease risk,and deepens the understanding of the online health community.Our conclusion helps patients choose appropriate doctors for selfhealth management and provides practical support for the platform managers of the online health community to improve the website design.