{"title":"网络健康社区中口碑学习对慢性病患者医师选择的影响机制：潜在Dirichlet分配分析和横断面研究","authors":"Linlin Han, Narongsak Tek Thongpapanl, Ou Li","doi":"10.1177/20552076251332685","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Word-of-mouth learning (WOML) plays a substantial role in patients' physician choice behavior. However, there is still a research gap in analyzing the mechanism of WOML on chronic disease patients' physician choice in online health communities (OHCs) considering individual differences.</p><p><strong>Objective: </strong>This study aims to develop a physician choice mechanism research model to reveal the influence of WOML on chronic disease patients' physician choice decision process from external interaction to internal cognition and emotion in OHCs based on social learning theory (SLT). The moderating effects of reasons for consultation and patients' demographic characteristics on the model's relationships were also explored.</p><p><strong>Methods: </strong>Guided by SLT, this study identified the external interaction factors and internal cognitive and emotional factors by analyzing 72,123 patients' online reviews based on a Latent Dirichlet Allocation model and developed the physician choice mechanism research model. The model was validated using structural equation modeling based on an online questionnaire survey of 526 valid Chinese patients with chronic disease. The moderating effect of reasons for medical consultation and demographic characteristics was examined using multi-group analysis.</p><p><strong>Results: </strong>Status capital (SC), decisional capital (DC), and price value (PV)) were the main external interaction factors to initiating chronic disease patients' internal cognition and emotion (perceived convenience (PC), perceived health benefits (PH), and patients' physician choice intention (CI)). PH and PC significantly mediated the relationship between SC, DC, PV, and CI. Reasons for medical consultation, district, and sex significantly moderated the relationships in the model.</p><p><strong>Conclusions: </strong>Considering individual differences, the results of this study advance a comprehensive understanding of how chronic disease patients interact with the environment through WOML to make physician choice decisions. OHCs can recommend suitable physician information to chronic disease patients considering individual differences to match patients' demands and improve service quality.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"11 ","pages":"20552076251332685"},"PeriodicalIF":2.9000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035117/pdf/","citationCount":"0","resultStr":"{\"title\":\"The mechanism of word-of-mouth learning on chronic disease patients' physician choice in online health communities: Latent Dirichlet allocation analyses and cross-sectional study.\",\"authors\":\"Linlin Han, Narongsak Tek Thongpapanl, Ou Li\",\"doi\":\"10.1177/20552076251332685\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Word-of-mouth learning (WOML) plays a substantial role in patients' physician choice behavior. However, there is still a research gap in analyzing the mechanism of WOML on chronic disease patients' physician choice in online health communities (OHCs) considering individual differences.</p><p><strong>Objective: </strong>This study aims to develop a physician choice mechanism research model to reveal the influence of WOML on chronic disease patients' physician choice decision process from external interaction to internal cognition and emotion in OHCs based on social learning theory (SLT). The moderating effects of reasons for consultation and patients' demographic characteristics on the model's relationships were also explored.</p><p><strong>Methods: </strong>Guided by SLT, this study identified the external interaction factors and internal cognitive and emotional factors by analyzing 72,123 patients' online reviews based on a Latent Dirichlet Allocation model and developed the physician choice mechanism research model. The model was validated using structural equation modeling based on an online questionnaire survey of 526 valid Chinese patients with chronic disease. The moderating effect of reasons for medical consultation and demographic characteristics was examined using multi-group analysis.</p><p><strong>Results: </strong>Status capital (SC), decisional capital (DC), and price value (PV)) were the main external interaction factors to initiating chronic disease patients' internal cognition and emotion (perceived convenience (PC), perceived health benefits (PH), and patients' physician choice intention (CI)). PH and PC significantly mediated the relationship between SC, DC, PV, and CI. Reasons for medical consultation, district, and sex significantly moderated the relationships in the model.</p><p><strong>Conclusions: </strong>Considering individual differences, the results of this study advance a comprehensive understanding of how chronic disease patients interact with the environment through WOML to make physician choice decisions. OHCs can recommend suitable physician information to chronic disease patients considering individual differences to match patients' demands and improve service quality.</p>\",\"PeriodicalId\":51333,\"journal\":{\"name\":\"DIGITAL HEALTH\",\"volume\":\"11 \",\"pages\":\"20552076251332685\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035117/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DIGITAL HEALTH\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/20552076251332685\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076251332685","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
摘要
背景：口碑学习（Word-of-mouth learning， WOML）在患者的医生选择行为中起着重要的作用。然而，在考虑个体差异的网络健康社区（online health communities, OHCs）中，WOML对慢性病患者医师选择的影响机制分析仍存在研究空白。目的：建立基于社会学习理论（SLT）的医生选择机制研究模型，揭示慢性疾病患者在职业健康中心从外部互动到内部认知和情绪的医生选择决策过程中，WOML的影响。探讨了就诊原因和患者人口学特征对模型关系的调节作用。方法：本研究以SLT为指导，基于潜狄利克雷分配模型，通过分析72,123例患者的在线评价，识别外部交互因素和内部认知和情感因素，建立医生选择机制研究模型。基于526名中国有效慢性病患者的在线问卷调查，采用结构方程模型对模型进行验证。采用多组分析检验就诊原因和人口统计学特征的调节作用。结果：状态资本（SC）、决策资本（DC）和价格价值（PV）是引发慢性疾病患者内部认知和情绪（感知便利（PC）、感知健康益处（PH）和患者医师选择意愿（CI））的主要外部交互因素。PH和PC显著介导了SC、DC、PV和CI之间的关系。就诊原因、地区和性别显著调节了模型中的关系。结论：考虑到个体差异，本研究的结果促进了对慢性病患者如何通过WOML与环境相互作用来做出医生选择决策的全面理解。健康中心可以根据个体差异向慢性病患者推荐合适的医师信息，匹配患者需求，提高服务质量。
The mechanism of word-of-mouth learning on chronic disease patients' physician choice in online health communities: Latent Dirichlet allocation analyses and cross-sectional study.
Background: Word-of-mouth learning (WOML) plays a substantial role in patients' physician choice behavior. However, there is still a research gap in analyzing the mechanism of WOML on chronic disease patients' physician choice in online health communities (OHCs) considering individual differences.
Objective: This study aims to develop a physician choice mechanism research model to reveal the influence of WOML on chronic disease patients' physician choice decision process from external interaction to internal cognition and emotion in OHCs based on social learning theory (SLT). The moderating effects of reasons for consultation and patients' demographic characteristics on the model's relationships were also explored.
Methods: Guided by SLT, this study identified the external interaction factors and internal cognitive and emotional factors by analyzing 72,123 patients' online reviews based on a Latent Dirichlet Allocation model and developed the physician choice mechanism research model. The model was validated using structural equation modeling based on an online questionnaire survey of 526 valid Chinese patients with chronic disease. The moderating effect of reasons for medical consultation and demographic characteristics was examined using multi-group analysis.
Results: Status capital (SC), decisional capital (DC), and price value (PV)) were the main external interaction factors to initiating chronic disease patients' internal cognition and emotion (perceived convenience (PC), perceived health benefits (PH), and patients' physician choice intention (CI)). PH and PC significantly mediated the relationship between SC, DC, PV, and CI. Reasons for medical consultation, district, and sex significantly moderated the relationships in the model.
Conclusions: Considering individual differences, the results of this study advance a comprehensive understanding of how chronic disease patients interact with the environment through WOML to make physician choice decisions. OHCs can recommend suitable physician information to chronic disease patients considering individual differences to match patients' demands and improve service quality.
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