Purpose Physicians’ knowledge sharing behavior (KSB) is crucial to the sustainable development of the online health communities (OHCs). While online reputation is known to incentivize physicians, prior studies often treat it as a single-dimensional signal, this study aims to explore synergistic mechanisms from multiple sources such as patients, peers and systems. Design/methodology/approach A three-dimensional online reputation signal research model was constructed covering patients, peers and systems based on signaling theory and online reputation-related literature. By acquiring the objective data of 37,382 physicians on a Chinese OHC, the effect of different reputation signals on physicians’ KSB was empirically tested. Findings Both patient- generated and system-generated reputations promote KSB, but they act as substitutes. Peer-generated reputation negatively affects KSB, though system-generated reputation mitigates this effect. No significant interaction exists between patient and peer signals. Offline seniority strengthens the impact of online reputation on KSB. Originality/value This study reveals the direct and interactive effects of multi-source reputation signals in OHCs, offering a nuanced view of signaling complexity and practical insights for patients, physicians and OHCs.

Despite growing interest in online health communities (OHCs), prior studies report inconsistent findings regarding the factors that drive users' continuous engagement. Furthermore, little is known about the relative importance of these factors and their hierarchical interactions. To address these gaps, this study poses two research questions: What are the key determinants of continuous OHC usage, and how do these determinants interact within a hierarchical structure? We conducted a meta-analysis of empirical studies to extract 16 critical factors, and applied the FUZZY-DEMATEL-AISM method to construct a multi-layered framework capturing their interrelationships. The findings reveal that attitude functions as the most direct top-level determinant, while trust, perceived value, and self-efficacy serve as transitional drivers. In contrast, system quality, service quality, and technology anxiety form the foundational layer influencing user behavior. This study contributes to theory by elucidating the structural logic underlying OHC engagement and to practice by providing actionable insights for enhancing user retention and optimizing digital health platform design. The results offer a systematic roadmap for researchers and practitioners aiming to understand and improve sustained user participation in digital health communities.

The engagement behaviors and treatment barriers for depressed patients in an online health community: a pre-/post-treatment comparison.

Online health communities have evolved into digital marketplaces where physicians have to compete for patients. Existing research examines physician-patient dynamics through a patient-centric lens, treating physicians as passive recipients of ratings and reviews, while the strategic role of physician self-disclosure remains unexamined. This gap constrains a comprehensive understanding of how physicians can actively shape patient decisions, making the investigation of strategic self-disclosure imperative. This study aims to investigate the relationship between physician self-disclosure breadth (scope of information) and depth (detailed expertise) and patient decision-making, as well as whether regional digital health care level (DHL) moderates these relationships. We conducted a cross-sectional analysis of observational data to test these relationships. Data were collected from China's online health care platform Haodf from September to December 2024. Self-disclosure breadth (including clinical performance, academic experience, and social reputation), self-disclosure depth (including expertise coverage, richness, and granularity), and patient decision-making (total visits) were captured through manual content coding and quantitative measurement. We used structured content analysis to extract the disclosure components, informational scope, and descriptive details of each profile. Then, using validated operational formulas, we calculated the composite indices for disclosure breadth and depth based on the coded dimensions. The study generated 1798 final physician samples with complete data across 14 focal variables. The hypotheses were tested using an ordinary least squares regression model, and 4 robustness checks were conducted, including variable substitution and different resampling techniques. In the primary ordinary least squares regression models, self-disclosure breadth was significantly and positively associated with patient visits (β=0.255, 95% CI 0.054-0.456; P=.01), as was self-disclosure depth (β=0.098, 95% CI 0.030-0.167; P=.005). The breadth×DHL interaction was positive and significant (β=0.261, 95% CI 0.061-0.461; P=.01). Similarly, the depth×DHL interaction was positive and significant (β=0.070, 95% CI 0.002-0.138; P=.045). It should be noted that the association for self-disclosure breadth was stronger than that of self-disclosure depth. DHL strengthened the relationship between the disclosure strategies with patient visits. This contextual amplification indicates that DHL serves as a critical boundary condition, determining the degree to which physician self-disclosure strategies translate into patient acquisition outcomes. This study reconceptualizes physicians as strategic agents shaping patient decision-making through purposeful self-disclosure. Different from existing studies treating physicians as passive recipients of ratings and reviews, our research demonstrates that physicians can strategically shape patient acquisition through self-disclosure breadth and depth. This study brings new insights to digital health markets by demonstrating that self-disclosure operates as a viable patient acquisition mechanism, wherein the DHL acts as a critical boundary condition. The findings have real-world implications: (1) physicians can leverage evidence-based disclosure strategies, (2) platforms should implement context-adaptive features, and (3) policymakers should prioritize digital infrastructure investments to enhance physicians' competitive capabilities and patient decision-making quality.

The impact of online health communities on the mental health of support seekers of china’s diabetic patients from the perspective of social support theory

Purpose Existing research has provided limited insights into the dynamic mechanisms through which multiple signals are interpreted within online health communities (OHCs). This study attempts to initiate a more integrative understanding of the dynamic interaction effects between patient-generated signals (i.e. herding and word-of-mouth signals) and physician-generated signals (i.e. central effort and peripheral effort signals) on online physician consultations. Design/methodology/approach This study adopts a dynamic panel modelling approach, applying longitudinal data collected from 844 physicians from June to December 2020. Specifically, the two-step system, generalised method of moments (GMM) with instrumental variables and propensity score matching (PSM) were employed to estimate the proposed research model. Findings This research provides empirical evidence that the herding signal and the word-of-mouth (WOM) signal have a positive effect on physician consultations within OHCs. Our findings also demonstrate that the peripheral effort signal complements the effect of the WOM signal on physician consultations, whereas it substitutes for the influence of the herding signal on physician consultations. In addition, this study finds that the central effort signal substitutes the effect of the WOM signal on physician consultation as it intensifies. Originality/value This study contextualises and frames a multidimensional signal framework of the herding signal, the WOM signal, the central effort signal and the peripheral effort signal in OHCs, which augments the predominant applications of signalling theory in e-commerce contexts. Furthermore, this research broadens the theoretical comprehension of signalling theory by revealing the substitutive and complementary effects among these signals, particularly in a mixed signalling environment.

Sleep Apnea Hypopnea Syndrome (SAHS) is a prevalent sleep disorder associated with substantial health risks, highlighting the need for improved public awareness. This cross-sectional analysis systematically evaluated the quality of SAHS-related videos on YouTube, Bilibili, and TikTok. Of 903 videos initially identified, 227 met the inclusion criteria for analysis. Cross-platform comparisons revealed that long-form platforms hosted higher-quality content, whereas short-form platforms generated greater engagement despite lower informational integrity. This study reveals a structural disconnect between informational quality and audience engagement, consistent with theories of algorithmic filtering. While professional identity remains a reliable predictor of quality, user engagement is largely driven by peripheral cues rather than medical accuracy. This study further contributes to the theoretical understanding of online health communication by situating platform-specific patterns within broader frameworks of algorithmic curation, heuristic processing, and trust formation. By integrating these theoretical perspectives with empirical quality assessments, the study offers a conceptually grounded explanation for why medically accurate content often remains less visible within algorithmic media environments. These findings underscore the need for platform-specific interventions that integrate credibility signals into recommendation algorithms to mitigate the spread of low-quality health information.

ObjectiveAs Online Health Communities (OHCs) become increasingly integral to healthcare delivery, understanding how to actively engage physicians in value co-creation is a critical practical challenge. This study aims to investigate the mechanisms through which external stimuli influence physicians’ value co-creation behavior (VCB) in OHCs. Specifically, it examines the mediating role of risk–benefit perceptions and the moderating role of physicians’ digital competency in this relationship.MethodsA cross-sectional survey was conducted among physicians in China with experience in OHCs. Based on the SOR framework and perceived value theory, a research model was developed encompassing environmental, technological, patient, and platform stimuli. Data from 547 valid questionnaires were analyzed using partial least squares structural equation modeling to test the hypotheses.ResultsPerceived benefit exerted a positive effect on VCB, whereas perceived risk had a negative impact. With the exception of the non-significant negative effect of patient compliance on perceived risk, all external stimuli significantly influenced these perceptions. Digital competency significantly moderated these relationships, it enhanced the positive effect of perceived benefit on VCB, importantly, buffered the negative effect of perceived risk on VCB.ConclusionThis study reveals that physicians’ VCB is driven by a nuanced risk–benefit calculus influenced by multilevel external stimuli. Digital competency plays a vital empowering role, helping physicians leverage benefits and mitigate risks. For OHCs operators and policymakers, our findings underscore the necessity of building a trustworthy environment through policy support and security features, while simultaneously implementing targeted training programs to enhance physicians’ digital competency, thereby fostering a vibrant and sustainable online health ecosystem.

ObjectiveIncluding patients’ experience-based knowledge in the development of clinical and public health guidelines has been shown to enhance the quality, relevance, and applicability of guidelines. However, the meaningful and methodologically sound inclusion of patient experiences remains a challenge. This study aimed to showcase the potential of NLP methods as an innovative tool for guideline development to gain insights into patients’ experiential knowledge and to incorporate this into the guideline development process.MethodsFor the revision of the Dutch public health guideline for scabies, we analyzed patients’ experiences with scabies infestation shared on “dokter.nl”, the Netherlands’ largest online health community, between December 4, 2014, and May 19, 2023. Structural topic modelling was performed to discern thematic clusters from these patient experiences.ResultsWe obtained 5781 unique posts on scabies and identified 13 major themes raised in forum conversations. The most prevalent themes revolved around community support (11.2%), uncertainty about treatment plans (11.1%) and coping with itching (11%). Recognizing scabies, alternative remedies, and decontamination measures were also issues frequently raised. The analysis highlighted the burden of disease and treatment—particularly the psychosocial burden—associated with scabies. This offered guideline developers an unprecedented insight into patients’ experiences resulting in alterations to the Dutch public health guideline for scabies.ConclusionPrevious studies have highlighted the benefits of the integration of experiential knowledge for guideline development. Our study provides a novel method to make this type of knowledge accessible and usable for medical guideline development, without additionally burdening patients.

Including patients' experience-based knowledge in the development of clinical and public health guidelines has been shown to enhance the quality, relevance, and applicability of guidelines. However, the meaningful and methodologically sound inclusion of patient experiences remains a challenge. This study aimed to showcase the potential of NLP methods as an innovative tool for guideline development to gain insights into patients' experiential knowledge and to incorporate this into the guideline development process. For the revision of the Dutch public health guideline for scabies, we analyzed patients' experiences with scabies infestation shared on "dokter.nl", the Netherlands' largest online health community, between December 4, 2014, and May 19, 2023. Structural topic modelling was performed to discern thematic clusters from these patient experiences. We obtained 5781 unique posts on scabies and identified 13 major themes raised in forum conversations. The most prevalent themes revolved around community support (11.2%), uncertainty about treatment plans (11.1%) and coping with itching (11%). Recognizing scabies, alternative remedies, and decontamination measures were also issues frequently raised. The analysis highlighted the burden of disease and treatment-particularly the psychosocial burden-associated with scabies. This offered guideline developers an unprecedented insight into patients' experiences resulting in alterations to the Dutch public health guideline for scabies. Previous studies have highlighted the benefits of the integration of experiential knowledge for guideline development. Our study provides a novel method to make this type of knowledge accessible and usable for medical guideline development, without additionally burdening patients.

ABSTRACT Online Health Communities (OHCs) empower patients to gain insights into their conditions and treatments but may inadvertently increase medication non-adherence. Grounded in dual-factor theory, this study examines non-adherence as a behavioral transition driven by enabling and inhibiting factors. Using structural equation modeling on survey data from 487 Chinese OHC users, we investigated how informational and emotional support (enabling factors), in contrast to satisfaction and status quo inertia (inhibiting factors), influence the intention to switch to alternative regimens. Findings reveal that informational and emotional support from OHCs positively influence attitudes toward alternative regimens, thereby increasing medication non-adherence intention. Conversely, satisfaction with current prescriptions and inertia decrease medication non-adherence intention. Notably, inertia moderates this process by diminishing the impact of positive attitudes toward alternatives on non-adherence. These insights help healthcare providers better understand the influence of OHCs and develop strategies to encourage medication adherence and improve patient outcomes.

The spillover effect of participating in crowdsourcing contests: Empirical evidence from online health communities

Module-Targeted AI Chatbot Deployment and Counselors’ Prosocial Contributions in Online Health Community

What happens when the CDC stops posting about measles on social media? An exploratory analysis of social media coverage during the 2025 measles outbreak.

Purpose This paper aims to explore how the linguistic style of doctor live streaming titles influences patient engagement behavior in online health communities. Specifically, we developed a framework to investigate the impact of three linguistic styles (categorized into analytical, social interactive and psychological intimacy types based on media naturalness theory (MNT)) on patient engagement, moderated by title, disease privacy and title professionalism. Design/methodology/approach To empirically assess the proposed model, this study draws on data collected from online health platforms to examine how linguistic styles of live streaming titles influence patient engagement. Data are analyzed using negative binomial regression. Findings All three linguistic styles positively influence patient engagement behavior. Additionally, disease privacy and title professionalism significantly moderate these effects, revealing how language features interact with contextual factors to shape engagement. Research limitations/implications This research extends MNT to online health communication and highlights the strategic role of language in doctor-patient interactions. However, the study is limited to one platform type. Future research could explore other cross-platform comparisons. Practical implications Findings provide practical guidance for doctors and administrators to optimize live-stream titles by strategically using linguistic styles, particularly under high-privacy or high-professionalism scenarios, thereby boosting patient engagement. It also recommends integrating linguistic inquiry and word count-like tools into digital healthcare platforms for automated title optimization and enhanced patient interaction. Originality/value This study is among the first to examine linguistic styles in healthcare live streaming. It contributes to the literature by identifying specific language types that promote engagement and by applying MNT to a novel digital health setting.

Deciphering patient selection of physicians in online health communities: insights from a dual-path perspective

An increasing number of patients are opting to utilise online health communities as their access to healthcare. However, there is limited research on the factors influencing patient choice in online health communities. The aim of this study was to explore the impact of physicians' knowledge-sharing in online health communities on patient choice and to analyse the potential theoretical boundaries of the relationship. This study used data collected from a large online health community in China for empirical analysis to illustrate a nonlinear relationship between physicians' knowledge-sharing and patients' choices. We found there was an inverted U-shaped relationship between physicians' knowledge-sharing and patients' choices. Moreover, the physician's pricing marked the non-linear relationship even steeper. This research serves to enrich the existing literature concerning determinants of patient choice by investigating the nonlinear impact of physicians' knowledge-sharing. This study has important practical implications for improving the quality of online healthcare services and the physician-patient relationship.

Social media's rapid and widespread adoption has significantly altered daily lifestyle choices and health-related behaviors, particularly among young people. Social media platforms have become indispensable to modern society's personal and professional spheres because they provide spaces for information exchange, entertainment, virtual networking, and even career advancement. These platforms often have an impact on how today's youth express themselves, communicate, compare themselves to others, and make decisions about their health. Given this, the current study examines the effects of social media use on the physical and mental health of young people in Chhattisgarh. An organized interview schedule was used to gather the primary data. Purposive sampling was used to select 500 respondents from each division of Chhattisgarh in order to guarantee regional representation. Using structural equation modeling (SEM) for statistical analysis and hypothesis testing, the researcher was able to quantify the correlation between social media use and various aspects of health outcomes. The findings demonstrate that social media can be both a risk and an opportunity. On the one hand, social media provides health-related information, motivational fitness content, peer support, and online health communities that can promote positive behavioral changes. Over-engagement, however, increases the risk of sedentary lifestyles, sleep disorders, anxiety, and increased social comparison pressures, all of which are detrimental to the physical and mental health of young people. According to the study, social media platforms are powerful sociocultural spaces that actively shape the attitudes, behaviors, and lifestyles of young people in Chhattisgarh. In order to minimize health risks and maximize the benefits of technology-driven social engagement, the results emphasize the necessity of focused interventions, digital literacy, and balanced usage.

This article engages with rhetoric of health and medicine (RHM) scholarship on embodiment and expertise in online health communication to demonstrate how rhetorical tactics help patients make embodied health decisions. This study analyzes 320 online postings, 84 published narratives, 30 surveys and written reflections, and 10 interviews in an online health community for Asherman syndrome (AS), a rare illness that develops after reproductive surgery. The findings of this study highlight how patients incorporate online information into their decision-making practices by accumulating embodied knowledge, tailoring questions, insisting on specific treatments, and switching healthcare providers. This article argues that patients’ rhetorical tactics, when shared and accumulated over time, can transform treatment outcomes.

BackgroundInternet health care plays a crucial role in addressing the challenge of distributing high-quality medical resources and promoting the optimal allocation of these resources and health equity in China. Online medical consultation (OMC) plays a more significant role than online health information seeking (OHIS). Currently, the proportion of Chinese patients using OMC is low. Therefore, it is essential to enhance patient engagement with OMC and fully leverage the role of internet health care in optimizing the allocation of medical resources.ObjectiveThis study aims to explore the correlation mechanisms of online medical community users’ switching behaviors from OHIS to OMC.MethodsThis study is based on the knowledge-attitude-practice theory, which combines the social support theory and the health belief model to construct a research model of users’ willingness to transition from OHIS to OMC. The study adopts a questionnaire survey and structural equation modeling method to conduct an empirical study.ResultsGaining knowledge about information support has a significant positive impact on perceived susceptibility (β=.339, P<.001), perceived severity (β=.348, P<.001), and perceived benefits (β=.361, P<.001), while having a significant negative impact on perceived barriers (β=–.285, P<.001). Gaining knowledge about emotional support positively affects perceived susceptibility (β=.220, P<.001) and perceived benefits (β=.149, P<.01) but does not significantly influence perceived severity (β=–.006, P>.05) or perceived barriers (β=.099, P>.05). Perceived susceptibility (β=.123, P<.05), perceived severity (β=.174, P<.001), and perceived benefits (β=.273, P<.001) positively influence patients’ transition to online consultation behavior, whereas perceived barriers (β=–.112, P<.05) negatively impact this switch. In addition, we found that gaining knowledge about information support not only directly affects patients’ behavior in switching to online consultations but also impacts patients’ OMCs through perceived susceptibility (14.23%), perceived severity (13.17%), and perceived benefits (25.28%). In contrast, gaining knowledge about emotional support does not directly influence patient behavior transfer; it operates only through perceived susceptibility (46.95%) and perceived benefit (52.90%).ConclusionsThis study integrated the knowledge-attitude-practice framework, social support theory, and health belief model to uncover the internal logic of patients’ behavioral transfers within online health communities. It confirmed the mediating role of the cognitive-emotional dual-drive pathway and health beliefs. The findings provide a scientific basis for the functional design of online health care platforms and for precise health knowledge dissemination strategies.