Online Health Communities Research Articles

Equity and spatial accessibility of healthcare resources in online health community network

Introduction: This study investigates the geographical distribution and fractal characteristics of the medical service network in China, using the “Good Doctor website” as a case study.Methods: Data for this study were extracted from the Good Doctor website Health Community. A two-tiered hierarchical network model was developed to analyze the geographical distribution and fractal characteristics of the medical service network in China.Results: Results unveil the hierarchical nature of hospital distribution and the interconnectivity among healthcare institutions. Shandong Province as a central node within the national hospital network, and networks of secondary hospitals show significant self-similarity and scale-free properties.Discussion: The small world and fractal characteristics shed light on the rapid dissemination of medical information and the robustness of the healthcare network. The results offer a novel perspective for understanding and optimizing the distribution of medical resources, and help improve the efficiency of healthcare services supply.

Advice seekers’ legitimation strategies in online health communities

Previous studies of different online health communities have shown the importance of examining advice seekers’ legitimation strategies. However, most research has been based on the qualitative analysis of small samples from discussion threads. Using a specialized corpus comprising 1836 advice seekers’ initiating messages (317,540 words) and a corpus-assisted discourse analysis approach, this paper first identifies the recurrent lexicogrammatical patterns that advice seekers use and then connects these patterns to particular legitimation strategies according to the specific pragmatic functions they serve across texts. In this way, three major legitimation strategies are structurally classified with the identification of their typical lexicogrammatical realizations: justification of presence, amplification of details and evocation of feelings and emotions. Empirically, this corpus-based investigation complements previous qualitative research, extending prior findings drawn from small samples. Methodologically, this study demonstrates the potential value of investigating lexicogrammatical realization patterns using a corpus approach for exploring (online) health discourse.

Online social support exchange among medical travelers in South Asia: a content analysis of Facebook posts

ABSTRACT In recent years, more than half of the total medical travelers visiting India each year belong to Bangladesh. This study explores social support exchange in an online health community comprising participants who intend to travel/have traveled/are traveling from Bangladesh to India for medical reasons. We used thematic content analysis to classify social support into informational, emotional, and instrumental types. We found that informational support was the most commonly exchanged, indicating the high informational needs of medical travelers. Contrary to the existing literature, instrumental support, often related to urgent treatment needs, was exchanged more frequently than emotional support. This could be due to the resource constraints medical travelers face and the possibility of group members’ geographical connectivity. This study underscores the role of online platforms in facilitating the exchange of social support. It illuminates critical themes related to medical travel, enriching our understanding of this demographic's unique challenges and needs.

The Effect of Characteristics of Patient Communication on Physician Feedback in Online Health Communities: An Observational Cross-Sectional Study

ABSTRACT With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients’ rendered information positively influences the physicians’ text (α = 0.123, t = 33.147, P < .001) and voice feedback (β = 0.201, t = 40.011, P < .001). Patients’ hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients’ rendered information on physicians’ text feedback (α = –0.040, t = –24.857, P < .001; α = –0.048, t = –15.784, P < .001), whereas, it strengthened the effect of the amount of patients’ rendered information on physicians’ voice feedback (β = 0.033, t = 14.789, P < .001; β = 0.017, t = 4.208, P < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients’ presented information on physicians’ text and voice feedback (α = 0.023, t = 4.870, P < .001; β = 0.028, t = 4.282, P < .001). This research contributes to the development of computer-mediated communication theories and sheds light on service delivery in the online health community.

Fight against hair loss together: exploring self-disclosure and social support in an online hair loss support community

Purpose Hair loss is often overlooked but psychologically challenging. However, the emergence of online health communities provides opportunities for hair loss patients to seek social support through self-disclosure. Nevertheless, not all disclosures receive the desired support. This research explores what patients disclose within the community and how their health narrative (content, form and linguistic style) regarding self-disclosure influences the social support they receive.Design/methodology/approachThis study investigated a 13-year-old online support group for Chinese hair loss patients with nearly 240,000 members. Using structural topic modeling, Linguistic Inquiry and Word Count, and a negative binomial model, the research analyzed the content of self-disclosure and the interrelationships between social support and three narrative dimensions of self-disclosure.FindingsSelf-disclosures are classified into 14 topics, grouped under analytical, informative and emotional categories. Emotion-related self-disclosures, whether in content or effective word use, receive deeper social support. Longer and image-rich posts attract more support in quantity, but not necessarily in quality, while cognitive words have a limited impact.Originality/valueThis study addresses the previously overlooked population of hair loss patients within online health communities. It employs a more comprehensive health narrative framework to explore the relationship between self-disclosure and social support, utilizing unsupervised structural topic modeling methods to mine text. The research offers practical implications for how patients seek support and for healthcare professionals in developing doctor-patient communication strategies.

The moderating role of face on value co-creation behavior and co-creation attitude in online health communities

PurposeGiven the progressive rise of online health communities (OHC) that have predominantly changed health delivery services, healthcare organizations still face tremendous challenges of low patient participation and lack of high-quality contribution to OHC. Prior scholars indicated that inducing patient value co-creation behavior (VCB) is substantially beneficial for the sustainable growth of OHCs. However, what drives patients' behavior to co-create value is still unknown. To fill this important gap, this study used the service-dominant logic of value co-creation theory and face (mianzi in Chinese) literature to discover how patient co-creation attitude (CA) affects patient VCB. Also, this study aimed to explore the joint mechanism of how face gain (FG) and face loss (FL) impact patients' VCB in OHCs.Design/methodology/approachThe survey data of 322 patients actively using OHC in China were analyzed via partial least squares structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA).FindingsThe results revealed that patient CA positively influences VCB, that is participation behavior (PB) and citizenship behavior (CB). Face gain (FG) strengthens the impact of CA and patient PB and CB, whereas face loss (FL) weakens the impact of CA and patient PB and CB. Furthermore, the fsQCA findings signify the robustness of the study model.Originality/valueThis study explores the multifaceted mechanism of patient value co-creation in OHC and discloses the crucial role of face for the first time. Further, the novel findings of this study provide a robust framework for advancing the understanding of important drivers of patient VCBs that significantly helps healthcare service providers and OHC managers to sustain OHCs.

Continuance intention and digital health resources from the perspective of elaboration likelihood model and DART model: a structural equation modeling analysis.

Internet hospitals, online health communities, and other digital health APPs have brought many changes to people's lives. However, digital health resources are experiencing low continuance intention due to many factors, including information security, service quality, and personal characteristics of users. We used cross-sectional surveys and structural equation modeling analysis to explore factors influencing user willingness to continue using digital health resources. Information quality (β = 0.31, p < 0.05), service quality (β = 0.19, p < 0.05), platform reputation (β = 0.34, p < 0.05), and emotional support (β = 0.23, p < 0.05) have significant positive effects on user value co-creation behavior. Additionally, user trust and perceived usefulness could mediate the association between user value co-creation behavior and continuance intention, with mediation effects of 0.143 and 0.125, respectively. User involvement can positively moderate the association between user value co-creation behavior and user trust (β = 0.151, t = 2.480, p < 0.001). Also, user involvement can positively moderate the association between value co-creation behavior and perceived usefulness (β = 0.103, t = 3.377, p < 0.001). The keys to solving the problem of low continuance intention are improving the quality and service level of digital health resources, and promoting users' value co-creation behavior. Meanwhile, enterprises should build a good reputation, create a positive communication atmosphere in the community, and enhance user participation and sense of belonging.

Exploring the Impact of Medical Science Articles by Physicians on Their Online Consultation Volume in Online Health Community: The Mediating Role of Paid Feedback

Exploring the Impact of Medical Science Articles by Physicians on Their Online Consultation Volume in Online Health Community: The Mediating Role of Paid Feedback

The Influence of Internet-Derived Misinformation on Medical Treatment Decisions: A Social Learning Perspective

Purpose “Internet-Derived Information Obstructing Treatment” refers to the phenomenon where patients make their health decisions based on misinformation found online, leading to poor or harmful medical choices. DeGroot’s social learning model is used in this study to enquire at how false information spreads on the internet and influences people’s choices about treatment. We examine how likely patients will choose the wrong treatment, impacting their mental health, such as by making anxiety and depression symptoms worse. In addition, we examine the dynamics of low, high, and mixed levels of influence in the spread of false information. Methods We derived a mathematical framework to analyse the impact of peer-to-peer information sharing on medical decisions using DeGroot’s social learning model by modelling the process of belief updates in digital health networks. Each person’s decision-making is impacted by the views and information they encounter from others; this is known as the multiplier effect of social learning and is incorporated into the model. This method mimics the increasing likelihood that patients will encounter health-related disinformation as they engage with various online communities. Low misinformation influence, high misinformation influence, and mixed initial beliefs were the three scenarios that were modelled in the study. Treatment choices and mental health results were evaluated in light of each scenario. Based on patients’ exposure to false information through internet platforms, the odds ratios (ORs) for negative medical decisions, anxiety, and depression were computed. Results In all of these situations, people were much more likely to make a bad treatment choice when they had incorrect information. Repeated interactions with peers who had been influenced by online false information raised patients’ chances of making bad treatment choices by 50% in the high misinformation scenario (95% confidence interval [CI]: 1.25–1.80). Some patients who were given false information had 40% more anxiety and 35% more depression (OR: 1.40, 95% CI: 1.10–1.70 and OR: 1.35, 95% CI: 1.05–1.65, respectively). According to the model, social learning made false information more powerful, and this was most clear in situations where false information was common. Conclusion DeGroot’s social learning process is a good way to explain how false information found on the internet can affect a patient’s choice of treatment and mental health. Misinformation from the internet can lead to bad medical decisions and higher mental health risks, especially in networks where peers have a lot of power. The results stress the need for targeted interventions to improve digital health literacy and stop the spread of false information in online health communities. Future research should look into ways to stop the social learning processes that keep spreading false information.

The Role of Self-Determination Theory in Explaining Patients' Motivation to Continue Using Telemedicine in a Post-Pandemic World

COVID-19 has led to a considerable increase in telemedicine use by physicians and patients. However, usage is expected to decline post-pandemic despite the benefits in terms of convenience, reachability, accessibility, and cost. We are investigating antidotes to this supposed decline from the patient’s perspective: Which psychological needs and motivations may increase the patient’s satisfaction with telemedicine and her or his continuance intention? Our research combines the well-known Expectation-Confirmation Model (ECM) from satisfaction research with motivation antecedents and outcomes according to Self-Determination Theory (SDT). We developed and shared a self-administered questionnaire in online health communities. A patient sample (n = 464) participated in the survey. A subsample (n = 151) had experiences with medical teleconsultation or similar medical applications, whereas other patients (n = 313) with teleconsultations in administration, business, or education only. Overall, both subsamples reveal almost the same results. Perceived usefulness (e.g., time-saving and quick access to healthcare treatment) is the most important continuance intention predictor. However, psychological needs from SDT (e.g., perceived competence and perceived relatedness) also determine motivation, satisfaction, and continuance intention. The combination of ECM and SDT appears to lay the foundation for improved research for digitalized healthcare delivery. Further, both subsamples demonstrate high satisfaction with telemedicine. Nevertheless, telemedicine providers and marketers should carefully optimize the patient journey while minimizing patient waiting time and focus on understanding users’ health needs to differentiate their services in the market.

Health Communication Film Implementation Strategy COVID-19-era: The Turning T.I.D.E. in HIV Multimedia Research

Among public health and social behavioral scientists there is an emergent interest in using film-based methodologies to promote health and wellness. During the novel coronavirus disease 2019 (COVID-19), this research method, as well as other forms of research, were thwarted. This article reports on our experience of implementing an online health communication film intervention under a research design initially intended for in-person communal viewing. We investigated if the film-based intervention could enhance the uptake of therapeutic modalities first learned through a brief five week session for Black and Latine adults living with HIV. To address changes in research methods attributed to COVID-19, the T.I.D.E. implementation method includes four critical considerations: 1) T- Tenacious approach, increased level of persistence leveraging social and clinical supports, 2) I- Immediate Needs, connecting participants to needed community resources, 3) D- Dissemination Plan revamp and harness technology to share information, and 4) E- Environmental Awareness privacy protocol to strengthen trust by participants.

How patients evaluate physicians in live Video: An empirical study from a dual process perspective

Live diagnosis is an application of live streaming in online health communities, through which physicians share knowledge and interact with patients in real time. Live videos enable patients to evaluate physicians comprehensively before a paid consultation. By applying dual-process theory, we examine the relationships between physicians’ speech features, demographic characteristics, the information quality of live content in live videos and patients’ subscription and consultation behavior. Data from 992 physicians who provided live diagnoses were collected from an online health community. Results show that physicians’ speech features and live content quality are significantly associated with patients’ subscription behavior, which is further associated with their online consultation behavior. This study provides a new perspective for investigating patients’ consultation behavior in the online health community context. It enriches the application of dual-process theory, and offers implications for physicians and online health community administrators in providing better live diagnosis services.

The impact of electronic word-of-mouth on patients’ choices in online health communities: A cross-media perspective

Despite extensive research into electronic Word-of-Mouth (eWOM) in the healthcare sector, its impact on patients’ choice of online consultation in Online Health Communities (OHCs) remains largely unexplored. The current study aims to fill this research gap by investigating the heterogeneous effect of different eWOM characteristics on both OHCs and Social Networking Sites (SNSs) from a cross-media perspective. Drawing upon the Elaboration Likelihood Model (ELM) and cognitive cost model, a research model is proposed and hypotheses are examined employing data gathered from 8,472 physicians across two platforms. The findings indicate that both the quality and quantity of eWOM in OHCs positively affects patients’ choice of online selection, eWOM on SNSs is also positively related to patients’ choice. Additionally, eWOM on SNSs negatively moderates the relationship between eWOM quality in OHCs and patients’ choice, while eWOM on SNSs exhibits a U-shape moderating influence on the relationship between eWOM quantity in OHCs and patients’ choice.

A qualitative study investigating users’ perspective of bariatric surgery online health communities in facilitating social support

ABSTRACT Objective To fulfil a need for greater access to social support postoperatively, adults who have undergone bariatric surgery have turned to Online Health Communities (OHCs). Prior research has signposted the potential “functional” dimensions of social support found via OHCs. However, the “structural” dimensions experienced on OHC have yet to be explored. This study aimed to explore users’ experience of the “functional” and “structural” dimensions of social support facilitated within bariatric surgery OHCs. Methods Semi-structured interviews were conducted with 13 adults who were waitlisted or had undergone bariatric surgery. Data were analysed with both deductive and inductive methodologies utilised. Deductive analysis was mapped to social support theories thus themes reflect “informational”, “emotional”, “belonging”, and “tangible” social support. Results There were five subthemes generated under the theme of “informational” social support, two under “emotional” and “tangible” social support, and one under “belonging” social support. Participants believed that the “informal” structural support in their life was insufficient and a contributing factor to turning to OHCs. For some participants, “formal” structural social support was facilitated via OHCs; however, most were seeking different types of support than what they can receive from their medical support team. The inductive analysis generated two themes including “access to reliable social support 24/7” and “satisfied with the support available on OHCs”, highlighting key advantages and value of OHCs. Conclusions There seems to be value for OHCs in bariatric surgery for social support. However, fundamentally the shared experiences and “belonging” social support seem to be a linchpin for the success of OHCs.

Why are physicians willing to contribute knowledge? Evidence from online health communities

The sustainable development of an online health community (OHC) is inseparable from the contribution of physicians. Nevertheless, little research has systemically examined physicians' knowledge contribution behavior (KCB) in the OHC context. Drawing on social cognitive theory, this study proposes an empirical model for exploring the influence of environmental factors (material incentives and non-material incentives) and cognitive factors (psychological capital) on physicians' KCB. We collected data from 270 physicians providing services in OHCs to examine the proposed theoretical relationships and model. The findings suggest that physicians' KCB is influenced by different incentive types. Specifically, extrinsic rewards and thanks letters have a positive effect on physicians' KCB, while virtual gifts negatively affect physicians' KCB. However, intrinsic rewards have no motivating effect on KCB. In addition, psychological capital plays an important role in the relationship between incentives and KCB. Accordingly, these results underscore the need to distinguish the impact of different incentives on physicians' KCB. This study therefore broadens the research scope of social cognitive theory and enriches the extant results concerning KCB in OHCs. Our findings also have effective implications for OHC practitioners.

Do peers really influence doctors' knowledge contribution behavior? Evidence from online health communities

PurposeThe online health community's success depends on doctors' active participation, so it is essential to understand the factors that affect doctors' knowledge contribution behavior in the online health communities. From the perspective of peer effect, this paper discusses the influence of focal doctors' peers on focal doctors' knowledge contribution behavior and the mechanism behind it. This paper aims to solve these problems.Design/methodology/approachEmpirical data of 1,938 doctors were collected from a Chinese online health community, and propensity score matching and ordinary least squares were employed to verify the proposed theoretical model.FindingsThe results show that the presence of focal doctors' peers in online health communities has a positive effect on the knowledge contribution behavior of focal doctors, and the economic returns and social returns of focal doctors' peers have a significant mediating effect.Originality/valueThis paper discusses focal doctors' knowledge contribution behavior from the perspective of peer effect. It enhances the understanding of focal doctors' behavior in the online health communities by exploring the mediating role of their peers' economic and social returns. The results of this paper extend the research in the field of peer effect and online health and provide management implications and suggestions for online health platforms and doctors.

Medical practice in gamified online communities: Longitudinal effects of gamification on doctor engagement

Gamification is used to increase the engagement of doctors on online health platforms. We track 2,106 doctors from a leading online health community (Good Doctor) over one year to investigate how gamification features (i.e., how actively doctors embellish their profiles and how they perform in popularity indicators via points and virtual gifts received) affect doctors’ future health service provision. The results showed that gamification can lead to high long-term doctor engagement. Specifically, virtual gifts and points were positively associated with doctors’ instrumental and socio-emotional participation, whereas customization was positively associated with doctors’ instrumental participation.

Clinical and Economic Burden Among Patients with Chronic Lymphocytic Leukemia Using a Novel Real-World Patient-Centered Database

Introduction Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults, with an estimated 18,740 new cases of CLL in 2023. This study describes current treatment patterns, healthcare resource use (HCRU) and patient voice in patients with CLL in the US using a novel patient-centered database. Methods A retrospective study using data from the Inspire Integrated Analytical Database (IIAD), which links Inspire patient voice with electronic health records (EHR) and medical and pharmacy claims through HIPAA-compliant tokenization. Patients worldwide with various conditions join Inspire's online health community and contribute their experience through online posts and survey participation (see Figure 1). Medical and pharmacy claims in IIAD range from 2013 to present, with EHR data ranging from 2010 to present. Inspire members were included in the study if they resided in the US and had at least two diagnoses for CLL (ICD-10 codes C91.10, C91.11 or C91.12) on at least two distinct dates that were between 30 and 60 days of each other. The first observed CLL diagnosis date was considered the index date. Patients with an index date on or before 6/30/2022 were included in the analysis. Baseline patient characteristics and HCRU were evaluated. CLL treatment was identified from medical and pharmacy claims. Online posts which CLL patients have viewed at least once were evaluated. Post topics are defined as named entities recognized by Inspire's Natural Language Processing (NLP) engine from all of the discussion posts written by any Inspire members. Descriptive statistics were reported. Results A total of 331 CLL patients were identified in the online community with linked claims and EHR data. Median follow-up time was 59 months from index date. The median age at diagnosis was 73 and 49% of patients were female. Patients were geographically represented across the US. 63% had ≥100 claims from a median of 25 care sites across 33 providers. During follow-up a median of 3 hospitalizations per patient were observed. 5% of patients experienced a Richter's transformation and 22% developed a secondary malignancy (lung, gastrointestinal or skin cancer) after their index CLL date. 104 patients (31%) of the cohort had available data for CLL treatment. Median time to first CLL treatment was 11.7 months (range: 1 day - 86.8 months). Ibrutinib was the most common medication (n = 43), followed by venetoclax (n = 30) and rituximab (n = 20). The 5 most common topics viewed by patients on the Inspire community website included: skin, side-effect, muscle, biopsy, and infection. Prior to starting therapy, searches on the Inspire platform included terms such as “imbruvica,” “calquence,” and “living with CLL.” Searches after CLL treatment revealed that patients broadened search terms to include other cancer types such as “pelvic cancer,” “liver metastasis” and “melanoma.” Conclusions This report utilized a unique dataset that integrates patient voice with EHR and claims data to describe clinical characteristics, and treatment patterns of CLL patients drawn from the patient-centered Inspire digital health community. The online population had a median age of 73 at diagnosis, consistent with the average age of CLL diagnosis (70 yrs.). Patients in our cohort initiated treatment approximately 1 year after CLL diagnosis. Online activities on the Inspire platform demonstrated that CLL patients are engaged in searching and reading discussion posts concerning the impact of side effects and treatments on quality of life, and emphasized emerging concerns about the potential impact of secondary malignancies. Future real-world studies need to integrate patient voice to fully understand the consequences of a cancer diagnosis.

The dynamics of knowledge sharing in chronically ill patient-led online health communities.

Patient-led online health communities (OHCs) provide an accessible way for patients to share their knowledge without the constraints of time and distance. By sharing knowledge, patients receive information from other members of the community that expands their knowledge. In this way, knowledge 'grows' and enhances the ability of patients in the community to adequately self-care in everyday life, that is, patient empowerment. This paper aims to understand the dynamics of knowledge sharing in patient-led OHCs. In search of an answer to the research question, the virtual ethnography research design was applied using an observational data collection method. The observational research was conducted in five patient-led OHCs of chronically ill patients on the Lithuanian version of the Facebook Platform. The results of the study provided insight into the dynamics of knowledge sharing by detailing the design of the discussions that took place in the studied communities and by characterising the path of knowledge sharing.

Value creation for online collaboration between doctors and medical institutions: empirical evidence from online health communities

PurposeDoctor–medical institution collaboration (DMIC) services are an emerging service mode in focal online health communities (OHCs). This new service mode is anticipated to affect user satisfaction and doctors' engagement behaviors. However, whether and how DMIC occurs is still ambiguous because the topic is rarely examined. To bridge this gap, this study explores doctors' participation in DMIC services and its effects on their online performance, as well as its effect on patients' evaluation of them on OHC platforms.Design/methodology/approachThe authors propose hypotheses based on structural holes theory. A unique dataset obtained from one of the most popular OHCs in China is used to test the hypotheses, and difference-in-differences estimation is adopted to test the causality of the relationship.FindingsThe results demonstrate that providing DMIC services improves doctors' online consultation performance and patients' evaluations of them but has no significant effect on doctors' knowledge-sharing performance on OHC platforms. Doctors' knowledge-sharing performance and consultation performance mediate the relationship between participation in DMIC services and patients' evaluation of doctors. Regarding doctors' participation in DMIC services, its impact on doctors' consultation performance and patients' evaluation of them is weaker for doctors with higher professional titles than for doctors with lower professional titles.Originality/valueThe findings clarify the value creation mechanisms of online collaboration between doctors and medical institutions and thereafter facilitate doctors' participation in DMIC services and enhance the sustainable development of OHCs.