Online Health Communities Research Articles

The beauty premium: Physicians’ facial expressions and patients’ selection and evaluation behavior in online health communities

BackgroundWith the development of information technology, online health communities (OHCs) are becoming an increasingly popular source of health information. ObjectivesWhile the impact of beauty has been extensively studied in various research fields, its role in OHCs has received little attention. This study aims to evaluate the effect of physicians’ appearance, smile, and positive emotions on patients’ selection and evaluation behavior in OHCs. Additionally, it explores the difference in the beauty premium among different types of physicians. MethodsOver 13,000 images of physicians and their relevant information were collected from the Good Doctor website, which is now China's leading OHC. We identified facial features in physicians’ photos based on deep learning and used Ordinary Least Squares (OLS) regression models to estimate the relationship between physicians’ facial expressions and patients’ behavior. We used PSM to address endogeneity issues and test the robustness of the results. ResultsThis study found that physicians’ appearance and smile positively impact patients’ selection and evaluation behavior, the results indicated that the beauty premium does exist in OHCs. In addition, heterogeneity analysis showed that the beauty of high titles, longer service duration of physicians has a greater influence on patients’ selection and evaluation behavior. ConclusionsThe beauty premium exists in OHCs. Therefore, this study provides new evidence on the impact of physicians’ facial attractiveness in OHCs and provides useful insights for patients, physicians, and platforms about the relationship between physician's structured or unstructured information and patients’ decision-making behaviors.

How do recommendations influence patient satisfaction? Evidence from an online health community

PurposeThis study aims to explore whether seeking recommendations for doctors from offline word-of-mouth or online reviews influences patient satisfaction after treatment, and how the source of recommendation affects this effect.Design/methodology/approachUsing a unique dataset of more than three million reviews from a popular Chinese online health community, this study used the coarsened exact matching method and built fixed-effect models to conduct empirical analysis.FindingsThe results suggest that selecting doctors according to recommendations can improve patient satisfaction and mitigate their dissatisfaction when encountering service failures. However, online recommendations were found to be less effective than offline sources in improving patient satisfaction.Originality/valueThis study provides important insights into patient satisfaction and doctor-patient relationships by revealing the antecedents of satisfaction and the potential for improving this relationship. It also contributes to the understanding of how recommendations in the healthcare context can improve patient satisfaction and alleviate the negative impact of service failures.

Online Medical Consultation Service-Oriented Recommendations: Systematic Review.

Online health communities have given rise to a new e-service known as online medical consultations (OMCs), enabling remote interactions between physicians and patients. To address challenges, such as patient information overload and uneven distribution of physician visits, online health communities should develop OMC-oriented recommenders. We aimed to comprehensively investigate what paradigms lead to the success of OMC-oriented recommendations. A literature search was conducted through e-databases, including PubMed, ACM Digital Library, Springer, and ScienceDirect, from January 2011 to December 2023. This review included all papers directly and indirectly related to the topic of health care-related recommendations for online services. The search identified 611 articles, of which 26 (4.3%) met the inclusion criteria. Despite the growing academic interest in OMC recommendations, there remains a lack of consensus among researchers on the definition of e-service-oriented recommenders. The discussion highlighted 3 key factors influencing recommender success: features, algorithms, and metrics. It advocated for moving beyond traditional e-commerce-oriented recommenders to establish an innovative theoretical framework for e-service-oriented recommenders and addresses critical technical issues regarding 2-sided personalized recommendations. This review underscores the essence of e-services, particularly in knowledge- and labor-intensive domains such as OMCs, where patients seek interpretable recommendations due to their lack of domain knowledge and physicians must balance their energy levels to avoid overworking. Our study's findings shed light on the importance of customizing e-service-oriented personalized recommendations to meet the distinct expectations of 2-sided users considering their cognitive abilities, decision-making perspectives, and preferences. To achieve this, a paradigm shift is essential to develop unique attributes and explore distinct content tailored for both parties involved.

Predicting the Information Need for Domestic Violence Survivors Based on the Fine-Tuned Large Language Model.

Women with domestic violence experiences often refuse to seek help face-to-face due to embarrassment. They begin to share their emotions and seek help from online health communities. Understanding and responding to these posts can be crucial in providing timely support to the victims. We proposed a fine-tuned large language model (LLM) capable of accurately predicting the informational need based on the content of postings. We fine-tuned the LAMMA2-7B-chat model based on the guidance of identifying the information need and a dataset comprising 273 posts from Reddit, which are manually annotated by domain experts. Furthermore, we evaluated the performance of our model using a random sample of 15 posts, and 66.6% were accurately predicted. The results demonstrate that our model can rapidly capture the information needs expressed in the posts, enabling healthcare providers to provide timely and useful support based on our predictions.

Online health communication

Online health communication

The effect of prosocial behavior and its intensity on doctors’ performance in an online health community

Online health communities (OHCs) are encouraging doctors to engage in prosocial behaviors to promote sustainable development of OHCs and benefit the user base, which may further influence doctor-level performance. However, it is unclear how prosocial behavior and its intensity affect doctor-level performance, such as doctor-patient relationship, online reputation, and online demand. The purpose of this study is to test the effects of prosocial behavior and its intensity on doctor-patient relationship, online reputation, and online demand. We conducted a series of empirical analyses on 103,208 doctor-level samples from a leading OHC in China. Initially, we applied the propensity score matching (PSM) method to obtain a more balanced sample, then, we employed a negative binomial regression model to analyze the sample after PSM, and finally, we performed a robustness test using a zero-inflated negative binomial regression model and changing the time window. Our research findings indicate that prosocial behavior positively affects the doctor-patient relationship, doctors’ online reputation, and online demand. The intensity of prosocial behavior has an inverted U-shaped relationship with the doctor-patient relationship, online reputation, and online demand. The doctor’s clinical title negatively moderates the effect of prosocial behavior on the doctor-patient relationship and online demand. Therefore, OHC operators can draw on our findings to encourage more doctors to engage in prosocial behavior while suggesting they consider the role of the intensity of prosocial behavior and clinical title.

Talking about pain plainly: authentic expression of pain management on Reddit

Verbal authenticity is the degree to which a person is monitoring self-expression that reflects one’s motivation. Though benefits of authentic expression are studied in interpersonal, social, and entrepreneurial success, few have explored authenticity within online health communities for social support and self-disclosure, especially when the health issues are stigmatized offline, such as living with chronic pain and opioid use. Given the health benefits authentic expression provides, the present study explored the discourse of pain management prevalent on Reddit.com and investigated the authentic expression patterns across its labeled communities: subreddits. Relevant messages (N = 57, 564) from posts and replies were collected and evaluated using the authenticity category developed by the Linguistic Inquiry and Word Count (LIWC) software. The analysis suggests that subreddits built for inviting inquiries such as “r/AskReddit” “r/AskDocs” had higher scores in terms of authentic expression, while others like “r/politics” “r/marvelstudios” had lower authenticity. Also, the more frequently a user posts and replies in a community, the more likely they expressed authentically for the post construction, but not for the reply authenticity. This study explicates the concept of authenticity by exploring what authentic expression means for health benefits in pain management. It also contributes to a growing body of studies focusing on the therapeutic effect of authentic expression in online health communities.

Paths of knowledge sharing of core and periphery users in online health communities: social support perspective

Paths of knowledge sharing of core and periphery users in online health communities: social support perspective

EPH32 Behaviors and Characteristics of Current and Previous Users of Glucagon-like Peptide-1 Receptor Agonists (GLP-1) in an Online Health Community

EPH32 Behaviors and Characteristics of Current and Previous Users of Glucagon-like Peptide-1 Receptor Agonists (GLP-1) in an Online Health Community

The Impact of Geographic and Social Proximity on Physicians: Evidence from the Adoption of an Online Health Community

The Impact of Geographic and Social Proximity on Physicians: Evidence from the Adoption of an Online Health Community

Developing an Online Health Community Platform for Facilitating Empowerment in Chronic Disease Prevention and Health Promotion.

This study aimed to develop an online health community platform for facilitating the empowerment of people with chronic diseases dwelling in the community regarding disease prevention and health promotion. The user-centered design approach included four main steps: (1) identifying the health problems and needs of target users, (2) developing the content of the platform, (3) constructing the platform, and (4) pilot testing, refinement, and finalization. An online health community platform available both in a mobile application and a Web-enabled application has been launched to facilitate empowerment and self-management by people with chronic conditions. The main components of the application comprised (1) screening for chronic diseases and health problems, (2) setting personal goals for health promotion and action planning to achieve the goals themselves, (3) offering an online health community with shared group goals that help users engage with their peers to attain their goals, and (4) creating one's own online health community and inviting others to participate. The platform has the potential to encourage people with chronic conditions to proactively engage in their own health promotion. Future studies are needed to determine the impact of the application on self-management and empowerment for its users.

EPH199 Social Determinants of Health Associated with Delayed Medical Care in an Online Health Community

EPH199 Social Determinants of Health Associated with Delayed Medical Care in an Online Health Community

Developing an Online Health Community Platform for Facilitating Empowerment in Chronic Disease Prevention and Health Promotion.

Developing an Online Health Community Platform for Facilitating Empowerment in Chronic Disease Prevention and Health Promotion.

Development of a User-friendly Health Promotion Website to Spread Evidence-based Information in Italy.

Appropriate communication models and strategies are crucial in order to strengthen preventive and health promotion interventions via digital platforms. Today, 52.23% of the Italian population use the Internet as a source of health-related information. The aim of the "Insegna Salute" project was to create a website that would enable people to satisfy their knowledge health needs and increase their awareness in the field of prevention. To develop the website, a qualitative literature research was carried out to collect an overview of effective online health communication strategies and tools before, during and after the COVID-19 pandemic. Further, we implemented the website insegnasalute.it according to the one-to-many (screen-to-face) communication model. The second part of the research focused on identifying tools to ensure the constant update of the platform. Finally, we proceeded with the creation of the visual identity. The research resulted in 28 sources regarding health communication, vaccine hesitancy, online health information seeking, visual identity, current digital and social trends and mis/disinformation. Many publications reported that healthcare professionals (HCPs) are the main providers of evidence-based information and the most effective agents against misinformation. Furthermore, most of the articles advocated the use of digital technologies, such as social media and websites, along with proactive and targeted communication strategies. Vaccination hesitancy and other health prevention issues require accurate tools to build trust-based relationships between users and healthcare professionals. In line with the preventive guidelines issued by the Italian Ministry of Health, new tools, such as "Insegna Salute", integrate health knowledge with communication strategies. In the wake of the COVID-19 pandemic, preventive measures are essential to protect the population from misinformation spread and the probability of getting ill.

Exploring the Impact of Online Medical Team Engagement on Patient Satisfaction: A Semantic Features Perspective.

Online medical teams (OMTs), a new mode of online healthcare service, have emerged in online health communities (OHCs) in China. This study attempts to explore the underlying mechanism of how OMTs' engagement influences patient satisfaction through the lens of semantic features. This study also scrutinizes the moderating effect of multiple specializations on the link between OMTs' engagement and semantic features. We utilized a linear model that had fixed effects controlled at the team level for analysis. A bootstrapping approach using 5000 samples was employed to test the mediation effects. The findings reveal that OMTs' engagement significantly improves language concreteness in online team consultations, which subsequently enhances patient satisfaction. OMT engagement has a negative impact on emotional intensity, ultimately decreasing patient satisfaction. Multiple specializations strengthen the impact of OMT engagement on both language concreteness and emotional intensity. This study contributes to the literature on OMTs and patient satisfaction, providing insights into patients' perceptions of OMTs' engagement during online team consultation. This study also generates several implications for the practice of OHCs and OMTs.

Information Seeking and Receiving of Older Adults with Diabetes in the Online Health Community: An Information Need Contextualization Perspective

ABSTRACT Online health communities (OHCs) are important online health communication channels for older adults with diabetes to access health information. When seeking health information, they often disclose a variety of contextual information (e.g., socio-economic situations) in their questions. Selective contextual information disclosure is a type of communication strategy for users in OHCs to elicit replies from others. In this study, we adopted text analysis to investigate what contextual information older adults with diabetes disclose to articulate their information needs and used the fixed-effect Poisson model to examine the relationships between different types of contextual information disclosure and informational support receipt. Our analyses were based on a dataset of 4,505 questions and corresponding replies from an online diabetes community. The results showed that cognitive information is the most frequently disclosed contextual information, while older adults tend to disclose demographic information in their questions less. Providing demographic and situational details in questions can enhance informational support receiving, resulting in an increased number of informational supports. However, disclosing cognitive, affective, informational channels, or support information does not significantly affect the informational support receiving. These findings can contribute to extending our existing understanding of information seekers’ communication strategies in OHCs.

How patients with chronic disease create value in online health communities? A mixed methods study from social technical perspective

How patients with chronic disease create value in online health communities? A mixed methods study from social technical perspective

Online groups show how technology supports healthcare needs for patients and families: an illustrative model for COPD facebook groups

Introduction:This study examines how online technologies can support patients and their families address specific medical needs by creating an integrated theoretical framework based on the Health Belief Model, Social Exchange Theory, and Technology Acceptance Model.Methods:We obtained a total of 264 responses from an online survey posted in several COPD Facebook groups. After data preprocessing, we were left with 155 responses that met our inclusion criteria. Using the Partial Least Squares-Structural Equation Model (PLS-SEM), we evaluate how individuals in Chronic Obstructive Pulmonary Disease (COPD) Facebook groups seek information.Results:This study examines the relationship between demographic variables, psychological attributes (including emotional support and self-worth), perceived disease severity, benefits and barriers, and the perceived utility and ease of internet use in the information-seeking behavior of COPD patients on Facebook.Discussion:The findings underscore the importance of ease of internet use and intuitive platform design as a critical determinant that positively affects user engagement and fosters active participation among online participants. These findings offer critical insights into how online communities help patients and families obtain broad support and enhance the adoption and acceptance of emerging healthcare technologies. This also shows the advantages that online platforms offer individuals managing chronic diseases. Given these insights, we urge healthcare providers to recognize the beneficial effects of online health communities on patient well-being and health outcomes. This understanding is essential for healthcare professionals seeking to enhance patient care, aiming to improve the quality of life for individuals with chronic diseases in an increasingly digital landscape.

The impact of doctors' facial attractiveness on users' choices in online health communities: A stereotype content and social role perspective

This study examines the impact of doctors' facial attractiveness on users' choices in online health communities (OHCs). We conducted a field study using a sample of 14,897 doctors registered on a Chinese OHC. The results indicate a significant negative relationship between the facial attractiveness of doctors and the number of visits to their homepage by users. However, this relationship only holds true for male surgeons and female internal medicine doctors, not for female surgeons or male internal medicine doctors. These findings suggest the possible presence of gender-specialty bias in the influence of facial attractiveness on patients' decision-making. To further investigate how facial attractiveness influences users' inclination to choose a particular doctor, we develop our research model drawing upon the stereotype content and social role perspective. Through a laboratory experiment, we found that OHC users' perceptions of doctors' warmth and competence act as mediating factors in the relationship between facial attractiveness and user choice. Additionally, this relationship is influenced by stereotypical gender-specialty fit.

Patient influencer: the impact of homophily on value co-creation behaviour in online health communities

ABSTRACT The world has witnessed a rapid rise of online health communities (OHCs) where patients can create a powerful network of support and resources to make a meaningful difference in people’s health lives. Despite this rapid rise, healthcare authorities and organisations are under enormous pressure to create a sustainable environment for OHCs. Prior studies revealed that encouraging patient value co-creation behaviour (VCB) is substantially beneficial for successful OHCs; however, what factors influence these patient behaviours to co-create value is still unknown. To fill this gap, this study uses the service-dominant logic perspective of value co-creation theory and discloses how homophily between patient influencers and patients in OHCs effect VCB. The data was collected through a self-administered survey from 422 patients who are users of OHC in China and was analysed via partial least squares structural equation modelling and fuzzy set qualitative comparative analysis (fsQCA). The results revealed that homophily positively influences VCBs, i.e. participation behaviour (PB) and citizenship behaviour (CB). A parasocial relationship only moderates the relations between homophily and (PB), whereas the influencer ethical interaction capability significantly moderates the relationship of both homophily with patient PB and CB. Furthermore, the fsQCA findings signify the robustness of the study model.