Understanding the factors influencing health professionals' online voluntary behaviors: Evidence from YiXinLi, a Chinese online health community for mental health

Online Medical Consultation Service-Oriented Recommendations: Systematic Review

BACKGROUND

Online health communities (OHCs) have given rise to a new e-service known as online medical consultation (OMC), enabling remote interactions between physicians and patients. To address challenges such as patient information overload and uneven distribution of physician visits, OHCs should develop OMC-oriented recommenders.

OBJECTIVE

We aimed to comprehensively investigate what paradigms lead to the success of OMC-oriented recommendations.

METHODS

A literature search 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 healthcare-related recommendations for online services.

RESULTS

The search identified 313 articles, of which 26 met the inclusion criteria. Despite the growing academic interest in OMC recommendations, there remains a lack of consensus of e-service-oriented recommenders on their definition among researchers. The discussion highlights three key factors influencing recommender success: features, algorithms, and metrics. It advocates for moving beyond traditional e-commerce-oriented recommenders to establish an innovative theoretical framework for e-service-oriented recommenders and addresses critical technical issues in two-sided personalized recommendations.

CONCLUSIONS

The review underscores the essence of e-services, particularly in knowledge-intensive and labor-intensive domains like OMC, 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 two-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.

CLINICALTRIAL

A Study of Factors Influencing the Volume of Responses to Posts in Physician Online Community

Today's diverse health needs place greater demands on physicians. However, individual doctors have limited capabilities and may encounter many unsolvable medical problems. The physician online community provides a platform for physicians to communicate with each other and help each other. Physicians can post for help about problems they encounter at work. The number of responses to physicians' posts is critical to whether or not the problem is resolved. This study collected information on 13,226 posts from a well-known physician online community in China to analyze the factors that influence the number of post replies. In the analysis of the post content of the physician online community, this study innovatively introduces word usage features in the medical field. TextMind was used to extract the rate of several types of words in posts that frequently appear when describing medical information. Ultimately, we found that the rate of time words, visual words, auditory words, and physiological process words used in posts had a positive and significant effect on the number of post responses. A series of new post features has been found to have an impact on the number of post replies in physician online communities. This finding is beneficial for physicians to quickly obtain peer assistance through online platforms, increasing the likelihood of solving workplace challenges and improving physician care, as well as the success of physician online communities.

Patient Engagement as Contributors in Online Health Communities: The Mediation of Peer Involvement and Moderation of Community Status

This study focuses on patient engagement in online health communities (OHCs) and investigates the mechanism related to the impact of social support provided by patients on their personal engagement. Based on social support theory, we put forward a research model and conduct empirical analysis using datasets of 4797 patients with 160,484 posts and 1,647,569 replies from an online health community in China. The mediation of peer involvement and moderation of community status are also examined. The results indicate that the subdimensions of social support positively influence patient engagement with informational support exerting the greatest impact. Peer patient involvement imposes significant partial and positive mediating effects on the relationships, especially on informational support. Community status negatively moderates the impacts of social interactions and informational support on patient engagement in that the influence of social interactions and informational support are more profound for patients with low community status. The findings can bring an understanding of patient engagement in OCHs, and provide theoretical and practical implications to facilitate the development of an online healthcare service.

What makes helpful online mental health information? Empirical evidence on the effects of information quality and responders’ effort

Although online health communities are popular in supporting mental health, factors leading to the helpfulness of mental health information are still under-investigated. Based on the elaboration likelihood model and motivation theory, we incorporate two types of health information-related constructs, i.e., information quality (central route) and responders’ effort (peripheral route), and adopt reputation as an extrinsic motivation to build our model. We crawl data from a Chinese online mental health community and extract 11 key variables, and then analyze the model with negative binomial regression. The empirical results indicate that the effect of the length of health information on its helpfulness votes is positively significant, while the effect of readability of health information on its helpfulness votes is relatively negative. In terms of responders’ effort, both the timelines of the response and interactive feedback have a significant positive impact on helpfulness of health information votes, while these effects are negatively moderated by the online reputation of responders. This study contributes to the literature on information evaluation mechanisms in online health communities.

Encouraging physicians' continuous knowledge-sharing in online health communities: A motivational perspective

Online health communities (OHCs) as an essential means of patient education can significantly improve patients' health literacy and treatment outcomes. However, sustaining these social benefits brought by OHCs establishes the prerequisite that physicians can continuously share their knowledge on OHCs. Although previous studies have explored physicians' knowledge-sharing in OHCs, scholarly knowledge related to the means of motivating physicians to continue sharing their knowledge remains limited. Therefore, this study developed a research model based on motivation theory to explore the influence of practical benefits, psychological rewards, and perceived connectedness with OHCs on physicians' continuous knowledge-sharing behaviors and the contingent role of physicians' online seniority status. The research model and relevant hypotheses were examined using objective data from one of the leading OHCs in China. The empirical results reveal that both practical benefits and psychological rewards positively affect physicians' continuous knowledge-sharing behaviors. However, an unexpected finding is that perceived connectedness is negatively associated with physicians' continuous knowledge-sharing behaviors. In addition, physicians' online seniority status strengthens the relationship between practical benefits and continuous knowledge-sharing behaviors but weaken the role of psychological rewards and perceived connectedness on continuous knowledge-sharing behaviors. This study contributes to the understanding of the motivational mechanisms underlying physicians' continuous knowledge-sharing behaviors in OHCs and provides significant practical implications for practitioners of OHCs.

Determining Factors Affecting the Users' Participation of Online Health Communities: An Integrated Framework of Social Capital and Social Support

As the national awareness of health keeps deepening, online health communities (OHCs) have achieved rapid development. Users' participation is critically important to the sustainable development of OHCs. Nevertheless, users usually lack the motive for participation. Based on the social capital theory, this research examines factors influencing users' participation in OHCs. The purpose of this research is to find out decisive factors that influence users' participation in OHCs, enrich the understanding of users' participation in OHCs, and help OHCs address the issue of sustainable development. The research model was empirically tested using 1277 responses from an online survey conducted in China. Data was analyzed using the structural equation modeling (SEM). We found informational support and emotional support to have significant direct effects over the structural capital, relational capital and cognitive capital of OHCs. Meanwhile, it is observed that relational capital and cognitive capital degree have a significant influence on knowledge acquisition and knowledge contribution of OHCs. For researchers this study provides a basis for further refinement of individual models of users' participation. For practitioners, understanding the social capital is crucial to users' knowledge acquisition and knowledge contribution that achieve high participation in OHCs.

The Impact of Health Information Privacy Concerns on Engagement and Payment Behaviors in Online Health Communities

Online health communities (OHCs) have enjoyed increasing popularity in recent years, especially in the context of the COVID-19 pandemic. However, several concerns have been raised regarding the privacy of users’ personal information in OHCs. Considering that OHCs are a type of data-sharing or data-driven platform, it is crucial to determine whether users’ health information privacy concerns influence their behaviors in OHCs. Thus, by conducting a survey, this study explores the impact of users’ health information privacy concerns on their engagement and payment behavior (Paid) in OHCs. The empirical results show that users’ concerns about health information privacy reduce their Paid in OHCs by negatively influencing their OHC engagement. Further analysis reveals that if users have higher benefit appraisals (i.e., perceived informational and emotional support from OHCs) and lower threat appraisals (i.e., perceived severity and vulnerability of information disclosure from OHCs), the negative effect of health information privacy concerns on users’ OHC engagement will decrease.

Lurking or active? The influence of user participation behavior in online mental health communities on the choice and evaluation of doctors

BACKGROUND

Web-based psychological counseling sites have become an important source of health information and expert assistance. Although many studies have suggested the feasibility and effectiveness of online consultation, there is an insufficient understanding of the influence of the distinction of users' participation behaviors online on health behavior decision-making.

OBJECTIVE

This study aimed to investigate whether and how the differences in the online participation behaviors of users affect their doctor selection and evaluation characteristics.

METHODS

First, we collected information from 7,781 paid consultation clients from a professional mental health service platform in China. Effective indicators and variables were formed through data cleaning and classification. Next, we used a mixed methods research approach that included qualitative text analysis (topic and sentiment) and quantitative statistical analysis (ANOVA).

RESULTS

The ANOVA results show that differences in online participation behaviors (diving, searching and socializing) have a significant impact on doctor selection based on consultation price (F_7,780=6.05; P = 0.00), online service volume (F_7,780=4.76; P = 0.00), online reputation (F_7,780=4.30; P = 0.01) and online answers (F_7,780=5.76; P = 0.00). When evaluating doctors, the frequency of reviews (F_7,780=69.62; P = 0.00) and the average length of the text (F_7,780=15.33; P = 0.00) were significantly different among users. Two of the three topics, namely, service attitude (F_7,780=28.63; P = 0.00) and self-expression (F_7,780=40.83; P = 0.00), had significant effects. In addition, our results show that differences in participating behaviors have a significant impact on both the positive (F_7,780=7.30; P = 0.00) and negative (F_7,780=9.44; P = 0.00) emotions involved in evaluating doctors.

CONCLUSIONS

Our findings provide preliminary insights for establishing the relationship between users' online information behavior and health decision-making. Further research should be conducted to verify the validity of the results and help apply them to the design of personalized customized services for the users in an online health community.

Understanding Online Health Community Users’ Payment Intention

Users often lack the motivation to pay for health information and services in online health communities (OHC). This may undermine the sustainable development of OHC. Integrating both perspectives of perceived value and trust, this research identified the factors affecting OHC users’ payment intention. The results indicated that payment intention is influenced by both functional value and trust. Functional value includes price utility and information quality, whereas trust includes trust in doctors and trust in community. We did not find the effect of emotional value and social value on payment intention. The results imply that OHC need to create a trustworthy climate and offer utilitarian value to users in order to facilitate their payment intention.

Examining Different Factors in Web-Based Patients' Decision-Making Process: Systematic Review on Digital Platforms for Clinical Decision Support System

(1) Background: The appearance of physician rating websites (PRWs) has raised researchers’ interest in the online healthcare field, particularly how users consume information available on PRWs in terms of online physician reviews and providers’ information in their decision-making process. The aim of this study is to consistently review the early scientific literature related to digital healthcare platforms, summarize key findings and study features, identify literature deficiencies, and suggest digital solutions for future research. (2) Methods: A systematic literature review using key databases was conducted to search published articles between 2010 and 2020 and identified 52 papers that focused on PRWs, different signals in the form of PRWs’ features, the findings of these studies, and peer-reviewed articles. The research features and main findings are reported in tables and figures. (3) Results: The review of 52 papers identified 22 articles for online reputation, 15 for service popularity, 16 for linguistic features, 15 for doctor–patient concordance, 7 for offline reputation, and 11 for trustworthiness signals. Out of 52 studies, 75% used quantitative techniques, 12% employed qualitative techniques, and 13% were mixed-methods investigations. The majority of studies retrieved larger datasets using machine learning techniques (44/52). These studies were mostly conducted in China (38), the United States (9), and Europe (3). The majority of signals were positively related to the clinical outcomes. Few studies used conventional surveys of patient treatment experience (5, 9.61%), and few used panel data (9, 17%). These studies found a high degree of correlation between these signals with clinical outcomes. (4) Conclusions: PRWs contain valuable signals that provide insights into the service quality and patient treatment choice, yet it has not been extensively used for evaluating the quality of care. This study offers implications for researchers to consider digital solutions such as advanced machine learning and data mining techniques to test hypotheses regarding a variety of signals on PRWs for clinical decision-making.

Research on the Characteristics and Usefulness of User Reviews of Online Mental Health Consultation Services: A Content Analysis

Online consultation based on Internet technology is gradually becoming the main way to seek health information and professional assistance. Online user reviews, such as content reviews and star ratings, are an important basis for reflecting users' views on the effectiveness of health services. Here, we used user reviews related to online psychological consultation services for content feature mining and usefulness analyses. We used a professional online psychological counseling service platform in China to collect user reviews that were liked by users as a data sample for a content analysis. An LDA topic model, dictionary-based sentiment analysis, and the NRC Word-Emotion Association Lexicon were used to extract the topic, sentiment, and context features of the content of 4254 useful reviews, and the influence of these features on the usefulness of the reviews was verified by a multiple linear regression analysis. Our results show that the content of online reviews by psychological counseling users presented a positive emotional attitude as a whole and expressed more views on the process, effects, and future expectations of counseling than on other topics. There was a significant correlation between the topic, sentiment, and context features of a user review and its usefulness: reviews giving high scores and containing topics such as "ease emotions" and "consulting expectations" received more user likes. However, the usefulness of a review was significantly reduced if it was in existence for too long. This research provides valuable suggestions for understanding the needs and emotional attitudes of users with mental health problems in terms of online psychological consultation; identifying the factors that affect the number of likes a review receives can help platform users write better consultation evaluations and thereby provide greater usefulness. In addition, the use of online reviews generated by users for content analysis effectively supplements the current research on online psychological counseling in terms of data and methods.

The Impact of Signals Transmission on Patients' Choice through E-Consultation Websites: An Econometric Analysis of Secondary Datasets

(1) Background: The COVID-19 pandemic has dramatically and rapidly changed the overall picture of healthcare in the way how doctors care for their patients. Due to the significant strain on hospitals and medical facilities, the popularity of web-based medical consultation has drawn the focus of researchers during the deadly coronavirus disease (COVID-19) in the United States. Healthcare organizations are now reacting to COVID-19 by rapidly adopting new tools and innovations such as e-consultation platforms, which refer to the delivery of healthcare services digitally or remotely using digital technology to treat patients. However, patients' utilization of different signal transmission mechanisms to seek medical advice through e-consultation websites has not been discussed during the pandemic. This paper examines the impact of different online signals (online reputation and online effort), offline signals (offline reputation) and disease risk on patients' physician selection choice for e-consultation during the COVID-19 crisis. (2) Methods: Drawing on signaling theory, a theoretical model was developed to explore the antecedents of patients' e-consultation choice toward a specific physician. The model was tested using 3-times panel data sets, covering 4231 physicians on Healthgrades and Vitals websites during the pandemic months of January, March and May 2020. (3) Results: The findings suggested that online reputation, online effort and disease risk were positively related to patients' online physician selection. The disease risk has also affected patients' e-consultation choice. A high-risk disease positively moderates the relationship between online reputation and patients' e-consultation choice, which means market signals (online reputation) are more influential than seller signals (offline reputation and online effort). Hence, market signals strengthened the effect in the case of high-risk disease. (4) Conclusions: The findings of this study provide practical suggestions for physicians, platform developers and policymakers in online environments to improve their service quality during the crisis. This article offers a practical guide on using emerging technology to provide virtual care during the pandemic. This study also provides implications for government officials and doctors on the potentials of consolidating virtual care solutions in the near future in order to contribute to the integration of emerging technology into healthcare.

Users' Willingness to Share Health Information in a Social Question-and-Answer Community: Cross-sectional Survey in China

BACKGROUND

Social question-and-answer communities play an increasingly important role in the dissemination of health information. It is important to identify influencing factors of user willingness to share health information to improve public health literacy.

OBJECTIVE

This study explored influencing factors of social question-and-answer community users who share health information to provide reference for the construction of a high-quality health information sharing community.

METHODS

A cross-sectional study was conducted through snowball sampling of 185 participants who are Zhihu users in China. A structural equation analysis was used to verify the interaction and influence of the strength between variables in the model. Hierarchical regression was also used to test the mediating effect in the model.

RESULTS

Altruism (β=.264, P<.001), intrinsic reward (β=.260, P=.03), self-efficacy (β=.468, P<.001), and community influence (β=.277, P=.003) had a positive effect on users' willingness to share health information (WSHI). By contrast, extrinsic reward (β=-0.351, P<.001) had a negative effect. Self-efficacy also had a mediating effect (β=.147, 29.15%, 0.147/0.505) between community influence and WSHI.

CONCLUSIONS

The findings suggest that users' WSHI is influenced by many factors including altruism, self-efficacy, community influence, and intrinsic reward. Improving the social atmosphere of the platform is an effective method of encouraging users to share health information.

Not just for the money? An examination of the motives behind physicians’ sharing of paid health information

Online platforms make it possible for physicians to share online information with the public, however, few studies have explored the underlying mechanism of physicians’ sharing of paid health information. Drawing on motivation theory, this study developed a theoretical framework to explore the effects of extrinsic motivation, enjoyment, and professional motivation on the sharing of paid information, as well as the contingent role of income ratio (online to offline) and online reputation. The model was tested with both objective and subjective data, which contain responses from 298 physicians. The results show that extrinsic motivation, enjoyment, and professional motivation play significant roles in inducing physicians to share paid information. Furthermore, income ratio can moderate the effects of motives on paid information sharing. Besides, the effect of professional motivation can be more effective in certain situations (low-level income ratio or high online reputation). This study contributes to the literature on knowledge sharing, online health behaviour, and motivation theory, and provides implications for practitioners.

Seeking or contributing? Evidence of knowledge sharing behaviours in promoting patients' perceived value of online health communities

BACKGROUND

Health knowledge, as an important resource of online health communities (OHCs), attracts users to engage in OHCs and improve the traffics within OHCs, thereby promoting the development of OHCs. Seeking and contributing health knowledge are basic activities in OHCs and are helpful for users to solve their health-related problems, improve their health conditions and thus influence their evaluation of OHCs (ie perceived value of OHCs). However, how do patients' health knowledge seeking and health knowledge contributing behaviours together with other factors influence their perceived value of OHCs? We still have little knowledge.

OBJECTIVE

In order to address the above gap, we root the current study in social cognitive theory and prior related literature on health knowledge sharing in OHCs and patients' perceived value. We treat health knowledge seeking and health knowledge contributing behaviours as behavioural factors and structural social capital as an environmental factor and explore their impacts on patients' perceived value of OHCs.

DESIGN

We have built a theoretical model composed of five hypotheses. We have designed a questionnaire composed of four key constructs and then collected data via an online survey.

SETTING AND PARTICIPANTS

We have distributed the questionnaire in two Chinese OHCs. We obtained a sample of 352 valid responses that were completed by patients having a variety of conditions.

RESULTS

The empirical results indicate that health knowledge seeking and health knowledge contributing have positive impacts on patients' perceived value of OHCs. The impact of health knowledge seeking on patients' perceived value of OHCs is greater than the impact of health knowledge contributing. In addition, structural social capital moderates the effects of health knowledge seeking and health knowledge contributing on patients' perceived value of OHCs. It weakens the effect of health knowledge seeking but enhances the effect of health knowledge contributing on patients' perceived value of OHCs.

CONCLUSIONS

These findings contribute to the literature on patients' perceived value of OHCs and on the role of structural social capital in OHCs. For OHC managers, they should provide their users more opportunities to seek or contribute health knowledge in their communities.

IoT Based Health—Related Topic Recognition from Emerging Online Health Community (Med Help) Using Machine Learning Technique

The unprompted patient’s and inimitable physician’s experience shared on online health communities (OHCs) contain a wealth of unexploited knowledge. Med Help and eHealth are some of the online health communities offering new insights and solutions to all health issues. Diabetes mellitus (DM), thyroid disorders and tuberculosis (TB) are chronic diseases increasing rapidly every year. As part of the project described in this article comments related to the diseases from Med Help were collected. The comments contain the patient and doctor discussions in an unstructured format. The sematic vision of the internet of things (IoT) plays a vital role in organizing the collected data. We pre-processed the data using standard natural language processing techniques and extracted the essential features of the words using the chi-squared test. After preprocessing the documents, we clustered them using the K-means++ algorithm, which is a popular centroid-based unsupervised iterative machine learning algorithm. A generative probabilistic model (LDA) was used to identify the essential topic in each cluster. This type of framework will empower the patients and doctors to identify the similarity and dissimilarity about the various diseases and important keywords among the diseases in the form of symptoms, medical tests and habits.

Attraction, selection, and attrition in online health communities: Initial conversations and their association with subsequent activity levels

BACKGROUND

The effectiveness of online health communities (OHCs) for improving outcomes for health care consumers, health professionals, and health services has already been well investigated. However, research on determinants of OHC users' activity levels, what is associated with attrition or attraction to these communities, and the impacts of initial posts is limited.

OBJECTIVES

We sought to explore topic exchanges in OHCs and determine how users' initial posts and community reactions to them are associated with their subsequent activity levels. We also aimed to extend the theory of Attraction-Selection-Attrition for Online Communities (OCASA) to this area.

METHODS

We examined exchanges in a major Australian OHC for cancer patients, analyzing about 2500 messages posted over 2009-18. We developed a novel annotation scheme to examine new members' initial posts and the community's reactions to them.

RESULTS

The annotation scheme includes five themes: informational support provision, emotional support provision, requests for help, self-reflection & disclosures, and conversational cues. Initial conversations were associated with future activity levels in terms of active posting versus non-active engagement in the community. We found that most OHC members disclosed personal reflections to bond with the community, and many actively posted to the community solely to provide informational and emotional support to others.

CONCLUSION

Our work extends OCASA theory to bond-based contexts, presents a new annotation scheme for OHC support topics, and makes an important contribution to knowledge about the relationship between users' activity levels and their initial posts. The findings help managers and owners understand how members use OHCs and how to encourage active participation. They also suggest how to attract new members and minimize attrition among existing members.

Exploring the Factors Influencing Consumers to Voluntarily Reward Free Health Service Contributors in Online Health Communities: Empirical Study

BACKGROUND

Rewarding health knowledge and health service contributors with money is one possible approach for the sustainable provision of health knowledge and health services in online health communities (OHCs); however, the reasons why consumers voluntarily reward free health knowledge and health service contributors are still underinvestigated.

OBJECTIVE

This study aimed to address the abovementioned gap by exploring the factors influencing consumers' voluntary rewarding behaviors (VRBs) toward contributors of free health services in OHCs.

METHODS

On the basis of prior studies and the cognitive-experiential self-theory (CEST), we incorporated two health service content-related variables (ie, informational support and emotional support) and two interpersonal factors (ie, social norm compliance and social interaction) and built a proposed model. We crawled a dataset from a Chinese OHC for mental health, coded it, extracted nine variables, and tested the model with a negative binomial model.

RESULTS

The data sample included 2148 health-related questions and 12,133 answers. The empirical results indicated that the effects of informational support (β=.168; P<.001), emotional support (β=.463; P<.001), social norm compliance (β=.510; P<.001), and social interaction (β=.281; P<.001) were significant. The moderating effects of social interaction on informational support (β=.032; P=.02) and emotional support (β=-.086; P<.001) were significant. The moderating effect of social interaction on social norm compliance (β=.014; P=.38) was insignificant.

CONCLUSIONS

Informational support, emotional support, social norm compliance, and social interaction positively influence consumers to voluntarily reward free online health service contributors. Social interaction enhances the effect of informational support but weakens the effect of emotional support. This study contributes to the literature on knowledge sharing in OHCs by exploring the factors influencing consumers' VRBs toward free online health service contributors and contributes to the CEST literature by verifying that the effects of experiential and rational systems on individual behaviors can vary while external factors change.

Improving cancer survivors' e-health literacy via online health communities (OHCs): a social support perspective

PURPOSE

Cancer survivors should have adequate e-health literacy to help them better use online health information. Online health communities (OHCs) can offer cancer survivors different types of social support that can represent another resource to improve health outcomes. However, there is little knowledge of how these OHC are directly related to a cancer survivors' e-health literacy. This study explores how different types of social support in OHCs are associated with cancer survivors' e-health literacy.

METHODS

A questionnaire was developed to collect data from two Chinese OHCs used by cancer survivors. The questionnaire is composed of two parts: six sociodemographic variables (i.e., gender, age, city, education, tenure, and prior Internet experience), two scales for informational support behaviors (i.e., health knowledge seeking and provision of health knowledge), a measure of emotional support within such a setting, and a measure of e-health literacy. Based on 162 complete samples, we determined the measurement properties of the scales used, provided descriptive statistics on major sociodemographic variables and conducted bivariate and multivariable hierarchical regression.

RESULTS

For cancer survivors, females demonstrate higher levels of e-health literacy. Higher education level was related to higher e-health literacy. Health knowledge seeking, contributing to health knowledge, and emotional support were all positively associated with e-health literacy. The interaction effect between health knowledge and emotional support is positively associated with e-health literacy.

CONCLUSIONS

Informational support and emotional support, as two major subtypes of social support within resources available in OHCs, are positively associated with e-health literacy among cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Cancer survivors might benefit from an active strategy for improving personal e-health literacy that includes more active informational involvement and emotional support rather than a passive lurking through e-health information and seeking and reading postings in OHCs.

Exploring the Effect of Market Conditions on Price Premiums in the Online Health Community

Online health communities allow doctors to fully use existing medical resources to serve remote patients. They broaden and diversify avenues of interaction between doctors and patients using Internet technology, which have built an online medical consultation market. In this study, the theory of supply and demand was adopted to explore how market conditions of online doctor resources impact price premiums of doctors’ online service. Then, we investigated the effect of the stigmatized diseases. We used resource supply and resource concentration to characterize the market conditions of online doctor resources and a dummy variable to categorize whether the disease is stigmatized or ordinary. After an empirical study of the dataset (including 68,945 doctors), the results indicate that: (1) the supply of online doctor resources has a significant and negative influence on price premiums; (2) compared with ordinary diseases, doctors treating stigmatized diseases can charge higher price premiums; (3) stigmatized diseases positively moderate the relationship between resource supply and price premiums; and (4) the concentration of online doctor resources has no significant influence on price premiums. Our research demonstrates that both the market conditions of online doctor resources and stigmatized diseases can impact price premiums in the online medical consultation market. The findings provide some new and insightful implications for theory and practice.

The role of off-topic discussions in online health support groups: insights from a content analysis of an online rectal cancer group

PURPOSE

Both off-topic discussions and exchanges of social support are important to the success of online health support groups. Analyzing their relationship could enhance our understanding of the nature of helpful interactions in online cancer support groups and ways promoting their success.

METHODS

A total of 15,284 messages were collected and analyzed from an online support group for rectal cancer. Two coders coded and categorized the messages into 211 threads using directed content analysis and a social support classification system. The relationship between off-topic discussions and social support was explored using the quadratic assignment procedure.

RESULTS

There are 91 threads of off-topic discussions, 83 threads of informational support, 22 threads of emotional support, seven threads of tangible support, five threads of network support, and three threads of esteem support. More of the off-topic discussions are associated with more emotional and tangible support. Both off-topic discussions and informational support are mutually influenced by the mediating role of emotional support. In addition, off-topic discussions and network support are mutually influenced by the mediating role of emotional and tangible support, and off-topic discussions and esteem support are mutually influenced by the mediating role of tangible support.

CONCLUSIONS

Off-topic discussions directly or indirectly promote different types of social support in an online rectal cancer support group.