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Background: Recent years have seen a rapid growth in the number of online health communities targeted at patients with long-term conditions. Myasthenia Gravis (MG) is a rare neurological disease for which such communities have not been analysed before. The aim of this study was to better understand the needs of the MG population through the collation and categorisation of questions that users of MG social media were asking fellow users on these platforms. Methodology: Systematic observation of four MG Facebook groups was conducted over a 2-month period. Groups were selected for analysis based on the following systematic criteria: Language (English), Membership (≥ 5,000 members), group activity (≥ 2 posts per week), target audience (general MG population) and researcher engagement with group administrators. The study protocol was reviewed by the institutional review board of the Charité--Universitätsmedizin Berlin (EA2/106/22). During the observation period, data were extracted from individual posts featuring questions made across each group using a systematic and objective coding scheme. All data points were coded directly from the source and collated into an SPSS database (IBM SPSS V.27, SPSS). Absolute and relative frequencies were calculated for categorical variables and proportions were compared across groups to validate the credibility and relevance of different requests. Results: Of the 2,062 posts observed (N = 2,062), 1,392 featured questions (n = 1,392). Questions were asked by 787 unique users: 531 were identified as one-time users (67%) and 256 were identified as repeat users (33%). Six hundred and fifty six users were classified as presumed diagnosed (83%), 61 as seeking diagnosis (8%), 69 as family and/or friends (9%) and as other (<0%). Eight unique categories of questions were observed including MG treatment (31%), Symptoms (19%), Living with MG (12%), Diagnosis (10%), non-MG medication (11%), Tests (8%), Location (4%) and Other (4%). Conclusion: Members of the MG population make active use of online health communities to seek and discuss practical information concerning various aspects of the disease, its diagnosis and care. The openness and willingness of the sample population to share sensitive medical information shows a high need for information not entirely catered to by the medical profession. [ABSTRACT FROM AUTHOR]

In online health communities based on doctor-doctor interactions, the sustained participation of doctors in information exchange within the community is not only crucial for the long-term development of online health communities but also contributes to enhancing the knowledge and professional capabilities of doctors across different regions. The purpose of this study is to explore the antecedents and consequences of information exchange behaviour among doctors. We collected interaction data among doctors from an online health community in China and utilised text mining to process unstructured data. This study employed a combination of econometric methods and generalised random forests to examine the causal mechanisms between antecedents and consequences of doctors’ information exchange behaviour. The results indicate that social capital and group characteristics have significant effects on information exchange behaviour, which in turn has significant positive effects on social benefits. In addition, the positive relationship between doctor information exchange and social benefit is higher in the clinical medicine discussion group. Information exchange behaviour mediates the relationship between group characteristics, social capital, and social benefits. Our study enriches the application of theories, deepens the understanding of social benefits, and is conducive to the stable and rapid development of online health communities based on doctor-doctor interactions. [ABSTRACT FROM AUTHOR]

Online health communities (OHCs) are able to facilitate social support exchange among people with similar health concerns, and the relationship between self-disclosure and social support exchange has been widely discussed. Build upon the previous studies, we extend the seminal theory of reasoned action (TRA) in this research, through the adoption of an salient but understudied construct, user role, which captures user inclination toward providing or seeking social support, and further explore how it impacts OHC users' self-disclosure intention. We adopt a mixed methods approach including manual coding, machine learning algorithms, and econometric analyses, and investigate over 4 million posts over 17 years from a well-developed breast cancer OHC to uncover both direct and indirect effects of user role on OHC users' intention of future self-disclosure intention. The results reveal both the main and moderating effects of user roles regarding users' self-disclosure intention. First, user with a more clear intention of social support seeking or providing are more likely to disclose personal information. Second, the relative tendency of support provision magnifies the positive effects of attitudinal and normative factors toward future disclosure. We also discuss the findings and implications of the extended TRA framework to generate some actionable insights of OHC design. [ABSTRACT FROM AUTHOR]

As the global demand for healthcare services continues to grow, improving the efficiency and effectiveness of the healthcare ecosystem has become a pressing concern. Information systems are transforming the healthcare delivery process, shifting the focus of healthcare services from passive disease treatment to proactive health prevention and the healthcare management model from hospital-centric to patient-centric. This study focuses on reviewing research in IS journals on the topic of e-health and is dedicated to constructing a theoretical model of intelligent health to provide a research basis for future discussions in this field. In addition, as the innovation of intelligent healthcare services has led to changes in its elements (e.g., an increase in the number of stakeholders), there is an urgent need to sort out and analyze the existing research.

Research on online pornography abstinence movements has predominantly focused on men's perspectives, often within the context of the broader manosphere. This focus has overshadowed the unique experiences and viewpoints of women in these movements. Our study aimed to fill this gap by exploring women-centric perspectives in pornography abstinence forums, particularly Porn Free Women (r/pornfreewomen). Using a mixed methods approach, this study examined the sexual scripts presented in women-dominated pornography abstinence communities. Our structural topic modeling analysis delineated the interplay of therapeutic, heteronormative, and empowerment themes that were evident in women's narratives and expressions. Further, our discourse analysis elucidated three specific scripts: the addiction script, the heterosexual script, and the liberation script. These interweaving narratives show that discussions of women's pornography abstinence are multifaceted and include a variety of perspectives to negotiate. These results contribute to a nuanced understanding of the values of health and well-being, sexual liberation, and feminism within women's pornography abstinence communities. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BackgroundRecent years have seen a rapid growth in the number of online health communities targeted at patients with long-term conditions. Myasthenia Gravis (MG) is a rare neurological disease for which such communities have not been analysed before. The aim of this study was to better understand the needs of the MG population through the collation and categorisation of questions that users of MG social media were asking fellow users on these platforms.MethodologySystematic observation of four MG Facebook groups was conducted over a 2-month period. Groups were selected for analysis based on the following systematic criteria: Language (English), Membership (≥ 5,000 members), group activity (≥ 2 posts per week), target audience (general MG population) and researcher engagement with group administrators. The study protocol was reviewed by the institutional review board of the Charité—Universitätsmedizin Berlin (EA2/106/22). During the observation period, data were extracted from individual posts featuring questions made across each group using a systematic and objective coding scheme. All data points were coded directly from the source and collated into an SPSS database (IBM SPSS V.27, SPSS). Absolute and relative frequencies were calculated for categorical variables and proportions were compared across groups to validate the credibility and relevance of different requests.ResultsOf the 2,062 posts observed (N = 2,062), 1,392 featured questions (n = 1,392). Questions were asked by 787 unique users: 531 were identified as one-time users (67%) and 256 were identified as repeat users (33%). Six hundred and fifty six users were classified as presumed diagnosed (83%), 61 as seeking diagnosis (8%), 69 as family and/or friends (9%) and as other (

IntroductionOnline health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users’ health decisions but also undermines social stability. It is of great significance to explore the factors that affect users’ ability to discern information in online health communities.MethodsThis study integrated the Stimulus-Organism-Response Theory, Information Ecology Theory and the Mindsponge Theory to constructed a model of factors influencing users’ health information discernment abilities in online health communities. A questionnaire was designed based on the variables in the model, and data was collected. Utilizing Structural Equation Modeling (SEM) in conjunction with fuzzy-set Qualitative Comparative Analysis (fsQCA), the study analyzed the complex causal relationships among stimulus factors, user perception, and the health information discernment abilities.ResultsThe results revealed that the dimensions of information, information environment, information technology, and information people all positively influenced health information discernment abilities. Four distinct configurations were identified as triggers for users’ health information discernment abilities. The core conditions included information source, informational support, technological security, technological facilitation, and perceived risk. It was also observed that information quality and emotional support can act as substitutes for one another, as can informational support and emotional support.DiscussionThis study provides a new perspective to study the influencing factors of health information discernment abilities of online health community users. It can provide experiences and references for online health community information services, information resource construction and the development of users’ health information discernment abilities.

Abstract Background With the growing availability of online health resources and the widespread use of social media to better understand health conditions, people are increasingly making sense of and managing their health conditions using resources beyond their health professionals and personal networks. However, where the condition is complex and poorly understood, this can involve extensive “patient work” to locate, interpret and test the information available. The overall purpose of this study was to investigate how women with polycystic ovary syndrome (PCOS) across two healthcare systems engage with online health resources and social media to better understand this complex and poorly understood lifelong endocrine disorder. Methods A semi-structured interview study was conducted with women from the US ( $$N=8$$ N = 8 ) and UK ( $$N=7$$ N = 7 ) who had been diagnosed with PCOS within the previous five years. Transcribed data was analysed using a reflexive thematic analysis method. Results We highlight the information needs and information-seeking strategies women use to make sense of how PCOS affects them, to gain emotional support, and to help them find an effective treatment. We also show how women with PCOS use online health and social media resources to compare themselves to women they view as “normal” and other women with PCOS, to find their sense of “normal for me” along a spectrum of this disorder. Conclusion We draw on previous models of sense-making and finding normal for other complex and sensitive health conditions to capture the nuances of making sense of PCOS. We also discuss implications for the design and use of social media to support people managing PCOS.

ABSTRACTObjective 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.

Purpose: This study aimed to assess the different needs of patients with breast cancer and their families in online health communities at different treatment phases using a Latent Dirichlet Allocation (LDA) model. Methods: Using Python, breast cancer-related posts were collected from two online health communities: patient-to-patient and patient-to-doctor. After data cleaning, eligible posts were categorized based on the treatment phase. Subsequently, an LDA model identifying the distinct need-related topics for each phase of treatment, including data preprocessing and LDA topic modeling, was established. Additionally, the demographic and interactive features of the posts were manually analyzed. Results: We collected 84,043 posts, of which 9504 posts were included after data cleaning. Early diagnosis and rehabilitation treatment phases had the highest and lowest number of posts, respectively. LDA identified 11 topics: three in the initial diagnosis phase and two in each of the remaining treatment phases. The topics included disease outcomes, diagnosis analysis, treatment information, and emotional support in the initial diagnosis phase; surgical options and outcomes, postoperative care, and treatment planning in the perioperative treatment phase; treatment options and costs, side effects management, and disease prognosis assessment in the non-operative treatment phase; diagnosis and treatment options, disease prognosis, and emotional support in the relapse and metastasis treatment phase; and follow-up and recurrence concerns, physical symptoms, and lifestyle adjustments in the rehabilitation treatment phase. Conclusion: The needs of patients with breast cancer and their families differ across various phases of cancer therapy. Therefore, specific information or emotional assistance should be tailored to each phase of treatment based on the unique needs of patients and their families. [ABSTRACT FROM AUTHOR]

Background: With the growing availability of online health resources and the widespread use of social media to better understand health conditions, people are increasingly making sense of and managing their health conditions using resources beyond their health professionals and personal networks. However, where the condition is complex and poorly understood, this can involve extensive "patient work" to locate, interpret and test the information available. The overall purpose of this study was to investigate how women with polycystic ovary syndrome (PCOS) across two healthcare systems engage with online health resources and social media to better understand this complex and poorly understood lifelong endocrine disorder. Methods: A semi-structured interview study was conducted with women from the US ( N = 8 ) and UK ( N = 7 ) who had been diagnosed with PCOS within the previous five years. Transcribed data was analysed using a reflexive thematic analysis method. Results: We highlight the information needs and information-seeking strategies women use to make sense of how PCOS affects them, to gain emotional support, and to help them find an effective treatment. We also show how women with PCOS use online health and social media resources to compare themselves to women they view as "normal" and other women with PCOS, to find their sense of "normal for me" along a spectrum of this disorder. Conclusion: We draw on previous models of sense-making and finding normal for other complex and sensitive health conditions to capture the nuances of making sense of PCOS. We also discuss implications for the design and use of social media to support people managing PCOS. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a qualitative study conducted in Italy about a peculiar online health community named #TERAPIADOMICILIARECOVID19 (#TDC19), which, since April 2020, has assisted people with COVID-19 with early-at-home therapy delivered by volunteer doctors, free of charge for patients. The aim of the paper was to analyse patients' motivations and strategies when negotiating risk in the context of this choice. Findings showed that patients' choices were the outcome of a process that forms an entangled ecology of care involving several dimensions, crossing micro, meso and macro levels: a) the process of knowledge-building by assessing mass-media, ascertaining the best protocol and recalling previous experiences with similar diseases; b) the experience of feeling abandoned by general practitioners (GPs) and healthcare institutions; c) the positive encounter with #TDC19's posts of gratitude written by people who were cured by #TDC19 doctors. In the end, patients' choice was not a leap of faith; they negotiated and balanced out the perceived risks associated with COVID-19 and with the possible available choices (GPs, do-it-yourself, #TDC19-doctors) based on a strategy that chiefly encompassed a blend of rational and in-between logics.

This study significantly contributes to both theory and practice by providing valuable insights into the role and value of healthcare in the context of online health communities. This study highlights the increasing dependence of patients and their families on online sources for health information and the potential of technology to support individuals with health information needs. This study develops a theoretical framework by analyzing data from a cross-sectional survey using partial least squares structural equation modeling and multi-group and importance–performance map analysis. The findings of this study identify the most beneficial technology-related issues, like ease of site navigation and interaction with other online members, which have important implications for the development and management of online health communities. Healthcare professionals can also use this information to disseminate relevant information to those with chronic illnesses effectively. This study recommends proactive engagement between forum admins and participants to improve technology use and interaction, highlighting the benefits of guidelines for effective technology use to enhance users' information-seeking processes. Overall, this study's significant contribution lies in its identification of factors that aid online health community participants in the information-seeking process, providing valuable information to professionals on using technology to disseminate information relevant to chronic illnesses like COPD. [ABSTRACT FROM AUTHOR]

IntroductionThe use of online follow-up services (OFUS) is becoming an increasingly important supplement to hospital care. Through OFUS, patients can find their doctors in online health communities (OHCs) and receive remote medical follow-ups after hospital treatment. However, the rate of effective use of OFUS by current patients is still low, and there is an urgent need for research to investigate the online information factors that affect patients' effective use of OFUS.MethodsBased on the elaboration likelihood model (ELM) of persuasion and an analysis of a panel dataset including 3,672 doctors in a leading OHC in China, this study explores how online information from doctors' knowledge contributions and patient feedback influences patients' effective use of OFUS.ResultsThe results show that both doctors' knowledge contributions and patient feedback positively influence patients' effective use of OFUS. Doctors' paid knowledge contributions and patients' paid feedback have stronger persuasive effects than doctors' free knowledge contributions and patients' free feedback, respectively. Moreover, there is a substitutional relationship between doctors' paid and free knowledge contributions and between patients' paid and free feedback in influencing patients' effective use of OFUS.DiscussionThe findings of this study suggest that OHC platforms and healthcare providers should account not only for the persuasive effects of doctors' knowledge contributions and patient feedback but also for influential differences and relationships between the types of doctors' knowledge contributions and patient feedback to better persuade patients to effectively use OFUS.

This article examines the impact of online health communities on the relationship between patients and physicians, specifically in Jordan. The study involved 61 patients from private hospitals in Jordan who were members of health communities on Facebook. The findings revealed that computer-mediated social support had a positive effect on the patient-physician relationship, while patient empowerment did not. The article suggests the need for online health community models in Jordan that can enhance patient-physician engagement and emphasizes the importance of patient empowerment and cultural considerations in these communities. The study was funded by INAYA MEDICAL COLLEGES, RIYADH, KSA. [Extracted from the article]

Social network analysis has been widely used in various fields including online health communities. However, it is still a challenge to understand how patients' individual characteristics and online behaviors impact the formation of online health social networks. Furthermore, patients discuss various health topics and form multiplex social networks covering different aspects of their illnesses, including symptoms, treatment experiences, resource sharing, emotional expression, and new friendships. Further research is needed to investigate whether the factors influencing the formation of these topic-based networks are different and explore potential interconnections between various types of social relationships in these networks. To address these issues, this study applied exponential random graph models to characterize multiplex health social networks and conducted empirical research in a Chinese online mental health community. An integrated social network and five separate health-related topic-specific networks were constructed, each with 773 users as network nodes. The empirical findings revealed that patients' demographic attributes (e.g., age, gender) and online behavioral features (e.g., emotional expression, online influence, participation duration) have significant impacts on the formation of online health social networks, and these patient characteristics have significantly different effects on various types of social relationships within multiplex networks. Additionally, significant cross-network effects, including entrainment and exchange effects, were found among multiple health topic-specific networks, indicating strong interdependencies between them. This research provides theoretical contributions to social network analysis and practical insights for the development of online healthcare social networks. [ABSTRACT FROM AUTHOR]

The growth of online health communities and socially generated health-related content has the potential to provide considerable value for patients and healthcare providers alike. For example, members of the public can acquire medical knowledge and interact with others online. However, the volume of information—and the consequent 'noise' associated with large data volumes—can create difficulties for users. In this paper, we present a data-driven approach to better understand these data from multiple stakeholder perspectives. We utilise three techniques—sentiment analysis, content analysis, and topic analysis—to analyse user-generated medical content related to Lyme disease. We use a supervised feature-based model to identify sentiments, content analysis to identify concepts that predominate, and latent Dirichlet allocation strategy as an unsupervised generative model to identify topics represented in the discourse. We validate that applying three different analytic methods highlights differing aspects of the information different stakeholders will be interested in based on the goals of different stakeholders, expert opinion, and comparison with patient information leaflets. [ABSTRACT FROM AUTHOR]

With the growing conflict between increased health awareness and the relative shortage of offline medical resources, online health communities (OHCs) have become an important resource for people seeking help with health difficulties. However, patients joining OHCs prefer to learn about health knowledge rather than to share. As a result, the supply and demand of health information in OHC are out of balance. We collected data from users of four major Chinese OHCs using a questionnaire survey to examine the knowledge sharing intention of OHCs users. A total of 324 cases were included in the final sample. We use structural equation modeling approach to test the proposed hypotheses. The results show that user environmental factors including informational support and emotional support affect trust toward members. Platform environmental factors including information quality and service quality affect trust toward community. Both trust toward members and trust toward community positively influence community commitment. Community commitment and trust toward members positively influence users' attitudes toward knowledge sharing. Both community commitment and attitude toward knowledge sharing have been proven to be strong predictors of knowledge sharing intentions. [ABSTRACT FROM AUTHOR]

Purpose: People with cancer routinely seek information and support in peer groups online. While peer communities constitute a major component of the health care landscape, they exist in isolation from clinical and research institutions. This study aimed to explore how and why cancer patients utilize online peer support groups and how they might be improved. Methods: A convenience sample of members of 6 closed Facebook cancer peer support groups (n = 291) participated in an online needs assessment survey. We further conducted semi-structured interviews with 14 members and 6 moderator-patients, hand-coding the free-text responses and interview transcripts. Results: Group participation was largely motivated by the desire to exchange information (79%) and to connect with others sharing the same condition (76%). Among study participants, 40% indicated they did not get information or support from any other online or offline organizations, 60% indicated they had few concerns with Facebook peer support groups, 84% indicated it was at least somewhat important that their health information and posts remain private, and 75% desired more input from experts in order to access evidence-based information and curb misinformation. About half wanted more group moderation, and moderators themselves expressed an urgent need for training and support. Conclusions: While online peer groups are a commonly utilized care component for many people with cancer or hereditary cancer risk and serve as a primary source of condition information, many participants desired more expert involvement in and moderation of groups. Privacy and security of health information was another key need expressed.

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.

As the economy and society develop and the standard of living improves, people's health awareness increases and the demand for health information grows. This study introduces an advanced BERT-LDA model to conduct topic-sentiment analysis within online health communities. It examines nine primary categories of user information requirements: causes, symptoms and manifestations, examination and diagnosis, treatment, self-management and regulation, impact, prevention, social life, and knowledge acquisition. By analyzing the distribution of positive and negative sentiments across each topic, the correlation between various health information demands and emotional expressions is investigated. The model established in this paper integrates BERT's semantic comprehension with LDA's topic modeling capabilities, enhancing the accuracy of topic identification and sentiment analysis while providing a more comprehensive evaluation of user information demands. This research furthers our understanding of users' emotional reactions and presents valuable insights for delivering personalized health information in online communities. [ABSTRACT FROM AUTHOR]

This study aims to provide a scientific mapping based on a bibliographic database of knowledge sharing in the health community of practice (CoP) and online health communities (OHCs). These online platforms have provided an efficient means for members to share best practices, expertise, and information on health-related matters and acquire knowledge in the fast-moving health and medical field. Applying a bibliometric method, this study contributes to the body of knowledge concerning health CoP function, capacity, and contribution. This study tends to uncover past themes (citation analysis), current themes (co-citation analysis), and predict trends (co-word analysis) on health CoP and OHCs perspectives. Findings indicate the imperative role of CoP in the field, mainly due to the rapid development of sophisticated tacit knowledge on complicated health issues and unpredictable diseases affecting public health. Implications on theory and managerial aspect to strengthen the function of CoP in providing optimum health service to the public is discussed. [ABSTRACT FROM AUTHOR]

Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors' consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients' information processing when choosing consultations. [ABSTRACT FROM AUTHOR]

The article considers the older people integration into online health communities. The author explored the role of such communities in constructing new types of sociality between older people, where online communities become intermediary actors structuring and changing the usual practices of everyday life and setting special context for older people’s communication. This study contributes to the study of the possibilities and limitations of online communities use in the context of the of older people lives with chronic illnesses in rural areas. For the people in focus, these communities can make up for the lack of communication often experienced by people who live in areas remote from major population centers and health centers. The importance of online communities is determined by the fact that it is often difficult for an older person in peripheral settlements to get the necessary advice or recommendation from a doctor, and communication in online health communities and medical forums compensates for this deficit, which is important in the treatment of the disease. Based on a study of groups of older people participating in online forums, different strategies for using online communities have been typified. In particular, three strategies have been identified: communication, using and observation. For each of them, the features of the use of online communities are outlined, as well as the role of such communities in everyday life. Usage and observation strategies are characterised by the fact that users are integrated into online communities mainly for treatment information and counselling, while for representatives of the communication strategy the communicative component is the most important, serving to discuss a variety of issues within rural life, including health, as well as therapeutic communication. This study contributes to the study of the possibilities and limitations of online communities in the context of the lives of older people with chronic illnesses in rural areas.

Dietary interventions are common but controversial treatments for autistic people. This study aims to understand the adoption of dietary interventions based on diffusion of innovations theory in the autism online community from four aspects: popularity, adoption process, the influence of opinion leaders, and post-adoption feedback. Our data was extracted from a Chinese autism community named Baidu Tieba autism forum. We applied a mixed-method including four analytical approaches: descriptive statistics for popularity analysis; machine learning models for automatic data classification and topic detection; social network analysis for exploring the influence of opinion leaders on the adoption phase; content analysis for revealing the family caregiver-reported feedback after adoption. Dietary interventions have become increasingly popular in the autism online community since 2018. Analysis of the adoption process revealed that family caregivers at different stages of adoption focused on different topics, and the number of interactions with opinion leaders had a significant effect on the highest level (p <.001) and stage span (p <.001) of health information adoption. According to findings from the feedback of family caregivers, the effects of dietary interventions varied from individuals with autism. Our study revealed the diffusion of unproven interventions, which is of great significance in promoting evidence-based practices. [ABSTRACT FROM AUTHOR]

Introduction: The use of online health communities (OHCs) for health information, disease self-management, and social support increased during the COVID-19 pandemic. However, there are limited data on the willingness of African American women (AAW) to participate in OHCs. Materials and Methods: A sample of 985 AAW completed an online survey. Multinomial logistic regression examined associations between three age groups (18–29, 30–50, and 51+ years) and 10 motivators and 10 barriers to participating in OHCs. Women 51+ years were the referent group. Results: Women 51+ years were more likely to have been diagnosed with obesity and hypertension than the other groups (p < 0.01), but less likely to be diagnosed with a mental health condition than the other groups (p < 0.01). The top 2 motivators were to learn about a disease/condition (70%) and to prevent a disease/condition (64%). There were no significant differences with these variables. However, compared with women 18–29 years of age, women 51+ years were more likely to be motivated to manage an illness (p < 0.001), and more likely than the other groups to be motivated to support others (p = 0.011). The top 2 barriers were being too busy (53%) and privacy concerns (45%). Compared with women in the two other groups, women 51+ years were more concerned about privacy (p < 0.001). Discussion: AAW expressed a willingness to participate in OHCs. Willingness to participate in OHCs will vary by the topic and disease/condition and the age group. Conclusions: Opportunities exist to recruit AAW in age-specific OHCs. [ABSTRACT FROM AUTHOR]

A significant number (49 %) of Indian users tend to rely on digital media to either access health-related information or use the internet as a precursor to visit a doctor [20]. According to a report by Raheja [48], "The Internet of Things" (IoT) connection has the potential to change the malfunctioning medical system into a comprehensive, effective, and individualised system. This will allow for a more proactive approach to wellness and overall health, reducing medical expenses through these inclusive practices. Online health communities in India demonstrate significant clout to transform the healthcare industry by empowering patients. They offer a platform to all key stakeholders, that are, the healthcare professionals, patients and even the caregivers alike, to come forth, share their experiences and develop remedies for various issues faced by the healthcare industry. This paper examines the antecedents involved in the empowerment of patients in Online Health Communities (OHCs) and the outcomes of this in the form of participant compliance. The research additionally examines the moderating impact of certain factors such as the patients' e-health literacy and health locus of control (HLOC) and the physicians' paternalism, in examining the relationship between patient empowerment and compliance. The findings of the research propose a construct or a theoretical model for the numerous factors and moderators associated with the patient's participation in online health communities. The social support available to patients leads to more empowered patients, ultimately resulting in higher Patient compliance. Further, this patient empowerment, which comprises of sense of autonomy, competence and self-efficacy makes people more compliant. The theoretical construct between patient empowerment and patient compliance, is further moderated by the patients' e-health literacy and health locus of control (HLOC) and the physicians' paternalism. [ABSTRACT FROM AUTHOR]

BackgroundAs a new type of medical service application for doctor-patient interaction, online health communities (OHCs) have alleviated the imbalance between the supply and demand of medical resources in different regions and the problems of “difficult and expensive access to medical care”, but also raised the concern of patients about the risk of disclosure of their health privacy information.MethodsIn this study, a dual-calculus model was developed to explore users' motivation and decision-making mechanism in disclosing privacy information in OHCs by combining risk calculus and privacy calculus theories.ResultsIn OHCs, users' trust in physicians and applications is a prerequisite for their willingness to disclose health information. Meanwhile, during the privacy calculation, users' perceived benefits in OHCs had a positive effect on both trust in doctors and trust in applications, while perceived risks had a negative effect on both trusts in doctors and trust in applications. Furthermore, in the risk calculation, the perceived threat assessment in OHCs had a significant positive effect on perceived risk, while the response assessment had a significant negative effect on perceived risk, and the effect of users' trust in physicians far exceeded the effect of trust in applications. Finally, users' trust in physicians/applications is a mediating effect between perceived benefits/risks and privacy disclosure intentions.ConclusionWe combine risk calculus and privacy calculus theories to construct a dual-calculus model, which divides trust into trust in physicians and trust in applications, in order to explore the intrinsic motivation and decision-making mechanism of users' participation in privacy disclosure in OHCs. On the one hand, this theoretically compensates for the fact that privacy computing often underestimates perceived risk, complements the research on trust in OHCs, and reveals the influencing factors and decision transmission mechanisms of user privacy disclosure in OHCs. On the other hand, it also provides guidance for developing reasonable privacy policies and health information protection mechanisms for platform developers of OHCs.

This study significantly contributes to both theory and practice by providing valuable insights into the role and value of healthcare in the context of online health communities. This study highlights the increasing dependence of patients and their families on online sources for health information and the potential of technology to support individuals with health information needs. This study develops a theoretical framework by analyzing data from a cross-sectional survey using partial least squares structural equation modeling and multi-group and importance–performance map analysis. The findings of this study identify the most beneficial technology-related issues, like ease of site navigation and interaction with other online members, which have important implications for the development and management of online health communities. Healthcare professionals can also use this information to disseminate relevant information to those with chronic illnesses effectively. This study recommends proactive engagement between forum admins and participants to improve technology use and interaction, highlighting the benefits of guidelines for effective technology use to enhance users’ information-seeking processes. Overall, this study’s significant contribution lies in its identification of factors that aid online health community participants in the information-seeking process, providing valuable information to professionals on using technology to disseminate information relevant to chronic illnesses like COPD.