Online Health Communities Research Articles

More knowledge, more choices? How peer recognition of physicians' knowledge sharing affect patients' consultation in online health communities.

The advent of telemedicine has revolutionized healthcare consultations, primarily due to the digital era and global health concerns. Online healthcare communities (OHCs) have emerged as platforms for physicians to share health-related articles, promoting digital public health awareness and knowledge dissemination. The continuous dissemination of health knowledge by physicians online is considered a crucial driving force in attracting patients to seek online consultations. Based on the elaboration likelihood model and the information overload theory, this study explores how persuasive messages from other patients' peer recognition, including knowledge popularity and attractiveness, affect patients' consultation decisions. Additionally, the study examines the three-way interaction between knowledge popularity, attractiveness, and quantity in shaping patient consultations. Using data collected from 2,676 physicians on haodf.com, this study established an ordinary least squares (OLS) regression model with time and city fixed effects to test the hypothesis. The results show that: (1) peer recognition (knowledge popularity and attractiveness) from other patients positively impacts patients' consultation; (2) knowledge attractiveness positively moderate the relationship between knowledge popularity and patients' consultation; (3) there is a three-way effect of knowledge popularity, knowledge attractiveness, and knowledge quantity on patients' consultation. Our findings offer valuable guidance for platform design and healthcare practitioners, boosting patient-physician engagement in online healthcare communities.

Welcome to #SpoonieTok: Understanding and supporting disability expertise storytelling abilities and collective information practices on TikTok and beyond

This work-in-progress poster explores individual and collective storytelling and information creation practices in chronic illness TikTok communities, with the ultimate goal to support these embodied, creative, and multimodal abilities on and off-app through codesigned storytelling support materials. Findings from ongoing data collection and grounded theory coding, include folks’ sharing of disability expertise: using platform features to visualize invisible disability; audio, visual, and community-specific mimetic options. Interviews with 11 community members illuminate how disabled creators on TikTok engage in algorithmically-mediated online health communities, which have slippery boundaries where information can be found serendipitously through algorithmic ranking, and foster opportunities to develop storytelling skills.

"Accepting the Poem of Destiny": Identity Reconstruction in a Chinese Online Depression Community.

As online health communities become important platforms for people with depression to express themselves, digital narratives provide a lens for understanding their identity work. Drawing on the communication theory of identity (CTI), this article explored the members' identity reconstruction by analyzing their narratives posted in a Chinese online depression community. The four levels of identities constructed by the members include "laggard" and "pioneer" at the personal layer, "idler" and "fighter" at the enacted level, "stress-maker" and "escaper" at the relational layer, and support providers and receivers at the communal layer. These identities at different levels usually interact in the narratives, showing that identity gaps exist among the members. The study shows that the members' autobiographical accounts of depression entail multiplicities and ambivalences, denying the dominant and stigmatizing representation of it by common sense and the media as a reductionist downward and one-way experience that is valueless and offers no possibility for personal growth. The findings regarding the communal level of identity show that narratives can help the narrators to create bonds of solidarity of an experience that is often marginalized.

Exploring Client Preferences for Psychological Counselors in a Chinese Online Health Community: Longitudinal Study.

Although online health communities are acknowledged for their role in bridging the supply-demand gap in mental health services, the client decision-making process in these environments remains underexplored. This study aimed to explore the impact of different signals presented on psychological counselors' home pages on clients' choices. Adopting signaling theory as the framework, this study classified information into online and offline signals and developed a theoretical model to examine client choice behaviors. We collected data from 487 psychological counselors in a leading Chinese online mental health community during March, June, September, and December 2023. Based on these data, we constructed a 4-period balanced panel dataset. A fixed effects model was used to analyze which signals influence clients' choices of psychological counselors. Regarding online signals, the service price (β=0.186, P<.001) and online reputation (β=0.489, P=.002) of psychological counselors positively influence clients' choices. Concerning offline signals, psychological counselors' practical experience (β=0.007, P<.001) is positively related to clients' choices. Moreover, the results indicate that the relationship between a counselor's prosocial behavior and clients' choices is not linear but rather exhibits an inverted U-shape. This study reveals that the varied information provided by psychological counselors has distinct impacts on clients' choices in online health communities. It broadens the application of signaling theory to online behaviors and emphasizes the importance of both online and offline signals. These insights offer strategic guidance for counselors and online platforms to better meet potential clients' needs by optimizing the information presented on psychological counselors' home pages.

Role of online health communities in patient compliance: a social support perspective

PurposeOnline health communities (OHC) can transform the healthcare industry, particularly in developing economies. Technology advancement and increased health literacy pave the way for these communities to become powerful tools for empowering patients. The purpose of this study was to empirically validate the linkages between social support and how it overarchingly influences patient compliance. Following social support theory, this study delineates how support from the community affects the patient–physician relationship (PERP) and consequently patient compliance regarding the treatment plan. This study also invents the role of patient trust in an OHC in moderating the relationship between PERP and engagement.Design/methodology/approachThis paper is based on social support and empowerment theories to investigate the importance of social support in improving patients’ health behaviours and health outcomes via patient empowerment, patient engagement and patient compliance. The authors surveyed users from three Facebook cancer communities in India to collect data. The authors used partial least squares structured equation modelling and necessary condition analysis (NCA) with 265 participants to support the proposed model.FindingsThe result demonstrates that PERP is a crucial factor for patient engagement in OHC, and patient engagement has a significant effect on patient compliance. The results also showed that trust was a significant moderator between PERP and engagement. The NCA analysis shows all the relationships are significant; however, emotional support is not a necessary condition for PERP.Research limitations/implicationsBy empowering cancer patients and enabling them to meet their emotional and informational needs through OHCs, the study model can aid in the development of solutions that will improve compliance with their treatment in an emerging economic context. The findings indicate the potential chain reaction of social support and PERP in online cancer health communities. This study also contributes to quantifying the social impacts of online healthcare services and how to enhance the healthcare compliance framework.Originality/valueThis study combines social support and empowerment theory with patient, physician, and technology to provide a fine-grained picture of PERP in OHC. It explains how social support in OHC promotes self-care behaviour. This linkage validation enables readers and the community at large to gain a more nuanced understanding of how social support – through PERP, engagement and trust – enables patient compliance using primary data.

“Giving them the best information I could with whatever I had at hand”. Physicians' online health communication practices in a post-normal science context

This study describes US-based physicians' online public communication practices, particularly on the social media platform Twitter/X, during the COVID-19 pandemic. We draw on 28 semi-structured interviews to examine how they responded to the unique COVID-19 context with respect to each of the four features of post-normal science (PNS): facts uncertain, values in dispute, stakes high, and decisions urgent. Our analysis reveals that the pandemic shifted what, why, and how physicians used the platform, and with whom they aimed to communicate. We discuss the implications of these changes in their online communication habits, discourses, and representations around social media as a reaction to the context of PNS brought about by the pandemic.

Myasthenia Gravis: utilising cross-platform quantitative content analysis to uncover and validate unmet needs.

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. 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. 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%). 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.

Are Multiple information sources better? The effect of multiple physicians in online medical teams on patient satisfaction

An emerging service model in online health communities (OHCs) is that of medical teams comprising multiple physicians who collaborate to offer diagnoses and recommendations to patients. Given its multiple information sources, this model has the potential to deliver high-quality services and enhance patient satisfaction. However, the effect of a wider range of information on patient satisfaction has yet to be empirically examined. Therefore, the current research aims to examine the effect of multiple sources of health-related information on the satisfaction of patients in OHCs. We construct a sample model and empirically test it using a dataset comprising 115,367 consultation records sourced from WeDoctor. The results show that responses from multiple physicians in OHC medical teams increase patient satisfaction. In addition, we explore the moderating effects of team composition and team replies. The results show that physicians with higher titles and affiliations with the same department and the same question's replies from multiple physicians all play a positive moderating role, while reply time plays a negative moderating role. This research enriches the existing literature by focusing on patient satisfaction in the context of OHCs and offers recommendations for research and practice.

Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA.

Online 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. This 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. The 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. This 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.

Patient-to-patient value co-creation in online health communities: a systematic literature review and research agenda

Purpose The idea of value co-creation involves the benefit actors gain from integrating resources through activities and interactions within a service network, with the environment enabling high-quality collaboration. This paradigm highlights customers’ ability to co-create value with service providers and other customers. This idea is gaining traction in health care. These days, patients are no longer passive recipients of health-care services; rather they have started taking proactive roles in their self-health management. This study aims to understand the phenomenon of value co-creation among patients within online health communities (OHCs). Design/methodology/approach A systematic literature review of papers published from 2003 to 2024 in Web of Science-indexed journals was conducted. The review highlights theories, contexts, characteristics and methodologies in this area, synthesizing insights from previous research and presenting a future research agenda for underexplored and unexplored contexts using emerging theoretical perspectives and analytical methodologies. Findings The review illuminates theoretical and empirical studies on value co-creation among patients in OHCs. Previous research shows that value co-creation among patients leads to cognitive, affective and physical benefits such as reduced anxiety and stress, increased assurance and self-confidence, improved quality of life, enhanced patient empowerment, acceptance of disease and treatment effectiveness and a sense of self-worth and well-being. Originality/value This review synthesizes insights from previous works and outlines a research agenda for future studies in underexplored and unexplored contexts using new theoretical perspectives and methodologies. Considering the role social media plays in an individual’s life, this work will help in deep diving into the role of such online communities in the health-care sector.

The Effect of Social Media Influencer Warranting Cues on Intentions to Use Non-Hormonal Contraception

ABSTRACT Young women increasingly get sexual health information from social media influencers, who use persuasive communication and can alter attitudes, intentions, and behaviors. Contraception is a commonly discussed health topic among influencers on social media. Previous research suggests that influencers negatively frame and encourage the discontinuation of hormonal contraception. At the same time, influencers also encourage the uptake of less effective non-hormonal options, such as fertility awareness-based methods. Though descriptive content analysis work details these patterns in influencer contraceptive messaging, there is no experimental research that explains message effects. The purpose of this study was to experimentally test the effect of influencer contraceptive-related messaging on behavioral health intentions. This study introduces warranting theory as a potentially valuable model for explaining online health communication message effects. Specifically, this study tested the effect of influencer messages containing sponsorship and medical disclaimers on intentions to use non-hormonal contraception. U.S. females (n = 296) ranging in age from 18–29 years old participated in a survey. Findings suggest that the interaction led to decreased intentions to use non-hormonal contraception. However, findings did not support a relationship between influencer messaging and impressions, which highlights potential boundary conditions for warranting theory and high-risk health behaviors. Additionally, there was a positive relationship between perceived trustworthiness and expertise of the influencer and intention to use non-hormonal contraception. Future research should test influencer messaging using real social media content and consider the effect of parasocial relationships. Practical implications highlight the need for comprehensive contraceptive counseling.

Supportive communication as a collective phenomenon: a dynamic systems account of emotional support provision and outcomes in online health communities

Supportive communication as a collective phenomenon: a dynamic systems account of emotional support provision and outcomes in online health communities

Exploring the impact of team engagement on patient satisfaction: insights from social support and transactive memory system

PurposeResearch on the impact of the engagement of online medical teams (OMTs) on patient evaluation, for example, satisfaction, remains insufficient. This study attempts to recognize the underlying mechanism of how OMTs’ engagement influences patient satisfaction by adopting social support as the mediator. This study also scrutinizes the moderating effects of the transactive memory system (TMS) on the link between OMTs’ engagement and social support.Design/methodology/approachWe utilized a linear model that had fixed effects controlled at the team level for analysis. A bootstrapping approach using 5,000 samples was employed to test the mediation effect.FindingsOur results reveal that OMTs’ engagement improves informational and emotional support, thereby promoting patient satisfaction. Specialization and credibility strengthen the impact of OMTs’ engagement on informational and emotional support. Simultaneously, coordination has an insignificant influence on the link between OMTs’ engagement and social support.Originality/valueThis study contributes to the literature on OMTs, social support, and TMS, providing insights into patients’ perceptions of OMTs’ engagement during online team consultation. This study also generates several implications for the practice of online health communities and OMTs.

Peer Support for Chronic Pain in Online Health Communities: Quantitative Study on the Dynamics of Social Interactions in a Chronic Pain Forum.

Peer support for chronic pain is increasingly taking place on social media via social networking communities. Several theories on the development and maintenance of chronic pain highlight how rumination, catastrophizing, and negative social interactions can contribute to poor health outcomes. However, little is known regarding the role web-based health discussions play in the development of negative versus positive health attitudes relevant to chronic pain. This study aims to investigate how participation in online peer-to-peer support communities influenced pain expressions by examining how the sentiment of user language evolved in response to peer interactions. We collected the comment histories of 199 randomly sampled Reddit (Reddit, Inc) users who were active in a popular peer-to-peer chronic pain support community over 10 years. A total of 2 separate natural language processing methods were compared to calculate the sentiment of user comments on the forum (N=73,876). We then modeled the trajectories of users' language sentiment using mixed-effects growth curve modeling and measured the degree to which users affectively synchronized with their peers using bivariate wavelet analysis. In comparison to a shuffled baseline, we found evidence that users entrained their language sentiment to match the language of community members they interacted with (t198=4.02; P<.001; Cohen d=0.40). This synchrony was most apparent in low-frequency sentiment changes unfolding over hundreds of interactions as opposed to reactionary changes occurring from comment to comment (F2,198=17.70; P<.001). We also observed a significant trend in sentiment across all users (β=-.02; P=.003), with users increasingly using more negative language as they continued to interact with the community. Notably, there was a significant interaction between affective synchrony and community tenure (β=.02; P=.02), such that greater affective synchrony was associated with negative sentiment trajectories among short-term users and positive sentiment trajectories among long-term users. Our results are consistent with the social communication model of pain, which describes how social interactions can influence the expression of pain symptoms. The difference in long-term versus short-term affective synchrony observed between community members suggests a process of emotional coregulation and social learning. Participating in health discussions on Reddit appears to be associated with both negative and positive changes in sentiment depending on how individual users interacted with their peers. Thus, in addition to characterizing the sentiment dynamics existing within online chronic pain communities, our work provides insight into the potential benefits and drawbacks of relying on support communities organized on social media platforms.

The impact of social support chatbots on patients’ value co-creation behavior in online health communities: a moderated mediation model

PurposeOnline health communities (OHCs) have emerged on the Internet, substantially changing the conventional healthcare delivery model. Despite this emergence, the lack of patient participation and contribution always limits the success and sustainability of OHCs. Previous studies have disclosed that patients’ value co-creation behavior (VCB) helps organizations sustain OHCs. However, how the recent surge in artificial intelligence (AI) tools, such as social support chatbots (SSCs), drives patients’ VCB is still unknown. Therefore, this study examines the complex mechanism behind patients’ VCB to establish sustainable OHCs.Design/methodology/approachUsing value co-creation and social support theories, the author develops a moderated mediation model and analyzes survey data from 338 respondents using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) methods.FindingsResults demonstrate that perceived social support (PSS) from SSCs positively affects VCB directly and indirectly via patient learning (PL). This indirect effect is stronger when patient ability/readiness (PAR) is high. ANN findings highlight the model’s robustness and the significant role of PAR in VCB.Originality/valueThis study’s integrated framework offers unique insights into key drivers of patients’ VCB in OHCs. The findings indicate that PSS from SSCs enhances PL and VCB, with PAR influencing the strength of these relationships. Understanding these dynamics can inform user-centric interventions to promote effective learning and collaboration in OHCs.

Review of Influencing Factors of Patients' Medical Choice Behavior in Online Health Community

The development of information technology has made online medical communities a new avenue for addressing medical resource shortages. However, the complexity of information and the asymmetry between physicians and patients makes patients confused when they consult in online health community (OHC). This study systematically analyzed and summarized relevant theories and factors influencing patients' medical choice behavior through literature review. The objective is to offer guidance for patients' decisions in selecting physicians and to support the sustainable development of online medical community platforms, as well as to provide practical insights for further exploration in this field. Objective: This review examines recent theories and factors influencing patients' medical choice behavior in online health community (OHC), aiming to offer insights for patient choice regarding physician selection and the sustainable development of online medical platforms. Methods: A literature analysis was conducted to summarize studies on patients' medical choice behavior in OHC, identifying relevant theories and influencing factors. Results: The analysis identified seven key theories in the study of patients' medical choice behavior: signal theory, trust theory, social capital theory, social exchange theory, the stimulus-organism-response (SOR) model, the elaboration likelihood model (ELM), and the opportunity-motivation-ability (OMA) framework. Factors such as physicians' professional capital, online effort, service quality, online reputation, patient preferences and disease heterogeneity significantly influence patients' medical choice behavior. Conclusion: There is a trend toward integrating multiple theories in understanding patients' medical choice behavior in OHC; however, interdisciplinary research remains limited. Most studies focus on patients’ medical choice behavior from the physicians' perspective, while research from the patients' viewpoint is lacking. This study suggests two future research directions: enhancing the integration of multidisciplinary theories and expanding the scope of research subjects.

Dynamic recommender system for chronic disease-focused online health community

Unequal distribution of healthcare resources poses a significant challenge in numerous regions and countries worldwide. Online Health Communities (OHCs) serve as pivotal platforms for patients to share treatment experiences and seek emotional support from peers facing similar health challenges. The facilitation of efficient user navigation to relevant sub-communities and topics within OHCs emerges as a critical need. Addressing these complexities, a recommendation system specifically designed for OHCs is proposed to tackle unique challenges such as simultaneous prediction of sub-communities and topics with varying levels of information, capturing the influence of evolving health stages on patient interactions, and ensuring coherent recommendations. To meet these challenges, OHCs are conceptualized as dynamic tripartite graphs that model three primary entities—patients, sub-communities, and topics—alongside their temporal interactions. Novel techniques including dynamic tripartite subgraph convolution and dynamic tripartite collaborative filtering are introduced to effectively capture the impact of changing health stages. Additionally, a multi-type entity prediction method is developed to forecast sub-communities and topics, incorporating robust constraints to ensure the validity of predictions. The study conducts extensive experiments using real-world datasets from two online chronic disease communities, including the Breast OHC dataset and the Bladder OHC dataset, encompassing 5,346,591 and 16,427 patient interactions, respectively. Results demonstrate significant advancements over state-of-the-art methods, achieving maximum improvements of 11% and 15% in Mean Reciprocal Rank and Recall metrics, respectively. Sensitivity analyses of online and batch-based algorithms provide insights into the trade-offs between efficiency and accuracy, supported by an illustrative application example highlighting the system’s superiority over existing approaches.

How Does an Online Mental Health Community on Twitter Empower Diverse Population Levels and Groups? A Qualitative Analysis of #BipolarClub.

Social media, including online health communities (OHCs), are widely used among both healthy people and those with health conditions. Platforms like Twitter (recently renamed X) have become powerful tools for online mental health communities (OMHCs), enabling users to exchange information, express feelings, and socialize. Recognized as empowering processes, these activities could empower mental health consumers, their families and friends, and society. However, it remains unclear how OMHCs empower diverse population levels and groups. This study aimed to develop an understanding of how empowerment processes are conducted within OMHCs on Twitter by identifying members who shape these communities, detecting the types of empowerment processes aligned with the population levels and groups outlined in Strategy 1 of the Integrated People-Centred Health Services (IPCHS) framework by the World Health Organization (WHO), and clarifying members' involvement tendencies in these processes. We conducted our analysis on a Twitter OMHC called #bipolarclub. We captured 2068 original tweets using its hashtag #bipolarclub between December 19, 2022, and January 15, 2023. After screening, 547 eligible tweets by 182 authors were analyzed. Using qualitative content analysis, community members were classified by examining the 182 authors' Twitter profiles, and empowerment processes were identified by analyzing the 547 tweets and categorized according to the WHO's Strategy 1. Members' tendencies of involvement were examined through their contributions to the identified processes. The analysis of #bipolarclub community members unveiled 5 main classifications among the 182 members, with the majority classified as individual members (n=138, 75.8%), followed by health care-related members (n=39, 21.4%). All members declared that they experience mental health conditions, including mental health and general practitioner members, who used the community as consumers and peers rather than for professional services. The analysis of 547 tweets for empowerment processes revealed 3 categories: individual-level processes (6 processes and 2 subprocesses), informal carer processes (1 process for families and 1 process for friends), and society-level processes (1 process and 2 subprocesses). The analysis also demonstrated distinct involvement tendencies among members, influenced by their identities, with individual members engaging in self-expression and family awareness support and health care-related members supporting societal awareness. The examination of the #bipolarclub community highlights the capability of Twitter-based OMHCs to empower mental health consumers (including those from underserved and marginalized populations), their families and friends, and society, aligning with the WHO's empowerment agenda. This underscores the potential benefits of leveraging Twitter for such objectives. This pioneering study is the very first to analyze how a single OMHC can empower diverse populations, offering various health care stakeholders valuable guidance and aiding them in developing consumer-oriented empowerment programs using such OMHCs. We also propose a structured framework that classifies empowerment processes in OMHCs, inspired by the WHO's Strategy 1 (IPCHS framework).

Endometriosis Online Communities: How Machine Learning Can Help Physicians Understand What Patients Are Discussing Online

Study ObjectiveUse machine learning to characterize the content of endometriosis online community posts and comments. DesignRetrospective Descriptive Study. SettingEndometriosis online health communities (OHCs) on the platform Reddit. ParticipantsUsers of the endometriosis OHCs r/Endo and r/endometriosis. InterventionsMachine learning was used to analyze thousands of posts made to endometriosis OHCs. Content of posts and comments was interpreted using topic modeling, persona identification, and intent labeling. Measurements included baseline characteristics of users, posts, and comments to the OHCs. Machine-learning techniques; topic modeling, intent labeling, and persona identification were used to identify the most common topics of conversation, the intents behind the posts, and the subjects of people discussed in posts. System performance was assessed via accuracy at F1-score. ResultsA total of 34 715 posts and 353 162 comments responding to posts were evaluated. The topics most likely to be a subject of a post were menstruation (8%), sharing symptoms (8%), medical appointments (8%), medical story (9%), and empathy (7%). The majority of posts were written with the intent of seeking information about endometriosis (49%) or seeking the experiences of others with endometriosis (29%). Users expressed a strong preference for surgeons performing excision rather than ablation of endometriosis. ConclusionEndometriosis OHCs are mostly used to learn about symptoms of endometriosis and share one's medical experiences. Posts and comments from users highlight the need for more empathy in the clinical care of endometriosis and easier access for patients to high-quality information about endometriosis.

Tell me what to do first: how behavioural skills drive users’ intention to adopt online health information

PurposeTo gain a deeper understanding of users’ health information adoption and to promote the effectiveness of health information spread in the context of online limited information, this paper aims to examine how the information-motivation-behavioural (IMB) skills model can be used to organize online health information by experimenting how different IMB elements (information, motivation and behavioural skills) affect users’ intention to adopt health information.Design/methodology/approachThe authors conducted an experiment with 48 participants who received health articles with various combinations and sequences of IMB elements, analysing the impact on information adoption intention to share and practice. The authors also examined the mediation effect of information usefulness and the moderating effect of perceived health status.FindingsThe authors found that: users’ adoption intention of information was influenced by the order of used IMB elements, not the number of elements used; users were more likely to adopt information that started with behavioural skills rather than the model-prescribed IMB sequence; and perceived usefulness mediated the relationship between IMB elements and users’ adoption intention, which means users with different levels of health status all pay more attention to information usefulness and practicability.Originality/valueThe study contributes to research on health communication by showing how the IMB model can be applied online to enhance the effectiveness of health information dissemination. It can also help online health communities arrange more effective and engaging health messages to promote users’ willingness to adopt.