Online Medical Consultation Service-Oriented Recommendations: Systematic Review.

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

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

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

Social support among chronically ill adolescent and young adult patients using a hospital-based online health community as part of a palliative care program: A qualitative study.

OBJECTIVES: Chronically ill adolescent and young adult (AYA) patients experience barriers to accessing psychosocial support/palliative care, increasing their risk for negative psychosocial outcomes. Online health communities (OHCs) have been recommended for AYAs as part of palliative care support programs; however, we lack research investigating palliative care programs targeting AYAs' psychosocial support needs that are delivered virtually and able to engage with patients both during and beyond inpatient admissions. Streetlight is a palliative care program designed for chronically ill AYAs. Developed as a complementary component that extends beyond the hospital setting, Streetlight Gaming and Online Team (SGOT) is an OHC aimed at facilitating social support to influence psychosocial outcomes. We investigated the existence and enactment of social support among chronically ill AYAs using SGOT and compared this to existing online social support categories to determine which support types are present within SGOT. METHODS: This was a qualitative phenomenological study. We performed deductive thematic analysis based on existing online social support categories. Nine semi-structured interviews were conducted with SGOT participants. RESULTS: Social companionship/belonging, esteem/emotional, and informational support were most prevalent within SGOT. Thirteen subthemes emerged representing how social support impacted AYAs' psychosocial wellbeing. Notably, coping with/managing illness, sense of community and normalcy, recommendations and advice, and shared interests unrelated to illnesses were subthemes that resonated with AYAs and added value to their experiences. SIGNIFICANCE OF RESULTS: SGOT is an impactful OHC used to meet AYAs' social support needs. What makes SGOT especially unique is its virtual delivery, wherein AYAs can conveniently maintain beneficial relationships with other chronically ill same-aged peers. AYAs need spaces where they can feel normal and access continuous support, both within and beyond inpatient admissions. This study enhances our understanding of online AYA psychosocial support programs. Findings can be used by healthcare professionals to implement similar palliative care and psychosocial support programs.

Complaining, Regret, Superiority, and Discovery: Chinese Patients' Sense Making of Depression in an Online Forum.

Drawing on observations of a Chinese online depression community, this article explored the members' sense making of depression by analyzing their narrative accounts of depression. Four types of sense making were predominant among the depression sufferers: complaining, regret, superiority, and discovery. The complaining narrative is the members' telling about the pain caused by family (parental control or neglect), school bullying, stress from study or work, and social norms. The regret narrative is the members' reflection on their habit of perfectionism and lack of self-disclosure. The superiority narrative is the members' attribution of depression to their intelligence and morality that surpass the average people. The discovery narrative is the members' novel understanding of the self, significant others, and key events. The findings suggest that the social and psychological explanation of the causes of depression, instead of the medical model, is popular among the Chinese patients. Their stories of depression are also stories of marginalization, visions for the future, and realizing the normalization of identity as depression patients. The findings have implications for public policy around support for mental health.

Exploring Social Support in an Online Support Community for Tourette Syndrome and Tic Disorders: Analysis of Postings.

BACKGROUND: Online support communities have become an accessible way of gaining social, emotional, and informational support from peers and may be particularly useful for individuals with chronic conditions. To date, there have been few studies exploring the online support available for tic disorders, such as Tourette syndrome. An exploratory study looking at users' experiences with using online support communities for tic disorders suggested that members used such communities to share experiences, information, and strategies for tic management. OBJECTIVE: To build on these preliminary findings, this study examined the provision of social support in an online community for Tourette syndrome. METHODS: Data were collected from one publicly available online support community for Tourette syndrome and tics, from its inception to December 2019, by randomly selecting 10% of posts and their corresponding comments from each year for analysis. This resulted in 510 unique posts and 3802 comments posted from 1270 unique usernames. The data were analyzed using inductive thematic analysis. RESULTS: The findings of this study suggest that users utilized the online community as a multifaceted virtual place where they could share and ask for information about tics, unload and share their feelings arising from living with Tourette syndrome, find people facing similar situations and experiences, and freely share the realities of living with Tourette syndrome. CONCLUSIONS: The results complement the findings from a preliminary study and suggest that online support communities have a potentially valuable role as a mechanism for sharing and gaining information on illness experiences from similar peers experiencing tics and can promote self-management of tics. Limitations and recommendations for future research are discussed.

Online social support and collective empowerment: Serial mediation effect on self-efficacy among mothers of children with type 1 diabetes.

AIM: To identify a serial multiple mediation effect of social support in online health communities and collective empowerment on the relationship between diabetes-related burden (DRB) and self-efficacy, among mothers using a continuous glucose monitoring device for children with type 1 diabetes (T1D). DESIGN: A secondary analysis, cross-sectional, descriptive study. METHODS: Data were obtained from 198 mothers of children with T1D via a web survey, from August to September 2020. Measures used were the Collective Empowerment in the Online Health Community Scale, a modified version of the Multidimensional Scale of Perceived Social Support, Problem Areas in Diabetes Survey-Parent Revised version and a modified version of the Maternal Self-efficacy for Diabetes Management Scale. Data were analysed using SPSS 25.0, and PROCESS MACRO for SPSS v3.5. RESULTS: A serial multiple mediation model was used. The indirect effects of both social support in online health communities and collective empowerment were identified in the relationship between DRB and diabetes self-efficacy (DSE). However, there was no indirect effect of social support in online health communities on these relationships. CONCLUSION: These findings suggest that online social support alone has a limited role in chronic disease management self-efficacy. Collective empowerment should be a strategic component in intervention development using online health communities to strengthen DSE in mothers of children with T1D. IMPACT: This study provides novel insights into the functional mechanism of online health communities for T1D. Peer mentor coaching by parents of children with T1D effectively helps other children's parents with its recent diagnosis. The findings recognize a need for strategies enhancing collective empowerment among parents of children with T1D. Along with peer coaching, these strategies should strengthen knowledge of resources and methods to impact social change as well as resource mobilization for collective actions.

Foresight study on online health community: The perspective of knowledge empowerment for patients with chronic diseases.

Patient empowerment is an indispensable precondition for patients to self-manage their disease. The article takes the position that patients are empowered for disease self-management through patient knowledge empowerment when sharing knowledge. One of the most important instruments to successfully empower a patient to manage a chronic disease and maintain social relations, which are also a precondition for the prevention of chronic illnesses, is the possibility to access online health communities (OHCs) and participate in them. The aim of the article is to model possible development scenarios of OHCs as enablers of patient knowledge in relation to other digital health technologies (DHTs). A foresight methodology was used to achieve the goal, employing a technology scanning approach after selecting 10 foresight studies, which resulted in four future scenario models for the empowerment of patients wcith chronic diseases through digital health communities. They reveal options for the future interoperability of OHCs with other DHTs and highlight their importance and significance for the healthcare system as a technology for balancing patient self-efficacy and social relations as well as the need to maintain and develop them.

Comparative Analysis of Social Support in Online Health Communities Using a Word Co-Occurrence Network Analysis Approach.

Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with others facing similar health problems and receive multiple types of social support, including but not limited to informational support, emotional support, and companionship. The aim of this study is to examine the differences in social support communication among people with different types of cancers. A novel approach is developed to better understand the types of social support embedded in OHC posts. Our approach, based on the word co-occurrence network analysis, preserves the semantic structures of the texts. Information extraction from the semantic structures is supported by the interplay of quantitative and qualitative analyses of the network structures. Our analysis shows that significant differences in social support exist across cancer types, and evidence for the differences across diseases in terms of communication preferences and language use is also identified. Overall, this study can establish a new venue for extracting and analyzing information, so as to inform social support for clinical care.

Identifying Self-Management Support Needs for Pregnant Women With Opioid Misuse in Online Health Communities: Mixed Methods Analysis of Web Posts.

BACKGROUND: The current opioid crisis in the United States impacts broad population groups, including pregnant women. Opioid use during pregnancy can affect the health and wellness of both mothers and their infants. Understanding women's efforts to self-manage opioid use or misuse in pregnancy is needed to identify intervention points for improving maternal outcomes. OBJECTIVE: This study aims to identify the characteristics of women in an online health community (OHC) with opioid use or misuse during pregnancy and the self-management support needs of these mothers. METHODS: A total of 200 web posts by pregnant women with opioid use participating in an OHC were double coded. Concepts and their thematic connections were identified through an inductive process until theoretical saturation was reached. Statistical tests were performed to identify patterns. RESULTS: The majority of pregnant women (150/200, 75.0%) in the OHC exhibited signs of misuse, and 62.5% (125/200) of the participants were either contemplating or pursuing dosage reduction. Self-managed withdrawal was more common (P<.001) than professional treatment among the population. A total of 5 themes of self-management support needs were identified as women sought information about the potential adverse effects of gestational opioid use, protocols for self-managed withdrawal, pain management safety during pregnancy, hospital policies and legal procedures related to child protection, and strategies for navigating offline support systems. In addition, 58.5% (117/200) of the pregnant women expressed negative emotions, of whom only 10.2% (12/117) sought to address their emotional needs with the help of the OHC. CONCLUSIONS: OHCs provide vital self-management support for pregnant women with opioid use or misuse. Women pursuing self-managed dosage reduction are prone to misinformation and repeated relapses, which can result in extreme measures to avoid testing positive for drug use at labor. The study findings provide evidence for public policy considerations, including universal screening of substance use for pregnant women, emphasis on treatment rather than legal punishment, and further expansion of the Drug Addiction Treatment Act waiver training program. The improvement of web-based platforms that can organize geo-relevant information, dispense clinically validated withdrawal schedules, and offer structured peer support is envisioned for harm reduction among pregnant women who opt for self-management of opioid misuse.

User Behaviors and User-Generated Content in Chinese Online Health Communities: Comparative Study.

BACKGROUND: Online health communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters globally. Chinese OHCs are no exception. However, user-generated content (UGC) and the associated user behaviors in Chinese OHCs are largely underexplored and rarely analyzed systematically, forfeiting valuable opportunities for optimizing treatment design and care delivery with insights gained from OHCs. OBJECTIVE: This study aimed to reveal both the shared and distinct characteristics of 2 popular OHCs in China by systematically and comprehensively analyzing their UGC and the associated user behaviors. METHODS: We concentrated on studying the lung cancer forum (LCF) and breast cancer forum (BCF) on Mijian, and the diabetes consultation forum (DCF) on Sweet Home, because of the importance of the 3 diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explored the key user activities, small-world effect, and scale-free characteristics of each social network. We examined the UGC of these forums comprehensively and adopted the weighted knowledge network technique to discover salient topics and latent relations among these topics on each forum. Finally, we discussed the public health implications of our analysis findings. RESULTS: Our analysis showed that the number of reads per thread on each forum followed gamma distribution (HL=0, HB=0, and HD=0); the number of replies on each forum followed exponential distribution (adjusted RL2=0.946, adjusted RB2=0.958, and adjusted RD2=0.971); and the number of threads a user is involved with (adjusted RL2=0.978, adjusted RB2=0.964, and adjusted RD2=0.970), the number of followers of a user (adjusted RL2=0.989, adjusted RB2=0.962, and adjusted RD2=0.990), and a user's degrees (adjusted RL2=0.997, adjusted RB2=0.994, and adjusted RD2=0.968) all followed power-law distribution. The study further revealed that users are generally more active during weekdays, as commonly witnessed in all 3 forums. In particular, the LCF and DCF exhibited high temporal similarity (ρ=0.927; P<.001) in terms of the relative thread posting frequencies during each hour of the day. Besides, the study showed that all 3 forums exhibited the small-world effect (mean σL=517.15, mean σB=275.23, and mean σD=525.18) and scale-free characteristics, while the global clustering coefficients were lower than those of counterpart international OHCs. The study also discovered several hot topics commonly shared among the 3 disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study found that after the outbreak of COVID-19, users on the LCF and BCF were much more likely to bring up COVID-19-related issues while discussing their medical issues. CONCLUSIONS: UGC and related online user behaviors in Chinese OHCs can be leveraged as important sources of information to gain insights regarding individual and population health conditions. Effective and timely mining and utilization of such content can continuously provide valuable firsthand clues for enhancing the situational awareness of health providers and policymakers.

Emotional adjustment post-stroke: A qualitative study of an online stroke community.

Understanding of emotional adjustment after stroke is limited. Under one-third of stroke survivors reporting emotional problems receive support. The aim of this study was to explore the process of emotional adjustment post-stroke and investigate the role played by participation in an online stroke community. We applied thematic analysis to 124 relevant posts within 114 discussion threads, written by 39 survivors and 29 carers. The contribution of online community engagement to emotional adjustment was explored using the Social Support Behaviour Code. Stroke survivors share common experiences of emotional adjustment and may not necessarily reach complete acceptance. Positive and negative trajectories of emotional adjustment were identified. Survivors progressed along, or moved between, positive and negative pathways not in a time-dependent manner but in response to "trigger events," such as physical setbacks or anti-depressant treatment, which may occur at any chronological time. An adapted version of Suhr's 1990 Social Support Behaviour Code showed that support provided through the online community took many forms, including advice, teaching, empathy and normalization of concerns. Participation in the stroke community was itself deemed to be a positive "trigger event." There is need to improve awareness of emotional adjustment and their "triggers" amongst stroke survivors, carers and clinicians.

Investigating relationships among cancer survivors' engagement in an online support community, social support perceptions, well-being, and moderating effects of existing (offline) social support.

PURPOSE: Socially supportive relationships help cancer survivors cope with their diagnosis and may improve quality of life; however, many survivors report unmet support and information needs. Online communities of survivors may address these needs, but research on their benefits have been equivocal. This cross-sectional, self-report study investigated relationships among cancer survivors' level of engagement in an online survivor community (The American Cancer Society Cancer Survivors Network®; CSN), perceptions of emotional/informational support available from online communities ("online social support"), well-being, and moderating effects of "offline social support." METHODS: Participants were 1255 registered users of the CSN who completed surveys between 2013 and 2014. Three types of engagement with the CSN-social/communal, interpersonal communication, and informational/search engagement-were identified through principal components analysis. Regression analyses examined hypotheses. RESULTS: More frequent social/communal and interpersonal communication engagement were associated with increased online social support (p < .0001), and the relationship between interpersonal communication engagement and online social support was strongest for survivors reporting lower offline social support (interaction ß = - .35, p < .001). Greater online social support was associated with increased well-being, but only among survivors reporting low offline social support (interaction ß = - .35, p < .0001). CONCLUSIONS: Engagement in online survivor communities may increase support perceptions that promote well-being, but benefits may accrue more to survivors reporting low offline social support. IMPLICATIONS FOR CANCER SURVIVORS: Newly diagnosed cancer survivors, particularly those with unmet emotional/informational support needs, should be given the opportunity to communicate with other survivors through online survivor support networks.

Privacy Protection in Online Health Communities: Natural Experimental Empirical Study.

BACKGROUND: An online health community (OHC) is a novel sharing channel through which doctors share professional health care knowledge with patients. While doctors have the authority to protect their patients' privacy in OHCs, we have limited information on how doctors' privacy protection choices affect their professional health care knowledge sharing with patients. OBJECTIVE: We examined the relationship between privacy protection and professional health care knowledge sharing in OHCs. Specifically, we examined the effects of privacy protection settings in an OHC on doctors' interactive professional health care knowledge sharing and searching professional health care knowledge sharing (two dimensions of professional health care knowledge sharing). Moreover, we explored how such effects differ across different levels of disease stigma. METHODS: We collected the monthly panel data of 19,456 doctors from Good Doctor, one of the largest OHCs in China, from January 2008 to April 2016. A natural experimental empirical study with difference-in-difference analysis was conducted to test our hypotheses. The time fixed effect and the individual fixed effect were both considered to better identify the effects of a privacy protection setting on professional health care knowledge sharing. Additionally, a cross-sectional analysis was performed for a robust check. RESULTS: The results indicate that the privacy protection setting has a significant positive effect on interactive professional health care knowledge sharing (ß=.123, P<.001). However, the privacy protection setting has a significant negative effect on searching professional health care knowledge sharing (ß=-.225, P=.05). Moreover, we found that high disease stigma positively impacts the effect of privacy protection on interactive professional health care knowledge sharing (coefficients are in the same valence) and negatively impacts the effects of privacy protection on searching professional health care knowledge sharing (coefficients are in the reverse valence). CONCLUSIONS: Privacy protection has a bilateral effect on professional health care knowledge sharing (ie, a positive effect on interactive professional health care knowledge sharing and a negative effect on searching professional health care knowledge sharing). Such bilateral switches of professional health care knowledge sharing call for a balanced state in conjunction with practical implications. This research also identifies a moderate effect of disease stigma on privacy protection settings and professional health care knowledge sharing.

Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study.

BACKGROUND: With the rapid development of online health communities, increasing numbers of patients and families are seeking health information on the internet. OBJECTIVE: This study aimed to discuss how to fully reveal the health information needs expressed by patients with hypertension in their questions in a web-based environment and how to use the internet to help patients with hypertension receive personalized health education. METHODS: This study randomly selected 1000 text records from the question data of patients with hypertension from 2008 to 2018 collected from Good Doctor Online and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning intention of each patient with hypertension based on the patient's question and used co-occurrence network analysis and the k-means clustering method to explore the features of the health information needs of patients with hypertension. RESULTS: The classification system for the health information needs of patients with hypertension included the following nine dimensions: drugs (355 names), symptoms and signs (395 names), tests and examinations (545 names), demographic data (526 kinds), diseases (80 names), risk factors (37 names), emotions (43 kinds), lifestyles (6 kinds), and questions (49 kinds). There were several characteristics of the explored web-based health information needs of patients with hypertension. First, more than 49% of patients described features, such as drugs, symptoms and signs, tests and examinations, demographic data, and diseases. Second, patients with hypertension were most concerned about treatment (778/1000, 77.80%), followed by diagnosis (323/1000, 32.30%). Third, 65.80% (658/1000) of patients asked physicians several questions at the same time. Moreover, 28.30% (283/1000) of patients were very concerned about how to adjust the medication, and they asked other treatment-related questions at the same time, including drug side effects, whether to take the drugs, how to treat the disease, etc. Furthermore, 17.60% (176/1000) of patients consulted physicians about the causes of clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, and medications and examinations. Fourth, by k-means clustering, the questioning intentions of patients with hypertension were classified into the following seven categories: "how to adjust medication," "what to do," "how to treat," "phenomenon explanation," "test and examination," "disease diagnosis," and "disease prognosis." CONCLUSIONS: In a web-based environment, the health information needs expressed by Chinese patients with hypertension to physicians are common and distinct, that is, patients with different background features ask relatively common questions to physicians. The classification system constructed in this study can provide guidance to health information service providers for the construction of web-based health resources, as well as guidance for patient education, which could help solve the problem of information asymmetry in communication between physicians and patients.

Understanding Weight Loss via Online Discussions: Content Analysis of Reddit Posts Using Topic Modeling and Word Clustering Techniques.

BACKGROUND: Maintaining a healthy weight can reduce the risk of developing many diseases, including type 2 diabetes, hypertension, and certain types of cancers. Online social media platforms are popular among people seeking social support regarding weight loss and sharing their weight loss experiences, which provides opportunities for learning about weight loss behaviors. OBJECTIVE: This study aimed to investigate the extent to which the content posted by users in the r/loseit subreddit, an online community for discussing weight loss, and online interactions were associated with their weight loss in terms of the number of replies and votes that these users received. METHODS: All posts that were published before January 2018 in r/loseit were collected. We focused on users who revealed their start weight, current weight, and goal weight and were active in this online community for at least 30 days. A topic modeling technique and a hierarchical clustering algorithm were used to obtain both global topics and local word semantic clusters. Finally, we used a regression model to learn the association between weight loss and topics, word semantic clusters, and online interactions. RESULTS: Our data comprised 477,904 posts that were published by 7660 users within a span of 7 years. We identified 25 topics, including food and drinks, calories, exercises, family members and friends, and communication. Our results showed that the start weight (ß=.823; P<.001), active days (ß=.017; P=.009), and median number of votes (ß=.263; P=.02), mentions of exercises (ß=.145; P<.001), and nutrition (ß=.120; P<.001) were associated with higher weight loss. Users who lost more weight might be motivated by the negative emotions (ß=-.098; P<.001) that they experienced before starting the journey of weight loss. In contrast, users who mentioned vacations (ß=-.108; P=.005) and payments (ß=-.112; P=.001) tended to experience relatively less weight loss. Mentions of family members (ß=-.031; P=.03) and employment status (ß=-.041; P=.03) were associated with less weight loss as well. CONCLUSIONS: Our study showed that both online interactions and offline activities were associated with weight loss, suggesting that future interventions based on existing online platforms should focus on both aspects. Our findings suggest that online personal health data can be used to learn about health-related behaviors effectively.

Consequences of Gift Giving in Online Health Communities on Physician Service Quality: Empirical Text Mining Study.

BACKGROUND: Gift giving, which has been a heavily debated topic in health care for many years, is considered as a way of expressing gratitude and to be beneficial for the physician-patient relationship within a reasonable range. However, not much work has been done to examine the influence of gift giving on physicians' service quality, especially in the online health care environment. OBJECTIVE: This study addressed the consequences of gift giving by mining and analyzing the dynamic physician-patient interaction processes in an online health community. Specifically, gift types (affective or instrumental) based on the motivations and physician-patient tie strength were carefully considered to account for differences in physicians' service quality. METHODS: The dynamic interaction processes (involving 3154 gifts) between 267 physicians and 14,187 patients from a well-known online health community in China (haodf.com) were analyzed to obtain empirical results. RESULTS: Our results reveal that patient gift giving inspires physicians to improve their service quality as measured by physicians' more detailed responses and improved bedside manner, and the degree of influence varied according to the strength of the physician-patient tie. Moreover, affective gifts and instrumental gifts had different effects in improving physicians' service quality online. CONCLUSIONS: This study is among the first to explore gift giving in online health communities providing both important theoretical and practical contributions. All of our results suggest that gift giving online is of great significance to promoting effective physician-patient communication and is conducive to the relief of physician-patient conflicts.

Collective Empowerment in Online Health Communities: Scale Development and Empirical Validation.

BACKGROUND: The role of online health communities (OHCs) in patient empowerment is growing and has been increasingly studied in recent years. Research has focused primarily on individualistic conception of patients' empowerment, with much less attention paid to the role of OHCs in the development of patients' collective empowerment. Although OHCs have immense potential for empowerment that goes beyond the individual, the concept and scale of collective empowerment in OHCs have not yet been developed or validated. OBJECTIVE: This study aimed to develop an instrument for measuring collective empowerment in online health communities (CE-OHC) and to test its quality by investigating its factorial structure, reliability, construct validity, and predictive validity. METHODS: The CE-OHC scale was developed according to a strict methodology for developing valid and reliable scales. An initial set of 20 items was first tested in the pilot study conducted in 2016 using a sample of 280 registered users of Slovenia's largest OHC. A refined version with 11 items was tested in the main study conducted in 2018 on a random sample of 30,000 registered users of the same OHC. The final sample comprised 784 users. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to investigate the factorial structure, discriminant validity, and convergent validity of the scale. Cronbach alpha coefficient was used to determine the CE-OHC scale's internal consistency. To establish the predictive validity, ordinary least squares regression was performed to test the role of CE-OHC in users' civic participation. RESULTS: The EFA resulted in a two-factor solution, and the two factors-knowledge of resources and resource mobilization for collective action-together explain 63.8% of the variance. The second-order CFA demonstrated a good fit to the data (root mean square error of approximation=0.07) and the scale had a good internal consistency (alpha=.86). Although evidence of the scale's convergent validity was partially provided, discriminant validity of the scale remained unconfirmed. Overall, CE-OHC was confirmed to be a predictor of users' civic participation, but the influence was somewhat weak and inconsistent across two subscales. CONCLUSIONS: The proposed CE-OHC scale is a reliable and relatively valid instrument and serves as a good baseline to advance the measurement of collective empowerment in OHC contexts. This is the first scale developed for this purpose, and future research should focus on the development of a clear nomological network of the collective empowerment construct in relation to the OHC settings.

Scaling PatientsLikeMe via a "Generalized Platform" for Members with Chronic Illness: Web-Based Survey Study of Benefits Arising.

BACKGROUND: Launched in 2006 for patients with amyotrophic lateral sclerosis, PatientsLikeMe is an online community offering patient-reported outcomes, symptom tracking, and social features. Every member of the site can see all the data reported by every other member, view aggregated reports, identify "patients like them," and learn about treatment options in order to live better with their condition. In previous studies, members reported benefits such as improved condition knowledge, increased medication adherence, and better management of side effects. However, the site evolved in 2011 from condition-specific "vertical" communities consisting only of people with the same disease to a "generalized platform," in which every patient could connect with every other patient regardless of condition and with generic, rather than condition-specific, data tools. Some, but not all, communities received further custom tracking tools. OBJECTIVE: We aimed to understand (1) whether members of PatientsLikeMe using the generalized platform still reported similar benefits and (2) assess factors associated with benefits, such as community customization, site use, and patient activation. METHODS: A cross-sectional retrospective custom survey was fielded to 377,625 members between 2016 and 2017 including the Patient Activation Measure (PAM). A benefit index was developed for comparability across conditions. RESULTS: The invitation was viewed by 26,048 members of whom 11,915 did not respond, 5091 opted out, 1591 provided partial data, and 17 were screened out. Complete responses were received from 7434 participants. Users perceived greatest benefit in understanding how their condition may affect them (4530/6770, 66.91% participants, excluding "does not apply" answers), understanding what might help them live better with their condition (4247/6750, 62.92%), which treatments were available (4143/6898, 60.06%), understanding treatment side effects (4182/6902, 60.59%), and important factors in making treatment decisions (3919/6813, 57.52%). The benefit index was 29% higher for the "most activated" patients (PAM level 4 vs PAM level 1; relative risk [RR]=1.29, P<.001), 21% higher for conditions with some community customization versus none (RR=1.21, P<.001), and 11% higher in those using the site most often versus least (RR=1.11, P<.001). CONCLUSIONS: Members of the generalized platform reported a range of benefits related to improved knowledge and understanding of their condition and treatment management. Condition-specific customization may improve their experience still further. Future studies will explore longitudinal changes to patient activation.

Increase in contralateral prophylactic mastectomy conversation online unrelated to decision-making.

BACKGROUND: The increased uptake of contralateral prophylactic mastectomy (CPM) among breast cancer patients remains poorly understood. We hypothesized that the increased rate of CPM is represented in conversations on an online breast cancer community and may contribute to patients choosing this operation. METHODS: We downloaded 328,763 posts and their dates of creation from an online breast cancer community from August 1, 2000, to May 22, 2016. We then performed a keyword search to identify posts which mentioned breast cancer surgeries: contralateral prophylactic mastectomy (n = 7095), mastectomy (n = 10,889), and lumpectomy (n = 9694). We graphed the percentage of CPM-related, lumpectomy-related, and mastectomy-related conversations over time. We also graphed the frequency of posts which mentioned multiple operations over time. Finally, we performed a qualitative study to identify factors influencing the observed trends. RESULTS: Surgically related posts (e.g., mentioning at least one operation) made up a small percentage (n = 27,678; 8.4%) of all posts on this community. The percentage of surgically related posts mentioning CPM was found to increase over time, whereas the percentage of surgically related posts mentioning mastectomy decreased over time. Among posts that mentioned more than one operation, mastectomy and lumpectomy were the procedures most commonly mentioned together, followed by mastectomy and CPM. There was no change over time in the frequency of posts that mentioned more than one operation. Our qualitative review found that most posts mentioning a single operation were unrelated to surgical decision-making; rather the operation was mentioned only in the context of the patient's cancer history. Conversely, the most posts mentioning multiple operations centered around the patients' surgical decision-making process. CONCLUSIONS: CPM-related conversation is increasing on this online breast cancer community, whereas mastectomy-related conversation is decreasing. These results appear to be primarily informed by patients reporting the types of operations they have undergone, and thus appear to correspond to the known increased uptake of CPM.

Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks.

Identifying topics of discussions in online health communities (OHC) is critical to various information extraction applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, we provide a multi-class schema, an annotated dataset, and supervised classifiers based on convolutional neural network (CNN) and other models for the task of classifying discussion topics. We apply the CNN classifier to the most popular breast cancer online community, and carry out cross-sectional and longitudinal analyses to show topic distributions and topic dynamics throughout members' participation. Our experimental results suggest that CNN outperforms other classifiers in the task of topic classification and identify several patterns and trajectories. For example, although members discuss mainly disease-related topics, their interest may change through time and vary with their disease severities.