Background: Online Health Communities (OHCs) enable people with long-term conditions to exchange peer self-management experiential information, advice and support. Highly active “superusers” are essential in fostering community interaction and effective information exchange. This study examines the sentiment distribution and dynamics in posts from two UK respiratory OHCs, focusing on interactions between regular users and superusers.

Methods: Sentiment analysis was conducted with a fine-tuned BioBERT model on anonymized data from Asthma UK (AUK) and the British Lung Foundation (BLF). BioBERT was fine-tuned using the COVID-19 Twitter Dataset to categorize sentiment as positive, neutral, or negative. Superusers were defined as the top 1% most active users and via VoteRank (users with the greatest spreading ability). The sentiment of regular users’ and superusers’ aggregated posts was then calculated and analysed.

Results: The fine-tuned model achieved 96% accuracy. Posts were predominantly positive, with a trend toward increasing positivity over time. Superusers generally wrote shorter, more positive posts and superusers defined by posting activity or VoteRank largely overlapped, showing that users who posted the most were also spreaders. Threads initiated by superusers typically encouraged regular users to reply with positive sentiment. When replying to threads started by regular users with different sentiment, superusers tended to be significantly and consistently more positive than regular users.

Conclusions: Network and Sentiment Analysis highlighted the essential role of superusers in respiratory OHCs. They not only generate consistently positive posts but also stimulate similarly positive responses from regular users, thereby sustaining a supportive online environment.

In rapid-onset disasters, emergent networks become vital lifelines for individuals isolated from established relief sources. Actors improvise their collaboration, relying on altered roles and structures which are not pre-planned. While literature on disaster relief has emphasized emergent efforts (e.g., David, 2006; Wachtendorf, 2003), how they fill gaps within the broader relief network as well as the differential capacity of individuals to mobilize such support remains underexamined. This study examines the patterns of individuals’ tangible, emotional, and information support ties during post-hurricane long-term recovery. We focus specifically on how residents’ sociodemographic characteristics, along with broader community contexts, influenced the composition of social support ties involving established and emergent actors.

Survey data capturing long-term recovery experiences were collected in 2022 from five coastal counties in Texas affected by Hurricane Harvey in 2017. The analysis draws on data from 776 individuals regarding household, neighborhood, and community recovery. Respondents identified people, groups, institutions, or programs that offered support across eight different time points, ranging from three days post-landfall to 48 months later. In addition to established institutions including federal and local governments, national nonprofits, and emergency services (e.g., fire and police departments), respondents named a range of sources such as religious organizations, mutual aid groups, local schools, restaurants, and food pantries. Multi-level personal network analyses are used to examine the key predictors of support network composition and density. Further, Twitter data from the first month following Hurricane Harvey will be used to examine the emergent networks of improvised relief during the early recovery phase.

Food insecurity and pulmonary diseases, such as tuberculosis, COPD, and asthma, remain critical public health concerns in Indonesia. While food insecurity exacerbates respiratory disease risk, social networks may serve as a protective factor by influencing access to resources, health behaviors, and healthcare utilization. This study investigates how social network diversity moderates the relationship between food insecurity and pulmonary diseases, with a focus on gender differences. Utilizing data from 27,288 adults in the Indonesian Family Life Survey, we assessed food insecurity via the Food Consumption Score and identified pulmonary diseases through self-reported physician diagnoses. A composite social network diversity measure captured household size and active ties across six social relationships, including spouse, parents, children, siblings, neighbors, and groups with and without religious affiliation. Gender-stratified multivariable logistic regression models, with interaction terms between food insecurity and social network diversity, examined moderating effects while adjusting for sociodemographic and health-related covariates. Results indicate food insecurity significantly increases pulmonary disease risk. A significant interaction effect was observed between food insecurity and social network diversity among women, suggesting that higher social network diversity attenuates the adverse impact of food insecurity on pulmonary health. The moderating effect plateaus at moderate levels of social network diversity, while highly diverse networks show diminished benefits. Findings suggest that women benefit more from social support networks in mitigating the health risks associated with food insecurity. This study highlights the gendered role of social networks in health disparities, emphasizing the need for targeted, network-based interventions to improve health resilience in food-insecure populations.

Depression has historically been the most common psychiatric illness worldwide and a significant contributor to the global burden of disease. An ongoing and steady increase in its prevalence (approximately 60% in the last three decades; Liu, 2024) has now positioned this condition as the top cause of disability globally (Friedrich, 2017; GBD Mental Disorders Collaborators, 2022; WHO, 2017). Depression raises risk of a wide range of physical and psychological illnesses (Harerimana et al., 2022; Monroe & Harkness, 2022; Netsi et al., 2018; Lawrence et al., 2010; Scott et al., 2016), including cardiovascular disease and cancer (Harshfield et al., 2020; Rajan et al., 2020; Scott et. al., 2016), as well as suicide (Mann et al., 2005; Miller & Campo, 2021; Ribeiro, Huang, Fox, & Franklin, 2018). Prior work has indicated the association of depression and the composition and mental health status of face-to-face community ties (e.g., friends, household members) (Bearman & Moody, 2004; Fowler et al., 2008; Rosenquist et al., 2011; Perkins et al, 2016), but this releationship is less explores in non-WEIRD settings. Our study uses a novel dataset (Airoldi & Christakis, 2024) that incorporates a large sample of 27,274 adults living in 176 villages in rural Honduras to model the associations of signed (friends and adversaries) network features on symptoms of depression and also specifically postpartum depression, controlling for demographic and socioeconomic factors. Our study includes a subsample of prospectively observed postpartum parents and negative ties, an unusual feature of social network studies addressing depression. We estimate several models by gender and explore uncommon structural traits such as triadic network structures (e.g., the positive-negative balance of triads). We find that women in more intransitive friendships were more likely to be depressed (in keeping with past work), while the same association was not found for men or postpartum parents. We observed in both genders a higher prevalence of depression among individuals whose friends had adversarial relationships (“negative triads”), as compared with those whose friends were friends (“balanced triads”) or those whose friends had no relation (“incomplete triads”). Our findings reinforce the importance of social network structure and psychological health beyond dyadic associations, especially in high-risk settings (LMIC, rural villages).

Extensive sociological research illustrates the value of personal networks for individual outcomes, highlighting that discussions are crucial for managing personal issues. However, our understanding of what occurs within discussion networks remains limited. To address this gap, I developed a novel method that captures problem-specific networks and measures their overlap. Utilizing originally collected data on the personal networks of emerging adults, I assess discussion patterns and their links to depression. There are three principal findings. First, problem networks form around primary appraisals rather than content domains. Second, the extent of overlap among discussants varies according to primary appraisals. Challenges (potential for gain) consist of specialized and segmented discussants, whereas threats (potential for loss) and harms (actual harm) are found in overlapping networks. Third, larger social responses to problems—with more discussants—are correlated with less severe depression. These findings indicate that discussion practices that match rather than provide access to, resources are an important mechanism that links discussing problems with mental health. The benefits of personal networks for mental health in emerging adults may primarily operate through a matching mechanism driven by cognitive appraisals with specialized and segmented discussants. Theoretically, network structure arises from social interactions; consequently, an instrument based on these interactions is essential for evaluating structure. By overlooking social interactions, our capacity to characterize mechanisms is restricted, especially as digital technologies, namely social media sites, afford new ways for young adults to organize their personal networks.

This study explores the impact of family interaction and family structure on self-rated health among Asian Americans from a social network perspective. Using data from the American Time Use Survey (ATUS), we analyze how different family structures shape individuals’ social connections and health outcomes. We further examine family interaction frequency and time as key mechanisms influencing health. We hypothesize that stronger family networks and more frequent interactions provide greater social support and emotional resources, leading to improved self-rated health. However, certain family structures or culture may introduce caregiving burdens or role strain, resulting in complex health effects. Employing an Ordered Probit Model, we control for socioeconomic status, age, gender, disability status, Asian subgroups, and cultural background. This study contributes new empirical evidence to the intersection of social networks and health research, highlighting the critical role of family networks in promoting well-being among Asian American communities.

Health emergencies are situational (Alonzo 1979). Social responses to bodily changes emerge from diverse social situations, including time, place, and people, influencing pathways to healthcare. Current network approaches, however, overlook real-time situations, focusing instead on stable personal networks that estimate responses during acute health emergencies. Consequently, specifying the social mechanisms affecting health inequality, particularly healthcare access, remains challenging. To increase specificity, we examine the momentary social situations of individuals who arrived at the hospital facing an acute health emergency—stroke. A survey of 246 individuals (egos) used novel situation-based name generators and identified two types of responders (alters) involved during responses: local (physically proximate alters) and remote (physically distant alters). There are four principal findings. First, 95.27% of individuals had responders involved, and among these, 48.09% reported a remote responder. Second, among the responders identified, remote responders were significantly more likely to be perceived as knowledgeable about stroke (49.71% versus 32.61%, p = 0.0034) and were medical experts (41.71% versus 17.39%, p < 0.0001) than local responders. Third, remote responders were significantly less likely first to notice symptoms than local responders (28.57% versus 52.90%, p < 0.0001), suggesting deliberate activation as a mechanism for gaining novel information during responses. Fourth, net of individual factors and social settings, remote responder involvement—situational structure—was significantly associated with an increased risk of delayed hospital arrival (>2 hours). A socio-situational approach reveals that the structural characteristics of situations are related to healthcare access, specifically the involvement of physically distant responders.

Past research has shown that chronic conditions tend to increase depressive symptoms. However, research on the moderating role of social networks has been largely asymmetric. Despite substantial interest in the positive aspects of relationships to provide social resources for coping with health changes and buffering depressive symptoms, less is known about how adverse aspects of social relationships and networks can be detrimental to coping efforts and amplify the mental health consequences of chronic conditions. To test whether and to what extent social costs may make chronic conditions more depressing, I use a national sample of adults aged 40 and above, the German Ageing Study (DEAS). Analyses evaluated the relationship between changes in chronic conditions and depressive symptoms and whether this association was exacerbated by social network costs. A structural equation modeling approach using dynamic panel models with fixed effects and full information maximum likelihood estimation adjusts for the effects of social resources, specific time-varying characteristics, and earlier depressive symptoms. This approach also improves confidence for causal inference into the moderating role of social network costs by accounting for missing data and confounding based on stable unobserved covariates. Results suggest that certain dimensions of social negativity amplify depressive symptoms following changes in chronic conditions, underscoring the detrimental impacts of social costs on mental health. With multimorbidity becoming increasingly prevalent across the adult life course, the double-edged nature of social relationships has the potential to substantially impact the mental health profile of aging populations.

Prenatal distress affects a significant proportion of pregnant individuals and can lead to adverse outcomes for both parent and child. While research has identified various risk factors, the role of family support and stress remains understudied, particularly regarding specific structural and qualitative dimensions of family networks. This mixed methods study examines the relationship between family dynamics and prenatal distress using data from the Family Matters Study (n=436). Pregnant participants were recruited from a North Carolina health system between 2023-2024 and completed virtual survey interviews using EgoWeb 2.0. A subset of the survey respondents (n=59) also participated in follow-up semi-structured interviews. In the survey, prenatal distress is measured using nine items from the Revised Prenatal Distress Questionnaire (NuPDQ). Using a social network approach, we examine whether structural features of family networks (size, density, transitivity) and qualitative aspects of family relationships (proportion of positive, negative, and ambivalent relationships) are associated with prenatal distress levels. We combine these results with an analysis of the qualitative data to better understand the ways that families induce or ameliorate stress during pregnancy. Unlike previous research that often focuses narrowly on partner support or uses broad measures of family support that hide the ambivalence common to family ties, our approach captures the complex nature of family networks during pregnancy. This research contributes to a more nuanced understanding of how specific family configurations and relationship qualities relate to psychosocial well-being during pregnancy.

Closures of obstetrics units in rural hospitals lead to maternity care deserts and a cascade of poor maternal health outcomes among underserved communities in the United States. Little is known about pregnant women’s social networks as drivers of care engagement under these dire maternal care circumstances.

This study uses social network analysis (SNA) to examine how social relationships influence health decisions among rural women during pregnancy and childbirth. Specifically, this study employs a mixed-methods approach, combining SNA with qualitative interviews, to assess the role of network size, density, centrality, and support quality in pre/postnatal care decision-making. Participants include pregnant and recently postpartum women from rural communities in Tennessee, recruited through local healthcare centers and community organizations. We investigate strong social ties as drivers of engagement with formal healthcare services, the extent to which prenatal misinformation exists within networks, and the role of network support in mitigating barriers to care. By mapping and analyzing the structure, strength, and composition of women’s social networks, we explore how family, friends, healthcare providers, and community members shape prenatal care utilization and birth choices.

Forthcoming findings will contribute to our understanding of how rural women's social networks shape health decisions and inform the design of interventions to enhance positive social influences, strengthen healthcare provider-patient relationships, correct misinformation, and improve maternal health outcomes in rural areas. Understanding these network dynamics can inform policies to address rural health disparities by leveraging community-driven, network-based solutions for maternal health.

Social support has been shown to be an effective factor in improving women’s postnatal mental wellbeing. Medical sociologists unpack social support as informational support, emotional support, and tangible support (Lin et al., 1999). For the migrant population, seeking social support from digital spaces is popular because they lack adequate offline social networks to provide social support in host countries.

In order to understand migrant women’s experience of accessing social support in digital spaces and how the online social support affects their postnatal mental wellbeing, my project focuses on migrant Chinese mothers living in the UK as an example. Twenty semi-structured interviews and three focus groups were employed to collect data. My presentation will address the types of social support that emerged from the groups and show how social support affects migrant Chinese mothers’ postnatal mental wellbeing. Additionally, the research shows that migrant Chinese mothers prefer to seek peer support from other migrant Chinese mothers during the postnatal period. My presentation will outline what barriers they experienced when seeking peer support from the local population.

Current research on social support and health mainly focuses on using quantitative methods to evaluate the relationship between social support and health outcomes. However, different types of social support have various impacts. Therefore, this qualitative research further unpacks the different impacts that different social supports have on mothers’ postnatal mental well-being, and contributes to the concept of social support by exploring the lived experience from the perspective of migrant Chinese mothers.

Providing social support is one of the key roles of social networks. The COVID-19 pandemic put social networks under stress, providing a unique opportunity to study how the erosion of social contact impacts social support and how supportive relationships are rebuilt after social contact reinitiates. In particular, it raises the question of who was resilient to this impact and able to recover from it. In this work, we study the social support available to US residents since the beginning of the pandemic using 34 waves of a large-scale online survey with around 20,000 respondents per wave and viable samples across all 50 US states roughly every two months. We first describe the trends in social support available, finding a significant decrease during the pandemic and a slow posterior recovery. Then, we address the question of whether the pandemic increased the inequalities in access to social support or changed the role of protective factors. For this, we run cross-sectional regressions as well as panel analysis, focusing on the factors associated with recovering social support after the pandemic. Finally, we study the role of social distancing and online communication means. Our results show that non face to face communication played a major role and point to significant inequalities, such as by SES. We also find that social contact does not directly translate to social support availability: high social contact periods are not necessarily periods with high social support, and social distancing plays a minor role at the individual level.

Background: Physical activity (PA) is essential for older adults, reducing chronic disease risk, improving health, and enhancing quality of life. However, PA declines with age, and many older adults do not meet PA guidelines. Functional social support (SOSU) can help reduce PA barriers by providing emotional, instrumental, informational, companionship, and validation support.

Aim: Although evidence suggests a positive association between functional SOSU and PA, findings remain inconsistent. This study refines previous research by systematically reviewing and meta-analyzing how functional SOSU influences PA in older adults. It examines associations between SOSU types and PA measures, with subgroup analyses by age, region, SOSU measure, and PA type.

Methods: We conducted a systematic review and meta-analysis according to PRISMA guidelines. The electronic databases APA PsycINFO, ProQuest, PSYINDEX, PubMed, Scopus, SocINDEX, and Web of Science were searched up to August 2023. English peer-reviewed studies focusing on community-dwelling older adults (mean age ≥60) were included. Study quality was assessed using the Newcastle-Ottawa scale, and outcome data were reported independently for each SOSU type.

Results: Of 20,907 abstracts screened, 43 studies met inclusion criteria for the systematic review, with most reporting a significant positive SOSU–PA association. For meta-analysis, studies measuring SOSU for PA and general SOSU were included. Analysis of 25 models showed a pooled effect size of β=0.13 for SOSU for PA and PA. The results suggest SOSU plays a key role in promoting PA, although heterogeneity and potential publication bias warrant further investigation. Random effects meta-regression will refine these findings.

Social influence can play an important role in explaining women’s contraceptive behaviors. There is limited evidence exploring whether social influence is occurring from exposure to alters using contraception, the perception that alters are using contraception, and/or beliefs that alters would be supportive of contraceptive use. To address this gap, we conducted a sociocentric network survey among all reproductive age women (ages 18-49; N=319) across eight villages in a rural parish in southwestern Uganda. We elicited their health network with a name generator and used name interpreter questions for data on ego’s perceptions of alters’ contraceptive use (women only) and whether ego thought alter would be supportive of ego using contraception. We gathered data on contraceptive-focused preference-aligned fertility practices, measured by (1) desire to use contraception and (2) current contraceptive use. Using multivariable logistic regression, we estimated individual and personal social network predictors of current contraceptive use and desired contraceptive use. We found that each additional alter believed to be supportive of contraceptive use was associated with significantly higher odds of egos using contraception, adjusting for ego age, education level, asset index, HIV-status, number of children, and intention to have more children (adjusted odds ratio [aOR] 2.73, p-value<0.001). Having alters using contraception or perceived by ego to use contraception was not associated with ego’s contraceptive use. Our findings demonstrate that alters’ support for contraceptive use matters and suggests that interventions encouraging individuals to share their support for contraceptive use is more important than whether alters engage in those behaviors.

Rheumatoid Arthritis (RA) is a chronic inflammatory disease that affects the joints, leading to pain and functional limitations. Patients with RA have higher rates of depression, which has been linked to worsened RA outcomes. However, there is a lack of research looking at patients’ social networks, and whether features of those networks are associated with depression and RA-attributable outcomes. Adults with RA symptoms (n = 69) in the Washington D.C. metro area completed a survey including measures of depressive symptoms and RA outcomes, along with personal network assessments. Participants with higher depression scores had more RA-attributable pain (b=0.013, p<0.01), more functional limitations in the categories of fine motor skills (b=0.12, p<0.01), mobility (b= 0.08, p<0.01), and body strength (b=0.04, p<0.01), and smaller personal networks (b=-0.03, p<0.01). Additionally, social network size modified the association of limitations in fine motor skills (b=-0.023, p<0.01) and mobility (b=-0.014, p<.01) with depressive symptoms. Future research aims to identify network mechanisms that improve quality of life for those diagnosed with RA. Initial findings suggest a need to identify ways to enhance or build personal networks to support people with RA.