After major health events, personal social networks serve as conduits of resources, support, and information to facilitate healthy recovery. However, mobilizing network resources to improve outcomes remains elusive, particularly within individualistic approaches to healthcare in the United States. An open question is whether personal network structure may be an important factor that deserves consideration when attempting to mobilize network resources during health setbacks. To address this question, we conducted a two-arm randomized controlled trial on blood pressure management after stroke, comparing individual counseling with a network-engaged approach that incorporated and supported patients’ existing personal networks. We recruited 45 stroke survivors: 21 in individual counseling and 24 in the network-engaged group. In the aggregate, the groups had no statistically significant differences in systolic blood pressure after 3 months. However, survivors in the network-engaged group with high constraint networks had significant blood pressure reduction compared to those with low constraint networks. These results indicate that patients and their network members in high-constrained structures may be more receptive to, or may reinforce, novel information about blood pressure management strategies. These results should be considered preliminary due to the small samples and limited network engagement, which offers lessons for future trials. However, the trial does suggest that aligning behavior change strategies with network structures has promise. This study offers important insights for clinical applications of personal network interventions.

Background: Many young adults (YA) diagnosed with cancer report feelings of social isolation following a cancer diagnosis, which can negatively impact health outcomes. This study (1) characterizes social network structure and composition and (2) examines the associations between social network metrics and social health outcomes among YA cancer patients over time.

Methods: The Social Health Study is a longitudinal study of YA cancer patients in Southern California surveyed at four timepoints over the first year following their cancer diagnosis. Participants (N = 163) completed an egocentric network survey and questionnaires on social health outcomes including loneliness, emotional, information, and tangible support at each study timepoint. Data were collected on alter relationships, demographics, and provisions of support: closeness (strength of connection), confidence (can confide in alter) and contact (interaction frequency). Multivariable linear mixed effect models with random intercepts for participants were run to test the longitudinal associations between network statistics (density, transitivity, constraint), provisions of support and each social health outcome while controlling for patient gender, age, and Hispanic/Latine ethnicity.

Results: Having a greater number of close alters was positively associated with greater feelings of emotional, information, and tangible support, while having more alters to confide in was associated with greater emotional and information support. Hispanic ethnicity was associated with lower information and tangible support.

Contributions: Social networks provide multiple forms of social support among YA cancer patients. These findings identify disparities in social support among Hispanic/Latine patients, highlighting the need to further investigate social health challenges among this patient population.

Health issues can exert a profound but varied influence on individuals' social networks. On the negative side, previous research suggests that the occurrence of a health event may impair an individual’s physical ability to be active and socialize with others or generate interpersonal conflict that can result in less contact with network members, thus leading to smaller and more constrained networks. On the positive side, health events may also give people the opportunity to mobilize their networks by strengthening existing ties and reconnecting with dormant ones, while also forming new social ties with professionals, service providers, and others. Hence, health events can constitute an important trigger for change leading to a reconfiguration of personal networks that modifies their composition, structure, and functioning.

In this study, we discuss how the diagnosis of a serious illness, chronic conditions, disability or injuries shape sociability and personal networks. Given the far-reaching consequences of health events, we posit that they can act as powerful catalysts for network transformation, altering in complex ways the composition and characteristics of an individual's social connections. We draw on three complementary datasets—the Normandy Panel, the Toulouse Older People Panel, and the University of California Social Networks Study—to examine the relationship between health events and network dynamics, focusing on the structure, function, and content of personal networks over time. To promote comparability, we created similar measures for the experience of a serious health problem at different observation times and examined variation in network characteristics, including network size, density, lost alters, added alters, change in number of kin and non-kin members, and churn, depending on whether the individual experienced a serious health event. Then, using qualitative data, we studied individuals’ life course trajectories and the network evolution of several contrasting cases to better understand the network variations following a health event. The findings highlight nuanced effects of health-related events on personal networks. The occurrence of a serious health issue is not significantly related to change in network size. It is, however, associated with member churn and subtle structural changes. The quantitative findings suggest that there is a decrease in network density due to diversification that mainly consists of adding extended kin in older people and adding nonkin in younger people. At times, this diversification is linked to new commitments to activities. In other cases, diversification is the result of adding professionals to the network. Despite the slight decline in densification in the quantitative analyses, our analysis of the qualitative also point to cases or stages characterized by an inward turn, where refocusing on stronger ties with close family took place after the health event. Furthermore, health events often coincided with other life events, like breakups or job changes, and health issues that occurred to a close alter, for example a spouse or intimate partner, sometimes impacted networks more than the ego’s condition. This study highlights the need to contextualize analyses of health events' impact on personal networks and resilience across life stages.

The Reducing Obesity Using Social Ties (ROBUST) study examines how social network processes can support weight loss in Black and Hispanic adults with obesity (BMI ≥ 30 kg/m²). Using a randomized controlled trial (RCT), we compare a 24-week social network-enhanced lifestyle intervention with an individual-level intervention (control), modeled after the Diabetes Prevention Program. Participants in the network-enhanced intervention (egos) recruit one or two social network members (alters) as ‘support partners’, who then engage in virtual sessions focused on communication and social support strategies to help the ego achieve their health goals.

We present baseline findings, including the composition and characteristics of participants’ personal networks, assessed using Network Canvas. We describe the demographic and health profiles of recruited alters, as well as their network roles, support functions, and positions. Analyses explore whether alter characteristics predict their selection as ‘support partners’ and whether these associations vary by the ego’s gender, race/ethnicity, and health indicators.

These baseline results will inform the full RCT evaluation, shedding light on the role of communal coping in weight loss and whether alter characteristics influence their engagement and effectiveness in the intervention. By explicitly targeting a population historically less responsive to lifestyle interventions, ROBUST aims to refine and tailor strategies for leveraging social networks to enhance weight loss outcomes.

For outbreak preparedness and response, the role of networks has been valued and useful for decades. The examples I will share have differences including in terms of governance yet all are impactful.

With personal experience of a number of such networks, I would like to share with you a practitioners experience of how these networks have evolved over the years including which methods were used to evolve and why they had to change.

I hope that I can learn from others to strengthen and further grow the ISARIC network, which is a federation of networks - a network of clinical research networks spanning over 130 countries. ISARIC is currently localising to the LMIC partners with decentralised decision making and leadership of research and capacity building.

Background: Stable close personal ties predict good mental health in adolescence. Evidence among young adults who have left formal education is more limited. We therefore describe how core network stability of rural South Africans predicts psychosocial wellbeing.

Methods: We study the first two waves of a sociocentric network study 20 months apart focused on young adults (ages 16-29) in rural South Africa run from 2022-25. At each wave respondents (egos) are asked to report on their key social contacts (alters); at Wave 2 respondents were asked what happened to their relationship with contacts named in Wave 1. Egos were also asked about their mental health using the 14-item Shona Symptom Questionnaire and the 8-item UCLA Loneliness Scale.

Preliminary Results: 429 individuals have completed both waves by February 2025. Egos named 3.2 alters in each wave, but 45% of alter identities changed. Baseline alters were 59% relatives, 31% friends and 10% sexual partners; family were most often retained, partners moderately and friends least. Poorer mental health at Wave 2 was associated with smaller baseline social networks and independently with greater turnover between waves, conditional on demographics, baseline mental health and network size. Wave 2 perceived social isolation was also greater in networks with more turnover but unrelated to network size.

Discussion: Unstable networks predict poor mental health among rural South African youth, suggesting targets for identifying those at risk and intervening to improve wellbeing. For Sunbelt we add data on alter types gained/lost and reasons for network turnover (e.g., interpersonal conflict, economic mobility), expecting negative peer influence and involuntary network loss to predict poor outcomes.