Objectives/Goals: This study’s objective was to explore how a personal cancer diagnosis impacts the social connectedness (i.e., quality, structure, and functions of social relationships) of adolescent/young adult cancer survivors (AYACS, patients diagnosed with cancer between 15 and 39 years old), to inform intervention development fostering social health. Methods/Study Population: In this qualitative study (part of larger study assessing AYACS’ psychosocial challenges), participants were 15–25 years old at the time of cancer diagnosis and within 6 years of cancer diagnosis. Participants (and consenting parents of participants 18 years old and older) had to have fluency in written and spoken English and access to a computer or smartphone. Qualitative interviewers utilized an interview guide to conduct individual participant interviews. Interviews were audio-recorded and transcribed verbatim. Thematic analysis was used to analyze data using a phenomenological approach to explore how a personal cancer diagnosis impacted social connectedness. Qualitative data related to social connectedness (corresponding to code “Relationships and Support”) are presented. Results/Anticipated Results: Three themes emerged through thematic analysis: (1) AYACS experience substantial heterogeneity related to social support needs; (2) AYACS leverage multiple relationships and resources when seeking support after a personal cancer diagnosis; (3) AYACS’ individual experiences were unique in that some noted positive changes, whereas others noted negative changes in relationships within social networks, specifically with peers. Discussion/Significance of Impact: AYACS experience various social support needs, and leverage multiple relationships when seeking social support. These translational findings create a foundation to develop AYACS social programming, foster peer relationships, and incorporate social science methods to aid intervention development to strengthen AYACS’ social connectedness.

Multi-layer networks arise when more than one type of relation is observed on a common set of actors. Modeling such networks within the exponential-family random graph (ERG) framework has been previously limited to special cases and, in particular, to dependence arising from just two layers. Extensions to ERGMs are introduced to address these limitations: Conway–Maxwell–Binomial distribution to model the marginal dependence among multiple layers; a “layer logic” language to translate familiar ERGM effects to substantively meaningful interactions of observed layers; and nondegenerate triadic and degree effects. The developments are demonstrated on two previously published datasets.

Genetic risk is particularly salient for families and testing for genetic conditions is necessarily a family-level process. Thus, risk for genetic disease represents a collective stressor shared by family members. According to communal coping theory, families may adapt to such risk vis-a-vis interpersonal exchange of support resources. We propose that communal coping is operationalized through the pattern of supportive relationships observed between family members. In this study, we take a social network perspective to map communal coping mechanisms to their underlying social interactions and include those who declined testing or were not at risk for Lynch Syndrome. Specifically, we examine the exchange of emotional support resources in families at risk of Lynch Syndrome, a dominantly inherited cancer susceptibility syndrome. Our results show that emotional support resources depend on the testing-status of individual family members and are not limited to the bounds of the family. Network members from within and outside the family system are an important coping resource in this patient population. This work illustrates how social network approaches can be used to test structural hypotheses related to communal coping within a broader system and identifies structural features that characterize coping processes in families affected by Lynch Syndrome.