Abstract A21: Exploring the social networks of newly diagnosed breast cancer patients

Abstract

Background: Minority women in the United States continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models such as patient navigation focus on the social causes of disparities, but evidence demonstrating how these interventions increase social support is lacking. Social network analysis provides a method to understand the complex social dynamics that contribute to better cancer outcomes. The purpose of this pilot study is to describe the social networks of newly-diagnosed breast cancer patients and explore the contributing role of patient navigators to those networks.

Methods: This descriptive pilot study explores the social networks of newly-diagnosed cancer patients enrolled in an active RCT comparing standard patient navigation versus patient navigation enhanced by legal advocacy. Eligible women were enrolled in the parent RCT, spoke English or Spanish, and agreed to complete the interview 3-7 months post-diagnosis. A convenience sample of 25 women was recruited to participate in a one hour interview to elicit information about their social networks related to cancer care support. Preliminary analysis visualized network structures to qualitatively identify patterns of network support (network types) and characterize the contributing role of types of support received (i.e. emotional and moral support, household help, access to resources). Secondly, network metrics (centrality, density, diversity, and knowledge exclusivity) were produced to quantify important structural attributes, influential individuals and critical types of supports. Comparisons using ANOVA identified potential differences between network types based on social network metrics.

Results: Participants had a mean age of 56.9 years (40-80). Forty six percent were Black, 21% White, 21% Hispanic and 12% Other. Three distinct network types were qualitatively identified: 1) Networks with predominantly kinship ties; 2) Networks with predominantly role-based and affective ties (i.e. health care workers and friends); and 3) Heterogeneous networks with multiple tie types. Examining network metrics in relation to network types indicated that role/affect-based networks were characterized by patients who had higher betweenness centrality, compared to kinship networks (p<0.05), indicating patients played a key role in connecting other network members. No other network-level metric was significantly associated with network type. In terms of types of support received, 21 of 24 networks had moral and emotional support holding the highest degree centrality (mean=0.743, SD=0.13), suggesting sampled patients received emotional/moral support from many sources. Patient navigators were identified in 6 of the 24 networks, despite all patients being assigned a patient navigator. In 4 of the 6 networks in which navigators were identified, they held the highest knowledge exclusivity, indicating that navigators provided types of support not found elsewhere in patient social networks.

Conclusions: Emotional and moral support is provided to cancer patients from many sources within their social networks. Among patients who identified navigators within their network, we found that they were able to provide distinctive support not found elsewhere in the network, suggesting they play a crucial role in the delivery of cancer care aimed at reducing disparities. Services and systems that identify and address deficits in specific types of support in patient social networks should be explored for their potential to reduce cancer health disparities.

Citation Format: Christine M. Gunn, Sharon M. Bak, Tracy A. Battaglia, Naomi Ko, Vanesa Noel, Victoria A. Parker. Exploring the social networks of newly diagnosed breast cancer patients. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr A21.