It is widely acknowledged that social network support plays an important role in the quality of life and illness management of breast cancer survivors. However, the factors and processes that enable and sustain such support are less well understood. This paper reports baseline findings from a prospective UK national cohort of 1,202 women with breast cancer (aged <50 years at diagnosis), recruited before starting treatment, conducted in 2016-2019. Descriptive, univariate and multivariate regression analyses explored associations between the individual, and network member characteristics, and the type of support provided. Social network members provided a substantial level of illness-related, practical and emotional support. Highest contribution was provided by friends, followed by close family members. The social network members of women who did not have a partner provided a higher level of support than those in networks with a partner. Women without higher education were more reliant on close family members than those with higher education, and this was more so for women without a partner. Women with higher education without a partner were more reliant on friends and were overall best supported. Women without higher education who did not have a partner were overall least well supported. They had much smaller networks, were highly reliant on close family members, and on high level contributions from all network members. There is a need to develop network-based interventions to support people with a cancer diagnosis, prioritising support for the groups identified as most at risk. Interventions that support engagement with existing network members during treatment, and those that help extend such networks after treatment, are likely to be of benefit. A network perspective can help to develop tailored support and interventions by recognising the interactions between network and individual level processes.
Copyright: © 2023 Vassilev et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.