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Navigated African American breast cancer patients as incidental change agents in their family/friend networks
Navigated African American breast cancer patients as incidental change agents in their family/friend networks
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Navigated African American breast cancer patients as incidental change agents in their family/friend networks
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Navigated African American breast cancer patients as incidental change agents in their family/friend networks
Navigated African American breast cancer patients as incidental change agents in their family/friend networks
Journal Article

Navigated African American breast cancer patients as incidental change agents in their family/friend networks

2022
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Overview
Background Patient navigation is an increasingly widespread intervention to address the persistent, severe, and disproportionate breast cancer (BC) burden that African Americans (AA) face. Navigation may have more widespread effects than previously estimated due to patient-driven diffusion of BC information. Methods This pilot study examined the network effects of a randomized controlled trial via recruitment of navigated and non-navigated AA BC patients as well as their network members. We estimated study arm differences in patient BC promotion (i.e., number of individuals to whom BC patients promote BC screening) and network BC screening (i.e., % BC screening among network members). Results Among our sample of 100 AA BC patients, navigated patients promoted BC screening to more individuals than non-navigated patients. BC patients were more likely to promote BC screening to children and individuals with whom they communicated more frequently. Some models further suggested more network BC screening among “navigated” network members relative to “non-navigated” network members. Conclusions Navigated AA patients promoted BC screening more widely throughout their networks than non-navigated AA BC patients. There were also suggestive findings regarding increased BC screening among their network members. Our pilot study highlights the potential for social network analysis to improve the precision of intervention effect estimates and to inform future innovations (e.g., integrating navigation and network-based interventions) with multilevel effects on cancer health disparities.