Under Dr. Koehly's leadership, the Social Network Methods Section focuses on three main scientific goals: 1) to develop methods that measure and model the complexities of relational systems; 2) to use such models to understand the social, psychological and communicative context of families at risk of hereditary and complex diseases; and, 3) to translate these findings into effective network-based interventions. The section applies these goals within three ongoing lines of research.
In their first line of research, section members aim to examine the influence of social relationships on the communication of genetic and genomic risk information within families (e.g., family health history, genetic test results) and behavioral encouragement, on individual health outcomes, including lifestyle and screening behaviors. One of the section's major findings is that family relationships are crucial to individual engagement in such behaviors, indicating the need for interventions that activate and enrich family connections. As new technologies advance the translation of genomic discoveries into clinical and public health settings, the role of the family network system in improving members' health outcomes has become more pronounced. Thus, Dr. Koehly engages in evaluating the influence of the familial social context on communication and encouragement processes, with the goal of defining interventions to promote healthy behaviors. Her research group has identified a set of common interpersonal processes underlying genetic risk communication within families for whom Lynch syndrome mutations and, separately, BRCA1/2 mutations, have been identified, or following uninformative genetic test results. However, it is unclear whether these processes are analogous across disease contexts. Accordingly, the researchers currently are investigating genomic risk communication and adaptation to risk in families across a diverse array of disease assessments. They also are investigating the role of non-family network ties, and variability due to cultural or ethnic context.
Through one such initiative, Families SHARE, the researchers are focused on developing tools to help families understand the role of family health history in their risk of common complex disease. These tools are not only educational, but also provide a platform for family members to engage in conversations about shared risk and to develop cooperative approaches for risk reduction. The researchers have developed a Families SHARE workbook that has been evaluated by key stakeholders in the community and is currently being used in a cross-cultural randomized control trial. In another project, Dr. Koehly is investigating how social relationships become subject to strain. Her group examines how social connections may improve resilience or exacerbate vulnerability of families with high levels of caregiving burden. They recently completed a pilot study to investigate caregiving networks that surround those affected by Alzheimer's disease, characterized by professional care providers and informal caregivers. This work has expanded to consider caregiving across the life course by studying caregiving for children affected by chronic health conditions, such as inborn errors of metabolism or Batten disease CLN3, as well as for adults affected by diseases, such as Alzheimer's or Parkinson's disease. This research will consider biomarkers of stress. The goal of this work is twofold: 1) to identify factors associated with resilience to chronic stress in families with high caregiver burden, and 2) to identify points of intervention that reduce stress response and improve health of those involved in caring for a loved one affected by chronic illness.
The third arm of research focuses on the development of methods to model the complexities of social systems in three broad areas. First, Dr. Koehly's research group explores problems in network measurement. This research aims to identify optimal approaches for combining multiple relational measurements that tap into the same underlying construct, with the goal of developing measures of reliability and validity for relational constructs. Second, the group aims to address the incomplete social network data common to the study of family systems or community-based research. These methods use both Bayesian and Frequentist approaches and imputation methods to "fill in the blanks" observed due to missing nodes and missing relational ties, offering a more complete picture of participant family systems, and to apply social network methods developed for whole networks to these studies. Finally, Dr. Koehly's group is developing methods to address questions related to informant accuracy. In so doing, they can identify key players in the network system that might be identified as family genomics health educators or primary care providers, based on assessments obtained from multiple informants.
Social Network Methods Section Members
Christopher Marcum, Ph.D., Staff Scientist
Dawn Lea, Ph.D., Nurse Consultant
Mindy Perilla, MPH, CCRC., Project Coordinator
Megan Cooper, LICSW, Clinical Research Coordinator
Jasmine Manalel, Ph.D., Postdoctoral Fellow
Calandra Whitted, MSPH, Graduate Student Fellow
Lena Eskin, BS, Post baccalaureate Fellow
Aaron Gurayah, BA, Post baccalaureate Fellow
Kelly Nguyen, BS, Undergraduate Scholarship Program Fellow
Anna Shetler, BA, Post baccalaureate Fellow
Tracy Swan, BS, Post baccalaureate Fellow
Fiona Gilpin Macfoy, Student Intern
Last Updated: March 1, 2019