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, the 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). Recent efforts consider relational influences, such as 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 have not been identified. 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 addition, the section has begun to translate the Families SHARE workbook to a web-based application, providing a research infrastructure for families to use for gathering and sharing their family health history information.
Other goals in the Koehly group are to understand how genetics/genomics, biology and social relationships intersect. In one such project, the group studies genetic and other biological susceptibilities to social and environmental influences. They consider how genetic markers associated with sensation-seeking and risk-taking might influence the structuring of social networks. Their working hypothesis is that those with shared risk markers for sensation-seeking/risk-taking tendencies will be more likely to affiliate with each other, creating an informal social group that can be targeted for intervention. Such interventions might engage these informal groups in positive health behaviors that address members' shared biological needs for sensation-seeking. In so doing, these interventions may capitalize on informal social relationships for sustainable behavior change.
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 Tay Sachs disease, as well as for adults affected by diseases, such as Alzheimer's or Parkinson's disease. This research will consider biomarkers of stress and potential contagion of these markers among family members. 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 a Bayesian approach and imputation methods to "fill in the blanks" observed due to missing nodes and missing relational ties, offering a fuller picture of participant family systems, and to apply social network methods developed for complete 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.
Laura M. Koehly, Ph.D., is chief and senior investigator in the Social and Behavioral Research Branch, National Human Genome Research Institute (NHGRI), National Institutes of Health. She earned her Ph.D. in quantitative psychology from the University of Illinois - Urbana/Champaign. Following graduate school, Dr. Koehly was a research associate at the University of Texas, M.D. Anderson Cancer Center and on the faculty at the University of Iowa and Texas A&M University. Dr. Koehly joined the NHGRI faculty in 2005.
Dr. Koehly's research focuses on developing and applying social network methods to the study of complex social systems, such as families and communities. Her expertise is on family network systems and the role of family social ties in individual members' engagement in health behaviors. Dr. Koehly is particularly interested in how genetic/genomic risk information can be used to activate network processes to improve families' health. Understanding the familial culture from a network perspective is important for the delivery of healthcare services and dissemination of genetic risk information.
Ultimately, her research aims to develop effective strategies to help families cope with disease-risk information, to increase patients' willingness to share such information with their personal physician and other health care personnel, and to motivate encouragement within the family to increase adherence to risk-reducing behaviors.
A new line of research aims to understand factors associated with resilience to chronic stress in families engaged in high caregiver burden due to chronic illness. This work aims to understand caregiving from a network perspective, capturing the varying roles of formal care providers, such as healthcare providers (e.g., genetic counselors, general practitioners) or caregiving staff, family members, as well as those who are like family (e.g. friends) in the process of direct care provision, decision making, communication, and support in families affected by hereditary disease.
- Lin J, Marcum CS, Wilkinson AV, Koehly LM. Developing Shared Appraisals of Diabetes Risk Through Family Health History Feedback: The Case of Mexican-Heritage Families. Ann Behav Med. 2018;52(3):262-271.
- Krivitsky PN, Koehly LM, Marcum CS. Exponential-Family Random Graph Models for Multi-Layer Networks. Psychometrika. 2020;85(3):630-659.
- de la Haye K, Whitted C, Koehly LM. Formative Evaluation of the Families SHARE Disease Risk Tool among Low-Income African Americans. Public Health Genomics. 2021:1-11.
- Koehly LM, Marcum CS. Multi-relational measurement for latent construct networks. Psychol Methods. 2018;23(1):42-57.
- Ashida S, Marcum CS, Koehly LM. Unmet Expectations in Alzheimer's Family Caregiving: Interactional Characteristics Associated With Perceived Under-Contribution. Gerontologist. 2018;58(2):e46-e55.
Related Scientific Focus Areas
Social and Behavioral Sciences
Genetics and Genomics
This page was last updated on Monday, December 6, 2021