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About
Background:
- Knowing one s family medical history is a part of staying healthy. Some health risks run in families, and knowing these risks can promote more healthy behavior. Different social and cultural factors may affect how family members share this information. Genetic risk information that is shared in one family may not be shared in the same way in another. This information may also be shared differently between spouses, siblings, or parents and children. It may even be shared with more distant relatives. Knowing the information that family members share and how they share it may help researchers improve genetic disease treatment and support plans. Family surveys of people who have genetic health risks may help provide this information.
Objectives:
- To study how family members affected by genetic-related diseases share health information with each other.
Eligibility:
Design:
Full description
Facilitating the dissemination of disease risk information and promoting engagement in healthful behaviors within families may be enhanced by using network-based interventions. Network-based interventions are innovative in that they are tailored to the structure of the social system within which individuals are embedded. Understanding the social and relational factors associated with processes of family risk dissemination, family encouragement, and support is essential to developing network-based intervention tools targeting the family. The first objective of the current project is to ascertain those key social pathways that can be used in a family-centered network-based intervention that promotes disease prevention and health promotion in at-risk families. To this end, efforts will be focused on assessing whether there is a consistent, small set of relational characteristics associated with the dissemination of family risk information and processes of both behavioral and emotional adaptation to disease risk across various disease and cultural contexts. The second objective is to examine the feasibility of using cognitive network approaches to assess social interactions among family members as a means to enhance the implementation of a network-based intervention. A cognitive network is an individual's perception of the relationships among their family (or network) members. Thus, cognitive network approaches can potentially be used to capture an accurate representation of family social structure based on the information provided by a small subset of optimally situated family members. Those key social pathways identified within the first objective of this research will be used to address the second objective. Families affected by diseases and disorders that span the spectrum of genetic penetrance, ranging from highly penetrant, monogenetic disease to less penetrant, common complex conditions, will be recruited for the study. Further, the current effort will seek to engage samples from diverse cultural backgrounds to address our limited knowledge regarding risk communication and adaptation in such families and to facilitate generalization of results. Study participants will be recruited from established cohorts, outreach events, or ongoing studies, both at the NIH and at extramural institutions. Family members will be recruited using a snowball sampling approach and will be asked to complete an in-person, web-based and/or telephone survey/interview. Interviews will have a semi-structured format to allow for slight deviations in prompts and probes to address participant questions. The research addressed in this protocol will lead to the development of an innovative methodology with the potential to improve the design and implementation of family-based interventions that promote disease prevention.
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Inclusion and exclusion criteria
EXCLUSION CRITERIA:
Individuals with cognitive difficulties will be excluded from the study, as participants will be required to comprehend and legally consent to participation in this study and complete the survey/interview(s).
1,061 participants in 3 patient groups
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Central trial contact
Laura M. Koehly, Ph.D.; Julia R Nummelin
Data sourced from clinicaltrials.gov
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