Over the past year, the Genetics Services Research Unit has completed several investigations in genetic counseling related research: One study of Bipolar disorder, an etiologically complex condition caused by genetic and environmental factors that affects 1-2% of the population aimed to understand the role of coping among adults adapting to bipolar disorder and the risk for a mood disorder in ones children. Methods: Adults were recruited from support/advocacy organizations to complete a web-based survey. Eligible participants reported having bipolar disorder and an unaffected child less than 31 years of age. Survey scales measured: illness perceptions, optimism, coping, adaptation, perception of childrens risk, and coping with risk to children. Our results found that participants were less well adapted to their condition than other populations of adults living with chronic conditions. Risks to ones children were associated with confidence in ones diagnosis (R=0.167, p=0.014), endorsing a genetic etiology (R=0-344, p<0.001), and having more affected individuals in the family (R=0.138, p=0.049). Multiple linear regression of parent adaptation included coping and optimism, and explained 55.9% of the variance (F=73.17, p<0.001). Multiple linear regression of parental coping included confidence in ones diagnosis and coping with bipolar disorder, and explained 10% of the variance (F=9.27, p<0.001). Effective coping strategies (active, social) may lead to greater adaptation to bipolar disorder and contribute to coping with risk to ones children. Confidence in ones own diagnosis affects parental perception of risk to ones children and to coping with perceived risk. Practice Implications: Clinical interventions aimed at increasing active and social coping with bipolar disorder are expected to lead to greater adaptation and more effective coping with perceived risks to ones children. Another study of parents with children with undiagnosed conditions explored the role of uncertainty. Uncertainty is a pervasive characteristic of illness. Yet little is known about the individual or situational factors that contribute to perceptions of uncertainty. This study aimed to examine the factors that contribute to perceived uncertainty among parents of a child with an undiagnosed condition. In this study, two hundred sixty six parents of a child, or children, affected by an undiagnosed medical condition for at least two years completed an electronically administered survey assessing theoretical predictors of perceived uncertainty. Multivariate linear regression analyses were used to identify the relationship of key variables to perceived uncertainty. Parents perceived control and optimism were negatively associated with uncertainty (B = -1.642, p <0.001, B = -0.300, p ≤0.01). Subjective disease severity was positively associated with perceived uncertainty (B = 1.388, p ≤0.001). Perceived control was negatively associated with two domains of uncertainty (ambiguity, p<0.001;lack of clarity, p<0.001). Our findings suggest that when parents experience greater uncertainty they feel less in control, which may lead to less effective coping and poorer adaptation. Areas where parents perceive greatest uncertainty may serve as targets for interventions to enhance perceptions of control over their childs condition. One study capitalized on the availability of new genetic technology. This study recruited 270 healthy insured adults age 25-40 from a parent research project, the Multiplex Initiative, which was conducted within a large health care system in Detroit MI, USA. All participants were offered a multiplex genetic test that assessed risk for eight conditions: type 2 diabetes, osteoporosis, hypertension, coronary heart disease, hypercholesterolemia, skin cancer, lung cancer and colorectal cancer. Data were collected from a baseline survey, a web-based decisional survey, and at the time of testing.
We aim ed to understand relationships between predictor variables and the decision to undergo testing using a conceptual model that originated from an amalgamation of the Theory of Planned Behavior and Protection Motivation Theory. Structural equation modeling identified response efficacy as a predictor (β=0.23, p<0.001) of attitudes toward multiplex genetic testing, which in turn predicted (β=0.46, p<0.001) intentions towards undergoing testing. Intentions to undergo testing were a strong predictor of testing behavior (β=0.97, p<0.001), with 17.67 fold higher uptake among those with intent to undergo testing than for those without. Overall, the tested model explained 56% of the variance in intentions and 95% of the variation in uptake. These findings support the use of variables from the Theory of Planned Behavior in modeling decision-making about a genetic test for multiple health conditions.
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