Type 2 diabetes familial risk personalization process profiles: Implications for patient–provider communication
Corresponding Author
Sandra Daack-Hirsch PhD, RN
College of Nursing, University of Iowa, Iowa City, Iowa
Correspondence Sandra Daack-Hirsch PhD, RN, Associate Professor, University of Iowa, College of Nursing, 50 Newton Rd, Iowa City, IA. Email: [email protected]
Search for more papers by this authorAmy C. Schumacher PhD, MS
College of Public Health, University of Iowa, Iowa City, Iowa
Search for more papers by this authorLisa Shah PhD, RN
School of Nursing, University of Pittsburgh, Pittsburg, Pennsylvania
Search for more papers by this authorShelly Campo PhD
College of Public Health, University of Iowa, Iowa City, Iowa
Search for more papers by this authorCorresponding Author
Sandra Daack-Hirsch PhD, RN
College of Nursing, University of Iowa, Iowa City, Iowa
Correspondence Sandra Daack-Hirsch PhD, RN, Associate Professor, University of Iowa, College of Nursing, 50 Newton Rd, Iowa City, IA. Email: [email protected]
Search for more papers by this authorAmy C. Schumacher PhD, MS
College of Public Health, University of Iowa, Iowa City, Iowa
Search for more papers by this authorLisa Shah PhD, RN
School of Nursing, University of Pittsburgh, Pittsburg, Pennsylvania
Search for more papers by this authorShelly Campo PhD
College of Public Health, University of Iowa, Iowa City, Iowa
Search for more papers by this authorAbstract
People who have a single first-degree relative with type 2 diabetes (T2D) are at increased risk for developing T2D over their lifetime. A positive family history of T2D is also associated with developing risk awareness and engaging in risk-reducing behaviors among the unaffected relatives. Yet, little is known about how people with a positive family history for disease personalize and process their familial risk to form perceptions about their own risk. In this mixed method study, we explored risk personalization among a diverse group of people between the ages of 18 and 60, with a positive family history of T2D, who were themselves unaffected (n = 109). We collected interview and survey data with respect to the familial risk perception personalization model. Using cluster analysis, qualitative and quantitative data were combined to inductively derive three distinct clusters representing three different familial risk perception personalization processes. These results can serve as a basis for tailored interventions aimed at reducing risk for T2D among people with increased risk due to familial history.
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