All things considered, my risk for diabetes is medium: A risk personalization process of familial risk for type 2 diabetes

Daack‐Hirsch, Sandra; Shah, Lisa; Jones, K.P.; Rocha, Brenda Chung da; Doerr, Megan; Gabitzsch, Emily; Meese, Thad

doi:10.1111/hex.12986

Cited by 9 publications

(25 citation statements)

References 44 publications

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“…They brought unresolved discrepancies to a larger, four‐member research team, who made final decisions through consensus. At this point we had developed a robust qualitative data set with numerous codes characterizing the major FRP model constructs (Daack‐Hirsch et al, , ).…”

Section: Methodsmentioning

confidence: 99%

“…As part of the survey, participants recorded their perceived T2D risk as none, low, moderate, or high. Because only two individuals stated their risk for diabetes was none, the “none” and “low” groups were combined and labeled “low.” We calculated a clinical measure of risk using MyFamily, a proprietary family history collection and clinical decision support tool developed at Cleveland Clinic (Daack‐Hirsch et al, ). The MyFamily T2D algorithm classifies risk for diabetes as population risk (low risk), double the population risk (moderate risk), or triple the population risk (high risk) based on data collected in the study survey.…”

Section: Methodsmentioning

confidence: 99%

“…How individuals cope with and control their risk influences their sense of salience and perception of vulnerability. We found that salience includes family history but is not focused solely on family history (Daack‐Hirsch, Jones, Doerr, & Meese, ). We also found that processing risk was based on an interpretation and balancing of individual risk factors that included family history (Daack‐Hirsch et al, ) rather than only ongoing family events as proposed by Walter et al (, ).…”

Section: Introductionmentioning

confidence: 97%

“…We found that salience includes family history but is not focused solely on family history (Daack‐Hirsch, Jones, Doerr, & Meese, ). We also found that processing risk was based on an interpretation and balancing of individual risk factors that included family history (Daack‐Hirsch et al, ) rather than only ongoing family events as proposed by Walter et al (, ). Participants' explanations of disease causation for T2D were multifactorial and included social, cultural, biological, and environmental factors.…”

Section: Introductionmentioning

confidence: 97%

“…Their explanations and beliefs about cause were also reflected in their risk assessments in that several risk factors were implicated (Daack‐Hirsch et al, ). Participants assessed how well or the extent to which they engaged in healthful behaviors that influenced their FRP personalization process (Daack‐Hirsch et al, ). Figure depicts our T2D FRP personalization model.…”

Section: Introductionmentioning

confidence: 99%

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Type 2 diabetes familial risk personalization process profiles: Implications for patient–provider communication

Daack‐Hirsch

Schumacher

Shah

et al. 2019

Research in Nursing & Health

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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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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Type 2 diabetes familial risk personalization process profiles: Implications for patient–provider communication

Daack‐Hirsch

Schumacher

Shah

et al. 2019

Research in Nursing & Health

Self Cite

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Measurement of Perceived Risk of Developing Diabetes Mellitus: A Systematic Literature Review

et al. 2023

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BACKGROUND: This systematic review describes approaches to measuring perceived risk of developing type 2 diabetes among individuals without diagnoses and describes the use of theories, models, and frameworks in studies assessing perceived risk. While a systematic review has synthesized perceived risk of complications among individuals with diabetes, no reviews have systematically assessed how perceived risk is measured among those without a diagnosis. METHODS: Medline, PubMed, PsycINFO, and CINA-HAL databases were searched for studies conducted through October 2022 with measures of perceived risk among adults ≥ 18 years without a diabetes diagnosis. Extracted data included study characteristics, measures, and health behavior theories, models, or frameworks used. RESULTS: Eighty-six studies met inclusion criteria. Six examined perceived risk scales' psychometric properties. Eighty measured perceived risk using (1) a single item; (2) a composite score from multiple items or subconstructs; and (3) multiple subconstructs but no composite score. Studies used items measuring "comparative risk," "absolute or lifetime risk," and "perceived risk" without defining how each differed. Sixty-four studies used cross-sectional designs. Twenty-eight studies mentioned use of health behavior theories in study design or selection of measures. DISCUSSION: There was heterogeneity in how studies operationalized perceived risk; only one third of studies referenced a theory, model, or framework as guiding design or scale and item selection. Use of perceived lifetime risk, absolute risk, or comparative risk limits comparisons across studies. Consideration of context, target population, and how data are utilized is important when selecting measures; we present a series of questions to ask when selecting measures for use in research and clinical settings. This review is the first to categorize how perceived risk is measured in the diabetes prevention domain; most literature focuses on perceived risk among those with diabetes diagnoses. Limitations include exclusion of non-English and gray literature and single reviewer screening and data extraction.

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Advancing the communication of genetic risk for cardiometabolic diseases: A critical interpretive synthesis

Law

Sultan

Finer

et al. 2023

Preprint

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Genetics play an important role in risk for cardiometabolic diseases - including type 2 diabetes, cardiovascular disease and obesity. Existing research has explored the clinical utility of genetic risk tools such as polygenic risk scores - and whether interventions communicating genetic risk information using these tools can impact on individuals' cognitive appraisals of disease risk and/or preventative health behaviours. Previous systematic reviews exploring the evidence base suggest mixed results. To expand current understanding and address knowledge gaps, we undertook a reflexive method of evidence synthesis to the literature - questioning the theoretical basis behind current interventions that communicate genetic risk information and exploring how the effects of genetic risk tools can be fully harnessed for cardiometabolic diseases. We obtained 188 records from a combination of database, website and grey literature searches - supplemented with reference chaining and expert subject knowledge within the review team. Using pre-defined critical interpretive synthesis methods, quantitative and qualitative evidence was synthesised and critiqued alongside theoretical understanding from surrounding fields of behavioural and social sciences. Existing interventions communicating genetic risk information focus predominantly on the "self", targeting individual-level cognitive appraisals, such as perceived risk and perceived behavioural control. This approach risks neglecting the role of contextual factors and upstream determinants that can reinforce individuals' interpretations of risk. It also assumes target populations to embody an "ascetic subject of compliance" - the idea of a patient who strives to comply diligently with professional medical advice, logically and rationally adopting any recommended lifestyle changes. We developed a synthesising argument - beyond the "ascetic subject of compliance" - grounded in three major limitations of this perspective: (1) Difficulty applying existing theories/models to diverse populations; (2) The role of familial variables and (3) The need for a life course perspective. Interventions communicating genetic risk information should account for wider influences that can affect individuals' responses to risk at different levels - including through interactions with their family systems, socio-cultural environments and wider health provision.

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All things considered, my risk for diabetes is medium: A risk personalization process of familial risk for type 2 diabetes

Cited by 9 publications

References 44 publications

Type 2 diabetes familial risk personalization process profiles: Implications for patient–provider communication

Type 2 diabetes familial risk personalization process profiles: Implications for patient–provider communication

Measurement of Perceived Risk of Developing Diabetes Mellitus: A Systematic Literature Review

Advancing the communication of genetic risk for cardiometabolic diseases: A critical interpretive synthesis

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