RESUMO
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 CINAHAL 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.
