Validation of the Binge Eating Disorder Questionnaire (BED-Q) in Individuals with Type 2 Diabetes

Background Binge Eating Disorder (BED) is an eating disorder characterized by recurrent episodes of binge eating accompanied by a sense of loss of control. This study aimed to examine the reliability, validity, and classification accuracy of a new instrument, the Binge Eating Disorder Questionnaire (BED-Q), in a sample of 364 individuals diagnosed with Type 2 diabetes (T2D). Methods A total of 364 participants were included from a Danish cohort of 2,465 individuals with T2D. BED diagnosis was established using the Structured Clinical Interview for the DSM (SCID) based on the DSM-5 criteria, which served as the reference standard. The BED-Q was evaluated for internal consistency and unidimensionality using Cronbach’s alpha and confirmatory factor analysis (RMSEA, CFI, TLI, SRMR). Receiver Operating Characteristic (ROC) analyses assessed diagnostic performance, and optimal cut-off values were determined using the area under the curve (AUC), sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value, and Youden’s index. Results The BED-Q showed excellent internal consistency (Cronbach’s α = 0.94; average inter-item correlation = 0.68), and confirmatory factor analysis supported a one-factor model with good final model fit (χ² (11) = 8.239, p = 0.692, CFI = 1.000, TLI = 1.006, RMSEA = 0.000, SRMR = 0.014). ROC analyses indicated good diagnostic accuracy (AUC = 0.86). A cut-off score of 12 provided optimal discrimination between BED and non-BED cases (Youden’s index = 0.71, sensitivity = 0.91, specificity = 0.81, PPV = 0.77, NPV = 0.92). Conclusions The BED-Q demonstrated excellent reliability, unidimensionality, and diagnostic accuracy relative to a gold standard structured clinical interview. These findings support the use of the BED-Q as a valid screening instrument for BED. A cut-off score of 12 provided optimal sensitivity and specificity, consistent with DSM-5 and ICD-11 criteria. Further validation in diverse populations is recommended.