Discriminability of the Beck Depression Inventory and its Abbreviations in an Adolescent Psychiatric Sample

Background: The Beck Depression Inventory (BDI) is a widely acknowledged self-report screening tool for evaluating the presence and intensity of depressive symptoms. The BDI-IA, although an older version, is highly correlated with the updated BDI-II, remains clinically valuable, and is widely used due to its free availability. Aim: This study aimed to examine the psychometric properties of the BDI-IA and compare its diagnostic accuracy with the abbreviated BDI-SF, BDI-PC, and BDI-6 versions against gold-standard research diagnoses in a representative Finnish adolescent clinical population. Methods: The participants were referred outpatient adolescents aged 13-20 years (N = 752, 73% female). We investigated structural validity with item factor analysis and evaluated the criterion validity of mean scores and factor scores with various diagnostic measures. Sample-optimal cut-offs (criterion unweighted Cohen's kappa) were estimated with a bootstrap procedure. Results: The sample-optimal cut-off for the full BDI was 19, slightly higher than that suggested by the previous literature. The abbreviations of the BDI-IA were demonstrated to be as good as the full scale in detecting depressive symptoms in all three diagnostic categorizations. Conclusion: The use of brief and user-friendly questionnaires such as the BDI-PC or BDI-6 is recommended to ensure optimal depression screening and minimize the administrative burden, especially in primary care settings where clinical decision-making and referrals often need to occur within a limited time frame.