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Comprehensive investigation of factor structure and gender equivalence of the Beck Depression Inventory-II among nonclinical adolescents.

Ana Paula Ferreira-MaiaClarice GorensteinYuan-Pang Wang
Published in: European child & adolescent psychiatry (2024)
The Beck Depression Inventory-II (BDI-II) is a widely used tool for rating the severity of depressive symptoms. Studies on the factor structure of the BDI-II in adolescents have yielded controversial findings. Most studies have reported an oblique two-factor model that describes the 'cognitive' and 'somatic-affective' dimensions. However, there is variation in the item composition of each factor across studies. Alternative factor structures have been proposed, including one-factor, three-factor, hierarchical, and bifactor models. Additionally, there is limited data on measurement invariance across genders. This study aimed to examine hypothetical factor structures and gender equivalence of the BDI-II in a sample of Brazilian nonclinical adolescents (N = 1,184, aged 13-18 years, 59.1% females). Cross-validation of the BDI-II was performed through exploratory (EFA) and confirmatory factor analysis (CFA). Measurement invariance was evaluated using multigroup-CFA (MG-CFA). EFA suggested an oblique two-factor model depicting "affective-cognitive" and "somatic" dimensions. CFA tested competing models for the structure of BDI-II, including the simple one- and two-factor models, a bifactor model, and the EFA model along with its corresponding bifactor model. All models demonstrated adequate and similar fitness, well-defined factors, and good reliability. Bifactor analyses indicated a robust general factor with low reliable variance in total scores attributed to multidimensionality caused by the group factors in bifactor models. MG-CFA supported invariance across gender, suggesting that the same BDI-II construct could be applied to both female and male adolescents. This study provides evidence that the BDI-II could be used as a unidimensional measure of depressive symptoms in adolescents by researchers and clinicians.
Keyphrases
  • depressive symptoms
  • young adults
  • physical activity
  • mental health
  • machine learning
  • mass spectrometry
  • palliative care
  • dna methylation
  • sleep quality