Evidence of a transdiagnostic cognitive-factor for the assessment of depression and anxiety disorders in primary care patients.

Depression and anxiety disorders are the most prevalent mental disorders in the world. The transdiagnostic approach to the study of these emotional disorders suggests that certain diagnostic categories, such as depression or anxiety disorders, share common underlying factors. This paper evaluated several models of common maladaptive cognitive factors in depressive and anxiety disorders (Study 1) and the predictive validity of these models (Study 2). In Study 1, 1703 primary care patients with suspected emotional disorder completed brief scales to assess the following cognitive factors: worry, rumination, attention to threat, and metacognitions. We found that the model with the best fit was the bifactor model, estimated through an exploratory structural equation model (ESEM). This bifactor model suggests that individual cognitive factors can be explained by a general factor plus four independent factors, evidencing the existence of a transdiagnostic cognitive factor (TD-C factor). In Study 2, a subgroup of 178 participants (from Study 1) were clinically diagnosed by semi-structured clinical interviews with major depressive disorder, generalized anxiety disorder, and/or panic disorder. The predictive validity of TD-C factor was acceptable (AUC > 0.80), but specific factors were not predictive (AUC < 0.70), indicating that TD-C factor was a significant predictor for each diagnosis. This study supports the claim that there is a transdiagnostic cognitive factor that can predict the diagnosis of various depressive and anxiety disorders, thus potentially representing a useful transdiagnostic assessment.