R B K Wanders1, H M van Loo1, J K Vermunt2, R R Meijer3, C A Hartman4, R A Schoevers4, K J Wardenaar1, P de Jonge1. 1. University of Groningen, University Medical Center Groningen,Interdisciplinary Center Psychopathology and Emotion regulation (ICPE),Groningen,The Netherlands. 2. Department of Methodology and Statistics,Tilburg University,Tilburg,The Netherlands. 3. Department of Psychometrics and Statistics,University of Groningen,Groningen,The Netherlands. 4. Department of Psychiatry,University of Groningen, University Medical Center Groningen,Groningen,The Netherlands.
Abstract
BACKGROUND: In search of empirical classifications of depression and anxiety, most subtyping studies focus solely on symptoms and do so within a single disorder. This study aimed to identify and validate cross-diagnostic subtypes by simultaneously considering symptoms of depression and anxiety, and disability measures. METHOD: A large cohort of adults (Lifelines, n = 73 403) had a full assessment of 16 symptoms of mood and anxiety disorders, and measurement of physical, social and occupational disability. The best-fitting subtyping model was identified by comparing different hybrid mixture models with and without disability covariates on fit criteria in an independent test sample. The best model's classes were compared across a range of external variables. RESULTS: The best-fitting Mixed Measurement Item Response Theory model with disability covariates identified five classes. Accounting for disability improved differentiation between people reporting isolated non-specific symptoms ['Somatic' (13.0%), and 'Worried' (14.0%)] and psychopathological symptoms ['Subclinical' (8.8%), and 'Clinical' (3.3%)]. Classes showed distinct associations with clinically relevant external variables [e.g. somatization: odds ratio (OR) 8.1-12.3, and chronic stress: OR 3.7-4.4]. The Subclinical class reported symptomatology at subthreshold levels while experiencing disability. No pure depression or anxiety, but only mixed classes were found. CONCLUSIONS: An empirical classification model, incorporating both symptoms and disability identified clearly distinct cross-diagnostic subtypes, indicating that diagnostic nets should be cast wider than current phenomenology-based categorical systems.
BACKGROUND: In search of empirical classifications of depression and anxiety, most subtyping studies focus solely on symptoms and do so within a single disorder. This study aimed to identify and validate cross-diagnostic subtypes by simultaneously considering symptoms of depression and anxiety, and disability measures. METHOD: A large cohort of adults (Lifelines, n = 73 403) had a full assessment of 16 symptoms of mood and anxiety disorders, and measurement of physical, social and occupational disability. The best-fitting subtyping model was identified by comparing different hybrid mixture models with and without disability covariates on fit criteria in an independent test sample. The best model's classes were compared across a range of external variables. RESULTS: The best-fitting Mixed Measurement Item Response Theory model with disability covariates identified five classes. Accounting for disability improved differentiation between people reporting isolated non-specific symptoms ['Somatic' (13.0%), and 'Worried' (14.0%)] and psychopathological symptoms ['Subclinical' (8.8%), and 'Clinical' (3.3%)]. Classes showed distinct associations with clinically relevant external variables [e.g. somatization: odds ratio (OR) 8.1-12.3, and chronic stress: OR 3.7-4.4]. The Subclinical class reported symptomatology at subthreshold levels while experiencing disability. No pure depression or anxiety, but only mixed classes were found. CONCLUSIONS: An empirical classification model, incorporating both symptoms and disability identified clearly distinct cross-diagnostic subtypes, indicating that diagnostic nets should be cast wider than current phenomenology-based categorical systems.
Authors: Naoise Mac Giollabhui; Lauren B Alloy; Lizanne J S Schweren; Catharina A Hartman Journal: Brain Behav Immun Date: 2021-05-27 Impact factor: 19.227
Authors: Lian Beijers; Hanna M van Loo; Jan-Willem Romeijn; Femke Lamers; Robert A Schoevers; Klaas J Wardenaar Journal: Psychol Med Date: 2020-08-11 Impact factor: 10.592
Authors: K J E Kokkeler; R M Marijnissen; K J Wardenaar; D Rhebergen; R H S van den Brink; R C van der Mast; R C Oude Voshaar Journal: Psychol Med Date: 2020-07-03 Impact factor: 7.723