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Casting wider nets for anxiety and depression: disability-driven cross-diagnostic subtypes in a large cohort

Published online by Cambridge University Press:  14 September 2016

R. B. K. Wanders ,
H. M. van Loo ,
J. K. Vermunt ,
R. R. Meijer ,
C. A. Hartman ,
R. A. Schoevers ,
K. J. Wardenaar  and
P. de Jonge
R. B. K. Wanders*
Affiliation:
University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Groningen, The Netherlands
H. M. van Loo
Affiliation:
University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Groningen, The Netherlands
J. K. Vermunt
Affiliation:
Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands
R. R. Meijer
Affiliation:
Department of Psychometrics and Statistics, University of Groningen, Groningen, The Netherlands
C. A. Hartman
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
R. A. Schoevers
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
K. J. Wardenaar
Affiliation:
University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Groningen, The Netherlands
P. de Jonge
Affiliation:
University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Groningen, The Netherlands
*
*Address for correspondence: R. B. K. Wanders, M.Sc., Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, P.O. Box 30.001, 9700 RB, Groningen, The Netherlands. (Email: r.b.k.wanders@umcg.nl)
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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.

Keywords

Anxietydepressiondisabilitylatent variable mixture modellingsubtypes
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 16 , December 2016 , pp. 3371 - 3382
Copyright
Copyright © Cambridge University Press 2016 

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