Publication
Title
Identifying panic disorder subtypes using factor mixture modeling
Author
Abstract
Background: The clinical presentation of panic disorder (PD) is known to be highly heterogeneous, complicating research on its etiology, neurobiological pathways, and treatment. None of the attempts to identifyPD subtypes have been independently reproduced, rendering the current literature inconclusive. Methods: Using a data-driven, case-centered approach (factor mixture modeling) on a broad range of anxiety symptoms assessed with the Beck anxiety inventory, the present study identifies PD disorder subtypes in a large (n = 658), welldocumented mixed-population sample from the Netherlands Study of Depression and Anxiety (NESDA), with subtypes being validated and detailed using a variety of clinical characteristics. Results: A three-class, one-factor model proved superior to all other possible models (Bayesian information criterion = 13,200; Lo-Mendel-Rubin = 0.0295; bootstrapped likelihood ratio test 0.0001), with the first class, a cognitive-autonomic subtype, accounting for 29.8%, the second class, the autonomic subtype, for 29.9%, and a third class, the aspecific subtype, for 40.3% of the population. The cognitive-autonomic and autonomic subtypes showed significant differences compared to the aspecific subtype (e.g., comorbidity and suicide attempts) but on severity differed between themselves only. Conclusion: Three qualitatively different PD subtypes were identified: a severe cognitive-autonomic subtype, a moderate autonomic subtype, and a mild aspecific subtype. Qualitative and quantitative differences were related to severity and clinical properties such as comorbidity, suicide attempts, sleep, and sense of mastery.
Language
English
Source (journal)
Depression and anxiety. - -
Publication
2015
ISSN
1091-4269
Volume/pages
32:7(2015), p. 509-517
ISI
000357330700006
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 12.05.2015
Last edited 15.09.2017
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