Categorical differentiation of the unipolar and bipolar disorders

Gordon Parker, Michael J. Spoelma, Gabriela Tavella, Martin Alda, Tomas Hajek, David L. Dunner, Claire O. Donovan, Janusz K. Rybakowski, Joseph F. Goldberg, Adam Bayes, Verinder Sharma, Philip Boyce, Vijaya Manicavasagar

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

There has been a longstanding debate as to whether the bipolar disorders differ categorically or dimensionally, with some dimensional or spectrum models including unipolar depressive disorders within a bipolar spectrum model. We analysed manic/hypomanic symptom data in samples of clinically diagnosed bipolar I, bipolar II and unipolar patients, employing latent class analyses to determine if separate classes could be identified. Mixture analyses were also undertaken to determine if a unimodal, bimodal or a trimodal pattern was present. For both a refined 15-item set and an extended 30-item set of manic/hypomanic symptoms, our latent class analyses favoured three-class solutions, while mixture analyses identified trimodal distributions of scores. Findings argue for a categorical distinction between unipolar and bipolar disorders, as well as between bipolar I and bipolar II disorders. Future research should aim to consolidate these results in larger samples, particularly given that the size of the unipolar group in this study was a salient limitation.

Original languageEnglish
Article number113719
JournalPsychiatry Research
Volume297
DOIs
Publication statusPublished - Mar 2021

Bibliographical note

Funding Information:
The study was funded by grants (# 1037196 , # 1176689 ) received from the Australian National Health and Medical Research Council (NHMRC). The contents of the published material are solely the responsibility of the individual authors and do not reflect the views of the NHMRC.

Publisher Copyright:
© 2021

ASJC Scopus Subject Areas

  • Psychiatry and Mental health
  • Biological Psychiatry

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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