Modelling self-diagnosed burnout as a categorical syndrome.


Journal

Acta neuropsychiatrica
ISSN: 1601-5215
Titre abrégé: Acta Neuropsychiatr
Pays: England
ID NLM: 9612501

Informations de publication

Date de publication:
Feb 2023
Historique:
pubmed: 15 9 2022
medline: 14 2 2023
entrez: 14 9 2022
Statut: ppublish

Résumé

There is currently little consensus as to how burnout is best defined and measured, and whether the syndrome should be afforded clinical status. The latter issue would be advanced by determining whether burnout is a singular dimensional construct varying only by severity (and with some level of severity perhaps indicating clinical status), or whether a categorical model is superior, presumably reflecting differing 'sub-clinical' versus 'clinical' or 'burning out' vs 'burnt out' sub-groups. This study sought to determine whether self-diagnosed burnout was best modelled dimensionally or categorically. We recently developed a new measure of burnout which includes symptoms of exhaustion, cognitive impairment, social withdrawal, insularity, and other psychological symptoms. Mixture modelling was utilised to determine if scores from 622 participants on the measure were best modelled dimensionally or categorically. A categorical model was supported, with the suggestion of a sub-syndromal class and, after excluding such putative members of that class, two other classes. Analyses indicated that the latter bimodal pattern was not likely related to current working status or differences in depression symptomatology between participants, but reflected subsets of participants with and without a previous diagnosis of a mental health condition. Findings indicated that sub-categories of self-identified burnout experienced by the lay population may exist. A previous diagnosis of a mental illness from a mental health professional, and therefore potentially a psychological vulnerability factor, was the most likely determinant of the bimodal data, a finding which has theoretical implications relating to how best to model burnout.

Identifiants

pubmed: 36102161
pii: S0924270822000254
doi: 10.1017/neu.2022.25
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

50-58

Auteurs

Gabriela Tavella (G)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.

Michael J Spoelma (MJ)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.

Dusan Hadzi-Pavlovic (D)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.

Adam Bayes (A)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.
Black Dog Institute, Randwick, NSW, Australia.

Artin Jebejian (A)

Gordon Private Hospital, Sydney, NSW, Australia.

Vijaya Manicavasagar (V)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.
Black Dog Institute, Randwick, NSW, Australia.

Peter Walker (P)

Lumiere Clinical Psychology, Sydney, NSW, Australia.

Gordon Parker (G)

Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.
Gordon Private Hospital, Sydney, NSW, Australia.

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Classifications MeSH