Psychosocial markers of age at onset in bipolar disorder: a machine learning approach.

Bolton, Sorcha ORCID: 0000-0001-5857-6748, Joyce, Dan W ORCID: 0000-0002-9433-5340, Gordon-Smith, Katherine ORCID: 0000-0003-4083-1143, Jones, Lisa ORCID: 0000-0002-5122-8334, Jones, Ian ORCID: 0000-0001-5821-5889, Geddes, John and Saunders, Kate EA (2022) Psychosocial markers of age at onset in bipolar disorder: a machine learning approach. BJPsych open, 8 (4). e133-.

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Official URL: http://dx.doi.org/10.1192/bjo.2022.536

Abstract

<h4>Background</h4>Bipolar disorder is a chronic and severe mental health disorder. Early stratification of individuals into subgroups based on age at onset (AAO) has the potential to inform diagnosis and early intervention. Yet, the psychosocial predictors associated with AAO are unknown.<h4>Aims</h4>We aim to identify psychosocial factors associated with bipolar disorder AAO.<h4>Method</h4>Using data from the Bipolar Disorder Research Network UK, we employed least absolute shrinkage and selection operator regression to identify psychosocial factors associated with bipolar disorder AAO. Twenty-eight factors were entered into our model, with AAO as our outcome measure.<h4>Results</h4>We included 1022 participants with bipolar disorder (μ = 23.0, s.d. ± 9.86) in our model. Six variables predicted an earlier AAO: childhood abuse (β = -0.2855), regular cannabis use in the year before onset (β = -0.2765), death of a close family friend or relative in the 6 months before onset (β = -0.2435), family history of suicide (β = -0.1385), schizotypal personality traits (β = -0.1055) and irritable temperament (β = -0.0685). Five predicted a later AAO: the average number of alcohol units consumed per week in the year before onset (β = 0.1385); birth of a child in the 6 months before onset (β = 0.2755); death of parent, partner, child or sibling in the 6 months before onset (β = 0.3125); seeking work without success for 1 month or more in the 6 months before onset (β = 0.3505) and a major financial crisis in the 6 months before onset (β = 0.4575).<h4>Conclusions</h4>The identified predictor variables have the potential to help stratify high-risk individuals into likely AAO groups, to inform treatment provision and early intervention.

Item Type:	Article
Uncontrolled Keywords:	Bipolar affective disorders, aetiology, childhood experience, psychosocial interventions, statistical methodology
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health
Depositing User:	Symplectic Admin
Date Deposited:	13 Jun 2023 14:44
Last Modified:	18 Mar 2024 03:31
DOI:	10.1192/bjo.2022.536
Open Access URL:	https://www.cambridge.org/core/journals/bjpsych-op...
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3170968