Pathways to suicidal ideation for young people engaged in mental health care.

Varidel, M; Hickie, IB; An, V; Cripps, S; Marchant, R; Robinson, J; La Sala, L; Capon, W; Turner, A; Tashevski, A; Scott, E; Iorfino, F

Pathways to suicidal ideation for young people engaged in mental health care.

Varidel, M Hickie, IB An, V Cripps, S

Marchant, R Robinson, J La Sala, L Capon, W Turner, A Tashevski, A Scott, E Iorfino, F

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Publisher:: W B SAUNDERS CO-ELSEVIER INC
Publication Type:: Journal Article
Citation:: Compr Psychiatry, 2025, 142, pp. 152611
Issue Date:: 2025-10

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Field	Value	Language
dc.contributor.author	Varidel, M
dc.contributor.author	Hickie, IB
dc.contributor.author	An, V
dc.contributor.author	Cripps, S https://orcid.org/0000-0003-3207-172X
dc.contributor.author	Marchant, R
dc.contributor.author	Robinson, J
dc.contributor.author	La Sala, L
dc.contributor.author	Capon, W
dc.contributor.author	Turner, A
dc.contributor.author	Tashevski, A
dc.contributor.author	Scott, E
dc.contributor.author	Iorfino, F
dc.date.accessioned	2026-02-13T01:26:56Z
dc.date.available	2025-06-05
dc.date.available	2026-02-13T01:26:56Z
dc.date.issued	2025-10
dc.identifier.citation	Compr Psychiatry, 2025, 142, pp. 152611
dc.identifier.issn	0010-440X
dc.identifier.issn	1532-8384
dc.identifier.uri	http://hdl.handle.net/10453/193464
dc.description.abstract	BACKGROUND: Suicidal thoughts and behaviours (STBs) have a profound impact on individuals, communities, and healthcare systems. A wide range of factors have been shown to be associated with STBs. Within prior research it is also common to distinguish between proximal and distal factors, usually by distinction of short compared to long-term prediction. OBJECTIVE: We aimed to learn the proximal and distal factors of suicidal ideation for young people engaged in mental health care using the inferred structure of probabilistic graphical models (PGMs). METHODS AND MATERIALS: We used cross-sectional data from a sample of 1020 help-seeking individuals aged 12-25 years from Australia that while engaged in mental health care, contributed data to a digital platform. The posterior distribution of the dependency structure assuming both undirected PGMs and Bayesian networks (BNs) was inferred. Causal effects were then estimated using a counterfactual query of the Bayesian networks. RESULTS: Depressed mood, functional impairment, poor social connection, and psychosis-like experiences were proximal factors. Whereas experiencing a traumatic event, anxiety, insomnia, and unrefreshed sleep were distal factors. Proximal factors had the greatest effect on suicidal ideation, while anxiety symptoms and experiencing a traumatic event were the most influential distal factors. CONCLUSIONS: These relative timings of events and their effects on suicidal ideation could be used to understand the future likelihood of suicidal ideation, and aid planning of targeted interventions.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	W B SAUNDERS CO-ELSEVIER INC
dc.relation	http://purl.org/au-research/grants/nhmrc/MRFCRI000279
dc.relation.ispartof	Compr Psychiatry
dc.relation.isbasedon	10.1016/j.comppsych.2025.152611
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	1103 Clinical Sciences
dc.subject.classification	Psychiatry
dc.subject.classification	3202 Clinical sciences
dc.subject.classification	5203 Clinical and health psychology
dc.subject.mesh	Humans
dc.subject.mesh	Suicidal Ideation
dc.subject.mesh	Adolescent
dc.subject.mesh	Male
dc.subject.mesh	Female
dc.subject.mesh	Young Adult
dc.subject.mesh	Cross-Sectional Studies
dc.subject.mesh	Adult
dc.subject.mesh	Australia
dc.subject.mesh	Child
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Mental Health Services
dc.subject.mesh	Risk Factors
dc.subject.mesh	Depression
dc.subject.mesh	Mental Disorders
dc.subject.mesh	Anxiety
dc.subject.mesh	Humans
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Risk Factors
dc.subject.mesh	Cross-Sectional Studies
dc.subject.mesh	Depression
dc.subject.mesh	Anxiety
dc.subject.mesh	Mental Disorders
dc.subject.mesh	Mental Health Services
dc.subject.mesh	Adolescent
dc.subject.mesh	Adult
dc.subject.mesh	Child
dc.subject.mesh	Australia
dc.subject.mesh	Female
dc.subject.mesh	Male
dc.subject.mesh	Young Adult
dc.subject.mesh	Suicidal Ideation
dc.subject.mesh	Humans
dc.subject.mesh	Suicidal Ideation
dc.subject.mesh	Adolescent
dc.subject.mesh	Male
dc.subject.mesh	Female
dc.subject.mesh	Young Adult
dc.subject.mesh	Cross-Sectional Studies
dc.subject.mesh	Adult
dc.subject.mesh	Australia
dc.subject.mesh	Child
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Mental Health Services
dc.subject.mesh	Risk Factors
dc.subject.mesh	Depression
dc.subject.mesh	Mental Disorders
dc.subject.mesh	Anxiety
dc.title	Pathways to suicidal ideation for young people engaged in mental health care.
dc.type	Journal Article
utslib.citation.volume	142
utslib.location.activity	United States
utslib.for	1103 Clinical Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Provost
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2026-02-13T01:26:55Z
pubs.publication-status	Published
pubs.volume	142

Abstract:

BACKGROUND: Suicidal thoughts and behaviours (STBs) have a profound impact on individuals, communities, and healthcare systems. A wide range of factors have been shown to be associated with STBs. Within prior research it is also common to distinguish between proximal and distal factors, usually by distinction of short compared to long-term prediction. OBJECTIVE: We aimed to learn the proximal and distal factors of suicidal ideation for young people engaged in mental health care using the inferred structure of probabilistic graphical models (PGMs). METHODS AND MATERIALS: We used cross-sectional data from a sample of 1020 help-seeking individuals aged 12-25 years from Australia that while engaged in mental health care, contributed data to a digital platform. The posterior distribution of the dependency structure assuming both undirected PGMs and Bayesian networks (BNs) was inferred. Causal effects were then estimated using a counterfactual query of the Bayesian networks. RESULTS: Depressed mood, functional impairment, poor social connection, and psychosis-like experiences were proximal factors. Whereas experiencing a traumatic event, anxiety, insomnia, and unrefreshed sleep were distal factors. Proximal factors had the greatest effect on suicidal ideation, while anxiety symptoms and experiencing a traumatic event were the most influential distal factors. CONCLUSIONS: These relative timings of events and their effects on suicidal ideation could be used to understand the future likelihood of suicidal ideation, and aid planning of targeted interventions.

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http://hdl.handle.net/10453/193464