ArticleThe Australian and New Zealand journal of psychiatry2023
Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.
Article in The Australian and New Zealand journal of psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Lived Experience Participation in Suicide Prevention Activities in Australia, a Scoping Review.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Graph learning based suicidal ideation detection via tree-drawing test.Frontiers in psychiatry · 2025Article
- Untapped Potential of Unobtrusive Observation for Studying Health Behaviors.JMIR public health and surveillance · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePrior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways to continually monitor such sites, limiting the potential to intervene. In this mixed-methods study, we examined the acceptability and feasibility of using an automated computer system to identify crisis behaviours.
methodsFirst, we conducted a large-scale acceptability survey to assess public perceptions on research using closed-circuit television and artificial intelligence for suicide prevention. Second, we identified crisis behaviours at a frequently used cliff location by manual structured analysis of closed-circuit television footage. Third, we configured a computer vision algorithm to identify crisis behaviours and evaluated its sensitivity and specificity using test footage.
resultsOverall, attitudes were positive towards research using closed-circuit television and artificial intelligence for suicide prevention, including among those with lived experience. The second study revealed that there are identifiable behaviours, including repetitive pacing and an extended stay. Finally, the automated behaviour recognition algorithm was able to correctly identify 80% of acted crisis clips and correctly reject 90% of acted non-crisis clips.
conclusionThe results suggest that using computer vision to detect behaviours preceding suicide is feasible and well accepted by the community and may be a feasible method of initiating human contact during a crisis.
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Registered trials
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