ReviewEvidence-based mental health2019
How accurate are suicide risk prediction models? Asking the right questions for clinical practice.
Review in Evidence-based mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Prediction models for self-harm and suicide: a systematic review and critical appraisal.BMC medicine · 2025Pooled it
- Digital cognitive-behavioural therapy to reduce suicidal ideation and behaviours: a systematic review and meta-analysis of individual participant data.Evidence-based mental health · 2022Pooled it
- Antidepressants in Children and Adolescents: Meta-Review of Efficacy, Tolerability and Suicidality in Acute Treatment.Frontiers in psychiatry · 2020Pooled it
- Suicidal Thoughts and Behaviors Do Not Influence Veterans' Alcohol Use Disorder or Posttraumatic Stress Disorder Recovery Trajectories in a Randomized Controlled Trial.Journal of studies on alcohol and drugs · 2026Trial
- Diagnostic accuracy of machine learning approaches for suicide‑related outcomes: a meta‑analysis.Annals of general psychiatry · 2026Article
- Enhancing personalized suicide risk prediction for VA patients by integrating discrete natural language processing models.Translational psychiatry · 2026Article
- A hierarchical machine learning model for predicting self-harm and suicidal behaviour in hospitalised patients with schizophrenia using clinical history and nursing observations.Frontiers in psychiatry · 2026Article
- Comparing structured versus unstructured suicide risk assessment across health professionals and the general population: a vignette-based study protocol (CARE).Frontiers in psychiatry · 2026Article
- Suicide Risk Assessments Understood as Medical Rituals: Functions and Implications from Societal and Medico-Ethical Perspectives.Journal of bioethical inquiry · 2025Article
- A biological phenotype of suicide attempt in adolescents with nonsuicidal self-injury: a machine-based learning approach.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025Article
- Moving Toward Meaningful Evaluations of Monitoring in e-Mental Health Based on the Case of a Web-Based Grief Service for Older Mourners: Mixed Methods Study.JMIR formative research · 2024Article
- Automatically extracting social determinants of health for suicide: a narrative literature review.Npj mental health research · 2024Review
- Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis.International journal of public health · 2024Article
- Development of mental health first-aid guidelines for suicide risk: a Delphi expert consensus study in Argentina and Chile.BMC psychiatry · 2023Article
- Article
- Predicting HIV infection in the decade (2005-2015) pre-COVID-19 in Zimbabwe: A supervised classification-based machine learning approach.PLOS digital health · 2023Article
- Risk of death by suicide following self-harm presentations to healthcare: development and validation of a multivariable clinical prediction rule (OxSATS).BMJ mental health · 2023Article
- Machine learning based identification of structural brain alterations underlying suicide risk in adolescents.Discover mental health · 2023Article
- A genetically informed prediction model for suicidal and aggressive behaviour in teens.Translational psychiatry · 2022Article
- Machine Learning Prediction of Suicide Risk Does Not Identify Patients Without Traditional Risk Factors.The Journal of clinical psychiatry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Prediction models assist in stratifying and quantifying an individual's risk of developing a particular adverse outcome, and are widely used in cardiovascular and cancer medicine. Whether these approaches are accurate in predicting self-harm and suicide has been questioned. We searched for systematic reviews in the suicide risk assessment field, and identified three recent reviews that have examined current tools and models derived using machine learning approaches. In this clinical review, we present a critical appraisal of these reviews, and highlight three major limitations that are shared between them. First, structured tools are not compared with unstructured assessments routine in clinical practice. Second, they do not sufficiently consider a range of performance measures, including negative predictive value and calibration. Third, the potential role of these models as clinical adjuncts is not taken into consideration. We conclude by presenting the view that the current role of prediction models for self-harm and suicide is currently not known, and discuss some methodological issues and implications of some machine learning and other analytic techniques for clinical utility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.