ReviewMolecular psychiatry2020
Suicide prediction models: a critical review of recent research with recommendations for the way forward.
Review in Molecular psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.
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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.
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Who cites it
101 citing papers in PubMed.
- A Randomized Control Trial of a Digital Health Tool for Safer Firearm and Medication Storage for Patients with Suicide Risk.Prevention science : the official journal of the Society for Prevention Research · 2024Trial
- The meaning of being suicidal - a reflective lifeworld research.International journal of qualitative studies on health and well-being · 2026Article
- Testing the integrated motivational-volitional model of suicidal behaviour among Danish adolescents in clinical psychiatric care: focus on volitional moderators.BJPsych open · 2026Article
- Neurocognitive and Temperament Predictors of Changes in Child and Adolescent Suicidal Thoughts and Behaviors for Youths With and Without Attention-Deficit/Hyperactivity Disorder.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- Judgments of predictability, preventability and causation of mental health homicides in England 2010 - 2023.Medicine, science, and the law · 2026Article
- Risk of unnatural death following self-harm in South Africa: development and validation of multivariable prognostic models.BMJ mental health · 2026Article
- Longitudinal changes in amygdala-supplementary motor area connectivity and their association with recurrent self-harm in adolescents with mood disorders.BMC psychiatry · 2026Article
- Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention.The annals of applied statistics · 2026Article
- Predicting suicide attempts in a high-risk clinical cohort of adolescents using machine-learning.European child & adolescent psychiatry · 2026Article
- Clinical and Genetic Evaluation of Suicide Death with and without Interpersonal Trauma Exposure.medRxiv : the preprint server for health sciences · 2026Article
- Predicting concurrent and short-term desire and intent to attempt suicide among people with body dysmorphic disorder using ecological momentary assessment of anxiety and shame.Journal of psychopathology and clinical science · 2026Article
- Enhancing personalized suicide risk prediction for VA patients by integrating discrete natural language processing models.Translational psychiatry · 2026Article
- Predicting and differentiating opioid and non-opioid drug poisonings using health records data.Journal of substance use and addiction treatment · 2026Article
- Predicting and Preventing Suicide at Entry to Mental Health Care: A Community-Engaged, Machine Learning Model Implementation.NEJM catalyst innovations in care delivery · 2026Article
- Indirect, machine learning-based suicide risk screening: Evidence from cross-National Validation.European psychiatry : the journal of the Association of European Psychiatrists · 2026Article
- Development and validation of the suicide risk score: a novel suicide risk prediction tool for patients with end-stage kidney disease.Clinical kidney journal · 2026Article
- Article
- Developing a Natural Language Processing Strategy to Avoid Biased Data in Electronic Health Record Suicide Risk Modeling.Psychiatric research and clinical practice · 2026Article
- Analysis of Multi-Domain Factors Influencing Mental Health and Suicide: A Comparative Study of Urban and Rural Areas at City, County, and District Levels in Korea.Journal of Korean medical science · 2025Article
- Predicting imminent suicide risk in a crisis hotline chat using machine learning.Scientific reports · 2025Article
41 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Suicide is a leading cause of death. A substantial proportion of the people who die by suicide come into contact with the health care system in the year before their death. This observation has resulted in the development of numerous suicide prediction tools to help target patients for preventive interventions. However, low sensitivity and low positive predictive value have led critics to argue that these tools have no clinical value. We review these tools and critiques here. We conclude that existing tools are suboptimal and that improvements, if they can be made, will require developers to work with more comprehensive predictor sets, staged screening designs, and advanced statistical analysis methods. We also conclude that although existing suicide prediction tools currently have little clinical value, and in some cases might do more harm than good, an even-handed assessment of the potential value of refined tools of this sort cannot currently be made because such an assessment would depend on evidence that currently does not exist about the effectiveness of preventive interventions. We argue that the only way to resolve this uncertainty is to link future efforts to develop or evaluate suicide prediction tools with concrete questions about specific clinical decisions aimed at reducing suicides and to evaluate the clinical value of these tools in terms of net benefit rather than sensitivity or positive predictive value. We also argue for a focus on the development of individualized treatment rules to help select the right suicide-focused treatments for the right patients at the right times. Challenges will exist in doing this because of the rarity of suicide even among patients considered high-risk, but we offer practical suggestions for how these challenges can be addressed.
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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.