Assessment of suicide risk
Suicide risk assessment refers to the process of evaluating an individual's likelihood of dying by suicide. While commonly practiced in psychiatric and emergency care settings, suicide risk assessments lack predictive accuracy and do not improve clinical outcomes.[1][2][3]
Overview
[edit]The goal of suicide risk assessment is to identify warning signs, contributing factors (e.g., mental illness, prior attempts), and protective factors (e.g., family support). However, suicide is a statistically rare event influenced by multiple interacting variables, which makes reliable prediction difficult.[4]
The concept of "imminent suicide risk" is often used to justify emergency interventions but lacks a solid empirical foundation.[5] Some psychiatrists advocate abandoning risk suicide assessment as a clinical tool due to its inaccuracy and potential harm.[6][7]
Limitations and meta-analyses
[edit]A meta-analysis by Large et al. (2016), which reviewed 37 studies involving over 500,000 psychiatric patients, found that although individuals categorized as high-risk were more likely to die by suicide (OR = 4.84), the tools used demonstrated only modest sensitivity (56%) and specificity (79%). Nearly half of suicides occurred in those not identified as high-risk, while most individuals categorized as high-risk did not die by suicide.[8]
Similarly, Carter et al. (2017) found that most suicide risk tools had a positive predictive value below 5%, meaning that the vast majority of those categorized as high-risk would not die by suicide.[9]
Practice and ethics
[edit]Despite limited accuracy, many clinicians use structured tools to classify patients as "low," "moderate," or "high" risk. Critics argue that this classification gives a false sense of precision and reflects legal defensiveness more than clinical utility.[2]
There is also frequent conflation of suicide with non-suicidal self-injury (NSSI), although the overlap between these behaviors is limited.[10] Empathic inquiry into an individual's distress, hopelessness, and reasons for living is increasingly considered more clinically valuable than risk stratification.[11]
Common tools
[edit]Commonly used instruments in suicide risk assessment include:
- Scale for Suicide Ideation (SSI)[12]
- Modified Scale for Suicide Ideation (MSSI)[13]
- Suicide Intent Scale (SIS)[14]
- Suicidal Affect Behavior Cognition Scale (SABCS)[15]
- Suicide Behaviors Questionnaire-Revised (SBQ-R)[16]
- Reasons for Living Inventory (RFL)[17]
These tools may help structure clinical conversations but none have demonstrated strong predictive validity.
Emerging research
[edit]Recent advances in suicide risk assessment are exploring the use of natural language processing and machine learning applied to electronic health records. While these approaches show promise, they remain largely exploratory and have not yet demonstrated consistent clinical utility.[18][19]
Professor Seena Fazel and colleagues have developed structured, data-driven models to assist suicide risk assessment. These include the Oxford Mental Illness and Suicide tool (OxMIS) and the Oxford Suicide after Self-harm tool (OxSATS), which combine demographic and clinical data to produce probabilistic estimates of suicide risk. These tools show promise in supporting clinical decision-making and may reduce reliance on subjective judgment, although further validation and implementation research is ongoing.[20]
Conclusion
[edit]Suicide risk assessments, as currently practised, lack sufficient predictive power to guide treatment decisions or prevent suicide reliably. Meta-analyses suggest that most individuals who die by suicide are not identified as high-risk, and many classified as high-risk do not die by suicide.
Moving away from the language of risk avoids clinician anxiety due to “high suicide risk” (95% false positive), leading to "care" aimed at reducing clinician anxiety rather than doing what is best for the patient.
References
[edit]- ^ Simon RI. "Suicide risk assessment: is clinical experience enough?" J Am Acad Psychiatry Law. 2006;34(3):276–8.
- ^ a b Bryan CJ, Rudd MD. "Advances in the assessment of suicide risk." J Clin Psychol. 2006;62(2):185–200.
- ^ Perlman CM, Neufeld E, et al. Suicide Risk Assessment Inventory: A Resource Guide. Ontario Hospital Association, 2011.
- ^ Bongar B. The Suicidal Patient: Clinical and Legal Standards of Care. American Psychological Association, 1991.
- ^ Simon RI. "Imminent suicide: the illusion of short-term prediction." Suicide Life Threat Behav. 2006;36(3):296–301.
- ^ Murray D. "Is it time to abandon suicide risk assessment?" BJPsych Open. 2016;2(1):e1–e2.
- ^ Murray D. "Suicide Risk Assessment Doesn't Work." Scientific American, 2017.
- ^ Large M, Ryan C, Carter G, Kapur N. "Can we usefully stratify patients according to suicide risk?" PLOS ONE. 2016;11(6):e0156322.
- ^ Carter G, Milner A, McGill K, et al. "Predicting suicide using clinical instruments: systematic review and meta-analysis." BMJ Open. 2017;7(3):e014979.
- ^ Gelder MG, Mayou R, Geddes JR. Psychiatry. Oxford University Press, 2005.
- ^ Dazzi T, Gribble R, Wessely S, Fear NT. "Does asking about suicide and related behaviours induce suicidal ideation? What is the evidence?" Psychol Med. 2014;44(16):3361–3363.
- ^ Beck AT, et al. "Assessment of suicidal intention: the Scale for Suicide Ideation." J Consult Clin Psychol. 1979;47(2):343–52.
- ^ Miller IW, et al. "The Modified Scale for Suicidal Ideation." J Consult Clin Psychol. 1986;54(5):724–5.
- ^ Beck RW, et al. "Suicidal Intent Scale." Psychol Rep. 1974;34(2):445–6.
- ^ Harris KM, et al. "The ABC's of Suicide Risk Assessment: Applying a Tripartite Approach to Individual Evaluations." PLOS ONE. 2015;10(6):e0127442.
- ^ Range LM, Knott EC. "Twenty suicide assessment instruments." Death Stud. 1997;21(1):25–58.
- ^ Linehan MM, et al. "Reasons for staying alive when you're suicidal." J Consult Clin Psychol. 1983;51(2):276–86.
- ^ McCoy TH, et al. "Improving suicide risk prediction with NLP: Machine learning applied to electronic health records." JAMA Psychiatry. 2016;73(10):1064–1071.
- ^ Barak-Corren Y, et al. "Predicting suicidal behavior using EHR data." Am J Psychiatry. 2017;174(2):154–162.
- ^ Fazel S, Wolf A, Fok ML, Hayes JF, et al. "Development and validation of structured suicide risk models: OxMIS and OxSATS." The Lancet Psychiatry. 2024.