Assessment of suicide risk

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Suicide risk assessment is 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] and it has even been suggested that clinicians doing suicide risk assessments may be putting their "own professional anxieties above the needs of service users and paradoxically, increasing the risks of suicide following self-harm." [3]

Contents

Overview

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] [5]

The concept of "imminent suicide risk" is often used to justify emergency interventions but lacks a solid empirical foundation. [6] Some psychiatrists advocate abandoning risk suicide assessment as a clinical tool due to its inaccuracy and potential harm. [7] [8]

Suicide risk assessments, as currently practised, lack sufficient predictive power to guide treatment decisions or prevent suicide reliably. Data 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. [9] [10] [11]

Limitations and meta-analyses

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. [12]

A meta-analysis by Joseph C. Franklin (2017) covering 365 longitudinal studies finds that 50 years of research have yielded only slight predictive power for suicidal ideation, attempts, and deaths; no risk factor category clearly outperforms, and accuracy has not improved over time. [13]

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. [14]

Practice and ethics

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] Undrill (2007) calls this "secondary risk" [15] : the risk to organizations or clinicians that arises from managing risk itself. Assessing a patient's primary risk for suicide can expose institutions to liability for possible errors, which is why secondary risk management can impair the quality of primary risk assessment. Baston (2024) argues that suicide risk assessment is necessary as long as medical resources are limited, so that those at high risk have priority over those at low risk. To circumvent the prediction problem, Baston refers to non-traditional conceptions of objective risk [16] [17] that do not rely on probability calculations but on a possible-worlds framework, taking into account a patient's reasons for living and dying rather than risk factors with low predictive power. [18]

There is also frequent conflation of suicide with non-suicidal self-injury (NSSI), although the overlap between these behaviors is limited. [19] Empathic inquiry into an individual's distress, hopelessness, and reasons for living is increasingly considered more clinically valuable than risk stratification. [20]

Common tools

Commonly used instruments in suicide risk assessment include:

These tools may help structure clinical conversations but none have demonstrated strong predictive validity.

Emerging research

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. [27] [28]

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. [29] [3]

See also

References

  1. ↑ Simon RI. "Suicide risk assessment: is clinical experience enough?" J Am Acad Psychiatry Law. 2006;34(3):276–8.
  2. 1 2 Bryan CJ, Rudd MD. "Advances in the assessment of suicide risk." J Clin Psychol. 2006;62(2):185–200.
  3. 1 2 3 Chan MKY, Bhatti H, Meader N, et al. Predicting suicide following self-harm: systematic review of risk factors and risk scales. British Journal of Psychiatry. 2016;209(4):277-283. doi:10.1192/bjp.bp.115.170050
  4. ↑ Bongar B. The Suicidal Patient: Clinical and Legal Standards of Care. American Psychological Association, 1991.
  5. ↑ Bryan, Craig J. (2022). Rethinking suicide: why prevention fails, and how we can do better. New York: Oxford University Press. ISBN   978-0-19-005063-4.
  6. ↑ Simon RI. "Imminent suicide: the illusion of short-term prediction." Suicide Life Threat Behav. 2006;36(3):296–301.
  7. ↑ Murray D. "Is it time to abandon suicide risk assessment?" BJPsych Open. 2016;2(1):e1–e2.
  8. ↑ Murray D. "Suicide Risk Assessment Doesn't Work." Scientific American, 2017.
  9. ↑ Mulder, Roger; Newton-Howes, Giles; Coid, Jeremy W. (October 2016). "The futility of risk prediction in psychiatry". British Journal of Psychiatry. 209 (4): 271–272. doi:10.1192/bjp.bp.116.184960. ISSN   0007-1250. PMID   27698212.
  10. ↑ Bryan, Craig J. (2022). Rethinking suicide: why prevention fails, and how we can do better. New York: Oxford University Press. ISBN   978-0-19-005063-4.
  11. ↑ Large, Matthew; Kaneson, Muthusamy; Myles, Nicholas; Myles, Hannah; Gunaratne, Pramudie; Ryan, Christopher (2016-06-10). DeLuca, Vincenzo (ed.). "Meta-Analysis of Longitudinal Cohort Studies of Suicide Risk Assessment among Psychiatric Patients: Heterogeneity in Results and Lack of Improvement over Time". PLOS ONE. 11 (6) e0156322. Bibcode:2016PLoSO..1156322L. doi: 10.1371/journal.pone.0156322 . ISSN   1932-6203. PMC   4902221 . PMID   27285387.
  12. ↑ Large M, Ryan C, Carter G, Kapur N. "Can we usefully stratify patients according to suicide risk?" PLOS ONE. 2016;11(6):e0156322.
  13. ↑ Franklin, Joseph C.; Ribeiro, Jessica D.; Fox, Kathryn R.; Bentley, Kate H.; Kleiman, Evan M.; Huang, Xieyining; Musacchio, Katherine M.; Jaroszewski, Adam C.; Chang, Bernard P.; Nock, Matthew K. (2017). "Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research". Psychological Bulletin. 143 (2): 187–232. doi:10.1037/bul0000084. ISSN   1939-1455. PMID   27841450.
  14. ↑ Carter G, Milner A, McGill K, et al. "Predicting suicide using clinical instruments: systematic review and meta-analysis." BMJ Open. 2017;7(3):e014979.
  15. ↑ Undrill, Guy (July 2007). "The risks of risk assessment". Advances in Psychiatric Treatment. 13 (4): 291–297. doi:10.1192/apt.bp.106.003160. ISSN   1355-5146.
  16. ↑ Pritchard, Duncan (July 2015). "Risk". Metaphilosophy. 46 (3): 436–461. doi:10.1111/meta.12142. ISSN   0026-1068.
  17. ↑ Ebert, Philip A.; Smith, Martin; Durbach, Ian (September 2020). "Varieties of Risk". Philosophy and Phenomenological Research. 101 (2): 432–455. doi:10.1111/phpr.12598. ISSN   0031-8205.
  18. ↑ Baston, René (2024-07-10). "Beyond prediction: a new paradigm for understanding suicide risk". Synthese. 204 (1) 35. doi:10.1007/s11229-024-04689-7. ISSN   1573-0964.
  19. ↑ Gelder MG, Mayou R, Geddes JR. Psychiatry. Oxford University Press, 2005.
  20. ↑ 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.
  21. ↑ Beck AT, et al. "Assessment of suicidal intention: the Scale for Suicide Ideation." J Consult Clin Psychol. 1979;47(2):343–52.
  22. ↑ Miller IW, et al. "The Modified Scale for Suicidal Ideation." J Consult Clin Psychol. 1986;54(5):724–5.
  23. ↑ Beck RW, et al. "Suicidal Intent Scale." Psychol Rep. 1974;34(2):445–6.
  24. ↑ Harris KM, et al. "The ABC's of Suicide Risk Assessment: Applying a Tripartite Approach to Individual Evaluations." PLOS ONE. 2015;10(6):e0127442.
  25. ↑ Range LM, Knott EC. "Twenty suicide assessment instruments." Death Stud. 1997;21(1):25–58.
  26. ↑ Linehan MM, et al. "Reasons for staying alive when you're suicidal." J Consult Clin Psychol. 1983;51(2):276–86.
  27. ↑ McCoy TH, et al. "Improving suicide risk prediction with NLP: Machine learning applied to electronic health records." JAMA Psychiatry. 2016;73(10):1064–1071.
  28. ↑ Barak-Corren Y, et al. "Predicting suicidal behavior using EHR data." Am J Psychiatry. 2017;174(2):154–162.
  29. ↑ 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.
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