Accuracy of Clinician Predictions of Future Self‐Harm: A Systematic Review and Meta‐Analysis of Predictive Studies
Open accessAbstract
Assessment of a patient after hospital‐treated self‐harm or psychiatric hospitalization often includes a risk assessment, resulting in a classification of high risk versus low risk for a future episode of self‐harm. Through systematic review and a series of meta‐analyses looking at unassisted clinician risk classification (eight studies; N = 22,499), we found pooled estimates for sensitivity 0.31 (95% CI : 0.18–0.50), specificity 0.85 (0.75–0.92), positive predictive value 0.22 (0.21–0.23), and negative predictive value 0.89 (0.86–0.92). Clinician classification was too inaccurate to be clinically useful. After‐care should therefore be allocated on the basis of a needs rather than risk assessment.
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Recent meta-analyses demonstrate that neither individual risk factors, composite risk scores, clinical judgment, nor adherence to theoretical models or artificial intelligence enables sufficiently accurate prediction of suicidal behavior.
“Recent meta-analyses demonstrate that neither individual risk factors, composite risk scores, clinical judgment, nor adherence to theoretical models or artificial intelligence enables sufficiently accurate prediction of suicidal behavior.”
From Suicide risk assessment: clinical implications of the unpredictability of suicidal behavior (2026) · cites this paper as [18]
The background discussion (p. 3) reports that individual risk factors and instruments or scales classify later suicide risk only modestly better than chance. The Conclusions (p. 15) find clinician predictions of repeated self-harm insufficiently accurate for clinical decisions. The paper does not assess adherence to theoretical models or artificial intelligence, so it does not support those parts of the sentence. (LLM, conf=0.87)
Experimental — accuracy not yet measuredIn Woodford et al.'s meta-analysis, 70% of those who engaged in self-injurious behavior after inpatient treatment had previously been assessed by their practitioners as not being at risk.
“It was found that 70% of those who engaged in self-injurious behavior after treatment had previously been assessed by their practitioners as not being at risk”
From Suicide risk assessment: clinical implications of the unpredictability of suicidal behavior (2026) · cites this paper as [18]
The Discussion (p. 10) says nearly 70% of people who later self-harmed were classified by clinicians as low risk. But the pooled estimate covers assessments after hospital-treated self-harm or psychiatric hospitalisation (Australia Abstract, p. 2); it is not a finding specific to people who received inpatient treatment. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe considerable dynamics of suicidal ideation and behaviour make it incredibly difficult to reliably assess a person's suicide risk.
“The considerable dynamics of suicidal ideation and behaviour - in addition to other factors (6) - make it incredibly difficult to reliably assess a person’s suicide risk (7, 8).”
From Ambivalence model of suicidality [ABS-model]: an orientation model for the treatment of suicidal individuals (2024) · cites this paper as [8]
The Discussion (p. 10) finds that clinician risk classifications miss nearly 70% of future self-harm cases, supporting the difficulty of reliable individual risk assessment. But the Discussion (p. 13) attributes poor prediction to the low prevalence of suicide and self-harm; it does not identify the dynamics of suicidal ideation and behaviour as the reason. (LLM, conf=0.88)
Experimental — accuracy not yet measuredIn Woodford et al.'s meta-analysis, around 80% of those who were assessed as being at high risk did not engage in self-injurious behavior.
“and that around 80% of those who were assessed as being at high risk did not engage in self-injurious behavior.”
From Suicide risk assessment: clinical implications of the unpredictability of suicidal behavior (2026) · cites this paper as [18]
In Woodford et al.'s meta-analysis, the predictions made by practitioners were only slightly better than chance.
“Taken together, the predictions made by practitioners in this meta-analysis were only slightly better than chance.”
From Suicide risk assessment: clinical implications of the unpredictability of suicidal behavior (2026) · cites this paper as [18]
Recent meta-analyses show that the prediction accuracy of suicide is alarmingly poor.
“recent meta-analyses show that the prediction accuracy of suicide is alarmingly poor (Franklin et al., 2017;Ribeiro et al., 2019;Woodford et al., 2019).”
From Suicide Crisis Syndrome: A systematic review (2024) · cites this paper as Woodford et al., 2019
A recent individual participant network meta-analysis was able to distinguish potentially helpful, less helpful, or potentially harmful iCBT components, and showed a decrease in dropout rates when human encouragement to proceed with iCBT was combined with automated encouragement.
“A recent individual participant network meta-analysis was able to distinguish potentially helpful (e.g., behavioural activation), less helpful, or potentially harmful (e.g., relaxation) iCBT components. The study also showed a decrease in dropout rates when human encouragement to proceed with iCBT was combined with automated encouragement. 629”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [629]
Clinical evaluations are not more accurate than structured assessments in predicting subsequent suicides and SRBs.
“But are clinical evaluations any more accurate than structured assessments in predicting subsequent suicides and SRBs? The evidence suggests not.”
From Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System (2020) · cites this paper as [109]
A more recent meta-analysis of seven studies found that clinical assessments were only weakly associated with subsequent suicides among patients after hospital treatment of SRBs.
“A more recent meta-analysis of seven studies found that clinical assessments were only weakly associated with subsequent suicides among patients after hospital treatment of SRBs (109).”
From Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System (2020) · cites this paper as [109]
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“In another meta-analysis, Woodford and colleagues (18) investigated the extent to which clinicians can predict which of their patients will engage in self-injurious behavior after being discharged from inpatient treat-ment.”
- Authors
- Woodford, R., Spittal, M. J., Milner, A., McGill, K., Kapur, N., Pirkis, J., Mitchell, A., & Carter, G.
- Affiliations
- University of Newcastle Australia (AU)
- The University of Melbourne (AU)
- University of Manchester (GB)
- University of Leicester (GB)
- Corresponding author
- Carter, Gregory
- ORCID
- Venue
- Suicide and Life-Threatening Behavior
- Publisher
- Wiley
- Published
- 2017-10-03
- Volume
- 49
- Issue
- 1
- Pages
- 23-40
- ISSN
- 0363-0234 (ISSN-L)
- 1943-278X
- OpenAlex
- W2762347168
- Cited by
- 92
- References
- 37
- Citations by year
- 2026: 11 · 2025: 16 · 2024: 14 · 2023: 11 · 2022: 10 · 2021: 12 · 2020: 8 · 2019: 8 · 2018: 2
- FWCI
- 0.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Suicide and Life-Threatening Behavior (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- Minerva Access (University of Melbourne) (submittedVersion)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- Hunter New England Local Health District
- Topics
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
- Social Sciences › Psychology › Clinical Psychology › Psychiatric care and mental health services
- Keywords
- self-harm, risk assessment, sensitivity and specificity, psychiatric hospitalization
- MeSH terms
- Aftercare, Mental Disorders, Humans, Predictive Value of Tests, Prognosis, Psychological Techniques, Sensitivity and Specificity, Self-Injurious Behavior, Risk Assessment
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