Evidence map›Paper›PMID 22833604›Full record

SynthesisBMJ (Clinical research ed.)2012

Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis.

Seena Fazel, Jay P Singh, Helen Doll, Martin Grann

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ (Clinical research ed.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 7 pooled it
39.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

93 citing papers in PubMed, 7 syntheses or guidelines pooled it, 521 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Use of risk assessment instruments to predict violence in forensic psychiatric hospitals: a systematic review and meta-analysis.European psychiatry : the journal of the Association of European Psychiatrists · 2018
    Pooled it
  5. Patient outcomes following discharge from secure psychiatric hospitals: systematic review and meta-analysis.The British journal of psychiatry : the journal of mental science · 2016
    Pooled it
  6. Violence risk assessment in psychiatric patients in China: A systematic review.The Australian and New Zealand journal of psychiatry · 2016
    Pooled it
  7. Pooled it
  8. Trial
  9. Article
  10. Improving risk assessment in forensic mental health: Temporal validation and clinical refinement of the FoVOx risk tool.European psychiatry : the journal of the Association of European Psychiatrists · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Article
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  16. Discriminative and predictive validity of risk assessment measures for women incarcerated for serious violent offences in Australia.Psychiatry, psychology, and law : an interdisciplinary journal of the Australian and New Zealand Association of Psychiatry, Psychology and Law · 2024
    Article
  17. Article
  18. Review
  19. Article
  20. Review

33 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 3 countries.

Seena FazelDepartment of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK. seena.fazel@psych.ox.ac.uk
Jay P Singh
Helen Doll
Martin Grann
Karolinska Institutet · SEUniversity of East Anglia · GBUniversity of South Florida · USWarneford Hospital · GB

Funding

Wellcome Trust 095806
6 · The paper itself

Abstract

objectiveTo investigate the predictive validity of tools commonly used to assess the risk of violence, sexual, and criminal behaviour.

designSystematic review and tabular meta-analysis of replication studies following PRISMA guidelines. DATA SOURCES: PsycINFO, Embase, Medline, and United States Criminal Justice Reference Service Abstracts. REVIEW

methodsWe included replication studies from 1 January 1995 to 1 January 2011 if they provided contingency data for the offending outcome that the tools were designed to predict. We calculated the diagnostic odds ratio, sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, the number needed to detain to prevent one offence, as well as a novel performance indicator-the number safely discharged. We investigated potential sources of heterogeneity using metaregression and subgroup analyses.

resultsRisk assessments were conducted on 73 samples comprising 24,847 participants from 13 countries, of whom 5879 (23.7%) offended over an average of 49.6 months. When used to predict violent offending, risk assessment tools produced low to moderate positive predictive values (median 41%, interquartile range 27-60%) and higher negative predictive values (91%, 81-95%), and a corresponding median number needed to detain of 2 (2-4) and number safely discharged of 10 (4-18). Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime.

conclusionsAlthough risk assessment tools are widely used in clinical and criminal justice settings, their predictive accuracy varies depending on how they are used. They seem to identify low risk individuals with high levels of accuracy, but their use as sole determinants of detention, sentencing, and release is not supported by the current evidence. Further research is needed to examine their contribution to treatment and management.

Indexed as

Antisocial Personality DisorderCrimeData Interpretation, StatisticalHumansMental DisordersPsychological TestsRisk AssessmentSensitivity and SpecificitySex OffensesViolence

Identifiers

PMID22833604
PMCPMC3404183
OpenAlexW2150445502

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.