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Identifying Causal Risk Factors for Violence among Discharged Patients

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  • Jeremy W Coid
  • Constantinos Kallis
  • Mike Doyle
  • Jenny Shaw
  • Simone Ullrich

Abstract

Background: Structured Professional Judgement (SPJ) is routinely administered in mental health and criminal justice settings but cannot identify violence risk above moderate accuracy. There is no current evidence that violence can be prevented using SPJ. This may be explained by routine application of predictive instead of causal statistical models when standardising SPJ instruments. Methods: We carried out a prospective cohort study of 409 male and female patients discharged from medium secure services in England and Wales to the community. Measures were taken at baseline (pre-discharge), 6 and 12 months post-discharge using the Historical, Clinical and Risk-20 items version 3 (HCR-20v3) and Structural Assessment of Protective Factors (SAPROF). Information on violence was obtained via the McArthur community violence instrument and the Police National Computer. Results: In a lagged model, HCR-20v3 and SAPROF items were poor predictors of violence. Eight items of the HCR-20v3 and 4 SAPROF items did not predict violent behaviour better than chance. In re-analyses considering temporal proximity of risk/ protective factors (exposure) on violence (outcome), risk was elevated due to violent ideation (OR 6.98, 95% CI 13.85–12.65, P

Suggested Citation

  • Jeremy W Coid & Constantinos Kallis & Mike Doyle & Jenny Shaw & Simone Ullrich, 2015. "Identifying Causal Risk Factors for Violence among Discharged Patients," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-17, November.
    • Handle: RePEc:plo:pone00:0142493
    DOI: 10.1371/journal.pone.0142493
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