title: Identifying Causal Risk Factors for Violence among Discharged Patients.
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<0.001), instability (OR 5.41, 95% CI 3.44-8.50, P<0.001), and poor coping/ stress (OR 8.35, 95% CI 4.21-16.57, P<0.001). All 3 risk factors were explanatory variables which drove the association with violent outcome. Self-control (OR 0.13, 95% CI 0.08-0.24, P<0.001) conveyed protective effects and explained the association of other protective factors with violence.
  
  
  CONCLUSIONS
  Using two standardised SPJ instruments, predictive (lagged) methods could not identify risk and protective factors which must be targeted in interventions for discharged patients with severe mental illness. Predictive methods should be abandoned if the aim is to progress from risk assessment to effective risk management and replaced by methods which identify factors causally associated with violence.
authors.affiliation: Violence Prevention Research Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London. Garrod Building, Turner Street, London E1 2AD, United Kingdom.
authors.forename: Jeremy W
authors.initials: JW
authors.lastname: Coid
authors.affiliation: Violence Prevention Research Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London. Garrod Building, Turner Street, London E1 2AD, United Kingdom.
authors.forename: Constantinos
authors.initials: C
authors.lastname: Kallis
authors.affiliation: Institute of Brain, Behaviour and Mental Health, University of Manchester. Oxford Road, Manchester M13 9PL, United Kingdom.
authors.forename: Mike
authors.initials: M
authors.lastname: Doyle
authors.affiliation: Institute of Brain, Behaviour and Mental Health, University of Manchester. Oxford Road, Manchester M13 9PL, United Kingdom.
authors.forename: Jenny
authors.initials: J
authors.lastname: Shaw
authors.affiliation: Violence Prevention Research Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London. Garrod Building, Turner Street, London E1 2AD, United Kingdom.
authors.forename: Simone
authors.initials: S
authors.lastname: Ullrich
mesh_terms: D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D010351:Patient Discharge; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D014754:Violence