Identifying Causal Risk Factors for Violence among Discharged Patients.

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 predictiv...

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Main Authors: Jeremy W Coid, Constantinos Kallis, Mike Doyle, Jenny Shaw, Simone Ullrich
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4640710?pdf=render
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author Jeremy W Coid
Constantinos Kallis
Mike Doyle
Jenny Shaw
Simone Ullrich
author_facet Jeremy W Coid
Constantinos Kallis
Mike Doyle
Jenny Shaw
Simone Ullrich
author_sort Jeremy W Coid
collection DOAJ
description 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.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.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.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.
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spelling doaj.art-dbe6bee788b341cbb65c9f454f1245ff2022-12-21T17:45:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011011e014249310.1371/journal.pone.0142493Identifying Causal Risk Factors for Violence among Discharged Patients.Jeremy W CoidConstantinos KallisMike DoyleJenny ShawSimone UllrichStructured 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.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.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.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.http://europepmc.org/articles/PMC4640710?pdf=render
spellingShingle Jeremy W Coid
Constantinos Kallis
Mike Doyle
Jenny Shaw
Simone Ullrich
Identifying Causal Risk Factors for Violence among Discharged Patients.
PLoS ONE
title Identifying Causal Risk Factors for Violence among Discharged Patients.
title_full Identifying Causal Risk Factors for Violence among Discharged Patients.
title_fullStr Identifying Causal Risk Factors for Violence among Discharged Patients.
title_full_unstemmed Identifying Causal Risk Factors for Violence among Discharged Patients.
title_short Identifying Causal Risk Factors for Violence among Discharged Patients.
title_sort identifying causal risk factors for violence among discharged patients
url http://europepmc.org/articles/PMC4640710?pdf=render
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