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Identifying Causal Risk Factors for Violence among Discharged Patients

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...

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Autores principales: Coid, Jeremy W., Kallis, Constantinos, Doyle, Mike, Shaw, Jenny, Ullrich, Simone
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640710/
https://www.ncbi.nlm.nih.gov/pubmed/26554711
http://dx.doi.org/10.1371/journal.pone.0142493
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author Coid, Jeremy W.
Kallis, Constantinos
Doyle, Mike
Shaw, Jenny
Ullrich, Simone
author_facet Coid, Jeremy W.
Kallis, Constantinos
Doyle, Mike
Shaw, Jenny
Ullrich, Simone
author_sort Coid, Jeremy W.
collection PubMed
description 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-20(v3)) 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-20(v3) and SAPROF items were poor predictors of violence. Eight items of the HCR-20(v3) 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.
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spelling pubmed-46407102015-11-13 Identifying Causal Risk Factors for Violence among Discharged Patients Coid, Jeremy W. Kallis, Constantinos Doyle, Mike Shaw, Jenny Ullrich, Simone PLoS One Research Article 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-20(v3)) 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-20(v3) and SAPROF items were poor predictors of violence. Eight items of the HCR-20(v3) 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. Public Library of Science 2015-11-10 /pmc/articles/PMC4640710/ /pubmed/26554711 http://dx.doi.org/10.1371/journal.pone.0142493 Text en © 2015 Coid et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Coid, Jeremy W.
Kallis, Constantinos
Doyle, Mike
Shaw, Jenny
Ullrich, Simone
Identifying Causal Risk Factors for Violence among Discharged Patients
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640710/
https://www.ncbi.nlm.nih.gov/pubmed/26554711
http://dx.doi.org/10.1371/journal.pone.0142493
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