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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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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. |
format | Online Article Text |
id | pubmed-4640710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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