Prospective Replication of the Violence Risk Appraisal Guide in Predicting Violent Recidivism Among Forensic Patients View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-08

AUTHORS

Grant T. Harris, Marnie E. Rice, Catherine A. Cormier

ABSTRACT

An exhaustive survey of a cohort of forensic patients provided an opportunity for a prospective replication of the predictive accuracy of the Violence Risk Appraisal Guide (VRAG). Data collected during the original survey also permitted a test of the predictive accuracy of clinical assessments of risk on the same cohort. The VRAG yielded a large effect size in predicting violent recidivism (ROC area = .80) over a constant 5-year follow-up and performed significantly better than averaged clinical opinions. The superiority of the VRAG was also observed at very short follow-up times and for very serious violence. Moreover, for 16 subsamples, observed rates of violent recidivism did not differ significantly from the expected rates. VRAG score was unrelated, and clinical judgments inversely related to violent recidivism in the small low-risk sample of female forensic patients. The authors conclude that, regardless of length of opportunity or severity of outcome, actuarial methods are more accurate than is clinical judgment. More... »

PAGES

377-394

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1016347320889

DOI

http://dx.doi.org/10.1023/a:1016347320889

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1046391095

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/12182529


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N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1016347320889'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1016347320889'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1016347320889'


 

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