@article{ref1,
title="The HCR-20 for predicting violence in adult females: a meta-analysis",
journal="Journal of forensic psychology research and practice",
year="2020",
author="Rossdale, Sapphire-Violet and Tully, Ruth J. and Egan, Vincent",
volume="20",
number="1",
pages="15-52",
abstract="This meta-analysis aimed to examine the effectiveness of the Historical Clinical Risk-20 violence management tool for predicting violence in adult female populations. The HCR-20 is a well-known tool which has been predominantly developed and validated on males. To date, there have been no published systematic reviews explicitly explore all generations of the HCR-20 and the predictive validity of the tool for females which encompasses measures of violence, recidivism and settings. Nine electronic databases and reference lists of relevant analyzes were searched. All papers were reviewed with pre-defined inclusion criteria, and quality assessment. Relevant papers were then subject to data extraction and synthesis. The electronic search revealed 1405 papers. After the exclusion process and quality assessment, 12 studies were included in the review. A meta-analysis was conducted using a total of 45 effect sizes assessing the predictive validity of the H, C, R, and Total items for violence and recidivism, followed by a sensitivity analysis. <br><br>RESULTS suggested a small effect size for H, C, and R items when assessing violence and for C, R, and total items for predicating recidivism in females. However, moderate effect sizes were found for total items when predicting violence and for H items for predicting recidivism. This review concludes that the HCR-20 assessment can be considered as a useful tool for understanding and assessing violence risk with females; however, further research is required to develop a more informed view of the HCR-20 assessment with females and should focus on the HCR-20 version three as the updated tool.<p /> <p>Language: en</p>",
language="en",
issn="2473-2850",
doi="10.1080/24732850.2019.1681875",
url="http://dx.doi.org/10.1080/24732850.2019.1681875"
}