Jodi L Viljoen, Ilvy Goossens, Sanam Monjazeb, Dana M Cochrane, Lee M Vargen, Melissa R Jonnson, Adam J E Blanchard, Shanna M Y Li, Jourdan R Jackson
{"title":"在预测暴力犯罪、任何犯罪和性犯罪方面,风险评估工具比非结构化判断更准确吗?直接比较研究的荟萃分析。","authors":"Jodi L Viljoen, Ilvy Goossens, Sanam Monjazeb, Dana M Cochrane, Lee M Vargen, Melissa R Jonnson, Adam J E Blanchard, Shanna M Y Li, Jourdan R Jackson","doi":"10.1002/bsl.2698","DOIUrl":null,"url":null,"abstract":"<p><p>We conducted a pre-registered meta-analysis of studies that directly compared the predictive validity of risk assessment tools to unstructured judgments of risk for violent, any, or sexual offending. A total of 31 studies, containing 169 effect sizes from 45,673 risk judgments, met inclusion criteria. Based on the results of three-level mixed-effects meta-regression models, the predictive validity of total scores on risk assessment tools was significantly higher than that of unstructured judgments for predictions of violent, any, and sexual offending. Tools continued to outperform unstructured judgments after accounting for risk of bias. This finding was also robust to variations in population, assessment context, and outcome measurement. Although this meta-analysis provides support for the use of risk assessment tools, it also highlights limitations and gaps that future research should address.</p>","PeriodicalId":47926,"journal":{"name":"Behavioral Sciences & the Law","volume":" ","pages":"75-113"},"PeriodicalIF":1.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771637/pdf/","citationCount":"0","resultStr":"{\"title\":\"Are risk assessment tools more accurate than unstructured judgments in predicting violent, any, and sexual offending? A meta-analysis of direct comparison studies.\",\"authors\":\"Jodi L Viljoen, Ilvy Goossens, Sanam Monjazeb, Dana M Cochrane, Lee M Vargen, Melissa R Jonnson, Adam J E Blanchard, Shanna M Y Li, Jourdan R Jackson\",\"doi\":\"10.1002/bsl.2698\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We conducted a pre-registered meta-analysis of studies that directly compared the predictive validity of risk assessment tools to unstructured judgments of risk for violent, any, or sexual offending. A total of 31 studies, containing 169 effect sizes from 45,673 risk judgments, met inclusion criteria. Based on the results of three-level mixed-effects meta-regression models, the predictive validity of total scores on risk assessment tools was significantly higher than that of unstructured judgments for predictions of violent, any, and sexual offending. Tools continued to outperform unstructured judgments after accounting for risk of bias. This finding was also robust to variations in population, assessment context, and outcome measurement. Although this meta-analysis provides support for the use of risk assessment tools, it also highlights limitations and gaps that future research should address.</p>\",\"PeriodicalId\":47926,\"journal\":{\"name\":\"Behavioral Sciences & the Law\",\"volume\":\" \",\"pages\":\"75-113\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771637/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Behavioral Sciences & the Law\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1002/bsl.2698\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"LAW\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavioral Sciences & the Law","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1002/bsl.2698","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/3 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"LAW","Score":null,"Total":0}
Are risk assessment tools more accurate than unstructured judgments in predicting violent, any, and sexual offending? A meta-analysis of direct comparison studies.
We conducted a pre-registered meta-analysis of studies that directly compared the predictive validity of risk assessment tools to unstructured judgments of risk for violent, any, or sexual offending. A total of 31 studies, containing 169 effect sizes from 45,673 risk judgments, met inclusion criteria. Based on the results of three-level mixed-effects meta-regression models, the predictive validity of total scores on risk assessment tools was significantly higher than that of unstructured judgments for predictions of violent, any, and sexual offending. Tools continued to outperform unstructured judgments after accounting for risk of bias. This finding was also robust to variations in population, assessment context, and outcome measurement. Although this meta-analysis provides support for the use of risk assessment tools, it also highlights limitations and gaps that future research should address.