An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentary

dc.contributor.authorFazel, Seena
dc.contributor.authorHurton, Connie
dc.contributor.authorBurghart, Matthias
dc.contributor.authorDeLisi, Matt
dc.contributor.authorYu, Rongqin
dc.date.accessioned2024-06-28T08:30:49Z
dc.date.available2024-06-28T08:30:49Z
dc.date.issued2024-05
dc.description.abstractPurpose: To conduct an umbrella review of Risk-Need-Responsivity (RNR) principles by synthesizing and appraising the consistency and quality of the underlying evidence base of RNR. Methods: Following PRISMA guidelines, we searched three bibliographic databases, the Cochrane Library, and grey literature from 2002 to 2022 for systematic reviews and meta-analysis on RNR principles. We summarized effect sizes, including as odds ratios and Area Under the Curve (AUC) statistic. We evaluated the quality of review evidence by examining risk of bias, excess statistical significance, between-study heterogeneity, and calculated prediction intervals for reported effect sizes. Results: We identified 26 unique meta-anlayses that examined RNR principles. These meta-analyses indicate inconsistent statistical support for the individual components of RNR. For the risk principle, there were links with recidivism (OR = 1.6, 95% CI [1.1, 2.3]). For the need principle, although there were associations between adherence to intervention programs and recidivism, risk assessment tools reflecting this principle had low predictive accuracy (AUCs 0.62–0.64). The general and specific responsivity principles received some support. However, the overall quality of the evidence was poor as indicated by potential authorship bias, lack of transparency, substandard primary research, limited subgroup analyses, and conflation of prediction with causality. Conclusion: The prevalent poor quality evidence and identified biases suggests that higher quality research is needed to determine whether current RNR claims of being evidence-based are justified.
dc.description.versionpublisheddeu
dc.identifier.doi10.1016/j.jcrimjus.2024.102197
dc.identifier.ppn1892428172
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/70275
dc.language.isoeng
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectCrime
dc.subjectOffending
dc.subjectRecidivism
dc.subjectRisk assessment
dc.subjectRNR
dc.subject.ddc150
dc.titleAn updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentaryeng
dc.typeJOURNAL_ARTICLE
dspace.entity.typePublication
kops.citation.bibtex
@article{Fazel2024-05updat-70275,
  year={2024},
  doi={10.1016/j.jcrimjus.2024.102197},
  title={An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentary},
  volume={92},
  issn={0047-2352},
  journal={Journal of Criminal Justice},
  author={Fazel, Seena and Hurton, Connie and Burghart, Matthias and DeLisi, Matt and Yu, Rongqin},
  note={Article Number: 102197}
}
kops.citation.iso690FAZEL, Seena, Connie HURTON, Matthias BURGHART, Matt DELISI, Rongqin YU, 2024. An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentary. In: Journal of Criminal Justice. Elsevier. 2024, 92, 102197. ISSN 0047-2352. Verfügbar unter: doi: 10.1016/j.jcrimjus.2024.102197deu
kops.citation.iso690FAZEL, Seena, Connie HURTON, Matthias BURGHART, Matt DELISI, Rongqin YU, 2024. An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentary. In: Journal of Criminal Justice. Elsevier. 2024, 92, 102197. ISSN 0047-2352. Available under: doi: 10.1016/j.jcrimjus.2024.102197eng
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Results: We identified 26 unique meta-anlayses that examined RNR principles. These meta-analyses indicate inconsistent statistical support for the individual components of RNR. For the risk principle, there were links with recidivism (OR = 1.6, 95% CI [1.1, 2.3]). For the need principle, although there were associations between adherence to intervention programs and recidivism, risk assessment tools reflecting this principle had low predictive accuracy (AUCs 0.62–0.64). The general and specific responsivity principles received some support.
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kops.sourcefield.plainJournal of Criminal Justice. Elsevier. 2024, 92, 102197. ISSN 0047-2352. Available under: doi: 10.1016/j.jcrimjus.2024.102197eng
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