1. An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model: Umbrella review and commentary.
- Author
-
Fazel, Seena, Hurton, Connie, Burghart, Matthias, DeLisi, Matt, and Yu, Rongqin
- Subjects
- *
BIBLIOGRAPHIC databases , *GREY literature , *STATISTICAL significance , *UMBRELLAS , *ODDS ratio , *RISK assessment - Abstract
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. 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. 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. 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. • The underlying evidence for RNR principles is mixed and mostly of low quality. • This evidence shows authorship bias and often lacks transparency. • All reviews that tested the risk principle were rated as low quality. • Higher quality research is needed to support the claims about the RNR principles. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF