Publikation:

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

Lade...
Vorschaubild

Dateien

Fazel_2-1gxsgdetrjoyb2.pdf
Fazel_2-1gxsgdetrjoyb2.pdfGröße: 3.95 MBDownloads: 64

Datum

2024

Autor:innen

Fazel, Seena
Hurton, Connie
DeLisi, Matt
Yu, Rongqin

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

ArXiv-ID

Internationale Patentnummer

Link zur Lizenz

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Hybrid
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Journal of Criminal Justice. Elsevier. 2024, 92, 102197. ISSN 0047-2352. Verfügbar unter: doi: 10.1016/j.jcrimjus.2024.102197

Zusammenfassung

Purpose: 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.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
150 Psychologie

Schlagwörter

Crime, Offending, Recidivism, Risk assessment, RNR

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690FAZEL, 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.2024.102197
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}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/70275">
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Yu, Rongqin</dc:creator>
    <dc:contributor>DeLisi, Matt</dc:contributor>
    <dcterms:issued>2024-05</dcterms:issued>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-06-28T08:30:49Z</dc:date>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/70275/1/Fazel_2-1gxsgdetrjoyb2.pdf"/>
    <dcterms:abstract>Purpose: 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.</dcterms:abstract>
    <dc:contributor>Yu, Rongqin</dc:contributor>
    <dc:contributor>Hurton, Connie</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/70275/1/Fazel_2-1gxsgdetrjoyb2.pdf"/>
    <dc:creator>DeLisi, Matt</dc:creator>
    <dc:contributor>Burghart, Matthias</dc:contributor>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/70275"/>
    <dc:creator>Burghart, Matthias</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-06-28T08:30:49Z</dcterms:available>
    <dcterms:title>An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model : Umbrella review and commentary</dcterms:title>
    <dc:creator>Fazel, Seena</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Hurton, Connie</dc:creator>
    <dc:rights>Attribution 4.0 International</dc:rights>
    <dc:language>eng</dc:language>
    <dc:contributor>Fazel, Seena</dc:contributor>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Ja
Diese Publikation teilen