Seeing the forest and the trees: Examining the impact of aggregate measures of recidivism on meta-analytic conclusions of intervention effects

Recidivism is a multidimensional construct that is operationalized in a variety of ways. We explored the impact of using aggregated measures of recidivism (i.e. multiple measures combined) versus disaggregated measures (i.e. defined specifically as parole violation, arrest, conviction, incarceration...

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Detalles Bibliográficos
Autor principal: Bouchard, Jessica (Autor)
Otros Autores: Wong, Jennifer S.
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2024
En: Criminology & criminal justice
Año: 2024, Volumen: 24, Número: 1, Páginas: 226-248
Acceso en línea: Volltext (kostenfrei)
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Palabras clave:
Recidivism
Meta-analysis
correctional intervention
conceptual similarity
Aggregate measures
Descripción
Sumario:Recidivism is a multidimensional construct that is operationalized in a variety of ways. We explored the impact of using aggregated measures of recidivism (i.e. multiple measures combined) versus disaggregated measures (i.e. defined specifically as parole violation, arrest, conviction, incarceration) in meta-analytic analyses of correctional intervention effectiveness. Using a sample of 20 meta-analyses, we compared within-study findings between aggregated and disaggregated measures. Over half (60%) of the studies differed with respect to the statistical significance of their aggregated versus disaggregated findings, suggesting that aggregated measures of recidivism may give an incomplete picture of treatment effectiveness. Disaggregating measures of recidivism in meta-analysis is recommended for a comprehensive assessment of the impacts of intervention approaches. Policy implications are discussed.
ISSN:1748-8966
DOI:10.1177/17488958221090577