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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Bibliographic Details
Main Author: Bouchard, Jessica (Author)
Contributors: Wong, Jennifer S.
Format: Electronic Article
Language:English
Published: 2024
In: Criminology & criminal justice
Year: 2024, Volume: 24, Issue: 1, Pages: 226-248
Online Access: Volltext (kostenfrei)
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Keywords:
Recidivism
Meta-analysis
correctional intervention
conceptual similarity
Aggregate measures
Description
Summary: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