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Juvenile drug court effects on recidivism and drug use: a systematic review and meta-analysis

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Abstract

Objectives

To conduct a meta-analysis of the effects of juvenile drug courts on general recidivism, drug recidivism, and drug use, and to explore variability in effects across characteristics of the drug courts and juvenile participants.

Methods

We conducted a comprehensive literature search to identify randomized and controlled quasi-experimental studies that reported the effects of juvenile drug courts in the United States. Random-effects meta-analysis models were used to estimate mean odds ratio effect sizes, and meta-regression models were used to explore variability in effects.

Results

The literature search yielded 46 eligible evaluation studies. The meta-analysis found that, overall, juvenile drug courts were no more or less effective than traditional court processing, with mean effects sizes that were not statistically significant for general recidivism, drug recidivism, or drug use. There was statistically significant heterogeneity in those effect sizes, but none of the drug court or participant characteristics coded from the study reports were associated with that variability. However, the juvenile drug court evaluations were generally of poor methodological quality, with very few studies employing random assignment and many instances of substantial baseline differences between drug court and comparison groups.

Conclusions

Juvenile drug courts were not found to be categorically more or less effective than traditional court processing for reducing recidivism or drug use. The great variability in effects, nonetheless, suggests that there may be effective drug courts, but no distinctive characteristics of the more effective courts could be identified from the descriptive information provided in the generally low quality research studies currently available.

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Notes

  1. ESM 2 presents results from meta-analyses estimated separately for specific post-program follow-up periods: 0–5.9 months, 6–11.9 months, 12–17.9 months, 18–23.9 months, and 24–35.9 months. To examine whether recidivism effects varied over follow-up periods, we estimated meta-regression models with robust variance estimates, including all effect sizes at all follow-up points, split by recidivism type. The results from these models provided no evidence that recidivism effects varied across follow-up periods (general recidivism b = 0.01, 95 % CI [−0.02, 0.03]; drug recidivism b = −0.01, 95 % CI [−0.10, 0.08]). We, therefore, elected to present the main findings using the general during-program and post-program periods, given that there was no evidence that effects varied significantly across shorter or longer post-program follow-up periods.

  2. See ESM 2 for results split by different post-program follow-up periods

  3. These three statistics are used to index the heterogeneity in the effect size distribution. The τ 2 statistic, or “between-studies variance component”, provides an estimate of the variance of the effect size distribution around the mean effect size. The I 2 statistic indicates the proportion of observed variability attributable to true heterogeneity, rather than chance. The Q statistic tests the null hypothesis that the effects are homogeneous and all observed variability is due to chance.

  4. b = unstandardized meta-regression coefficient; β = standardized meta-regression coefficient equivalent to the bivariate correlations shown in Tables 3 and 4.

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Acknowledgments

This work was supported by Subcontract Number 0373700101 from the American Institutes for Research under the Prime Contract Number 2014-DC-BX-K001 from the U.S. Department of Justice. The content is solely the responsibility of the authors and does not necessarily represent the official views of the American Institutes for Research or the U.S. Department of Justice.

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Correspondence to Emily E. Tanner-Smith.

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Tanner-Smith, E.E., Lipsey, M.W. & Wilson, D.B. Juvenile drug court effects on recidivism and drug use: a systematic review and meta-analysis. J Exp Criminol 12, 477–513 (2016). https://doi.org/10.1007/s11292-016-9274-y

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