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For whom does prison-based drug treatment work? Results from a randomized experiment

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Abstract

Objectives

Prison-based therapeutic community (TC) drug treatment followed by community aftercare is widely recognized as the most effective treatment paradigm for drug-dependent offenders. However, few randomized experiments have addressed this question and fewer studies have examined how interactions between treatment modality and individual characteristics may explain variations in outcomes.

Methods

Using a randomized experimental design, this study examined the effects of treatment modality [TC vs. Outpatient (OP) group counseling], individual psychosocial characteristics (e.g., risk, negative affect), and interactions on reincarceration over a 3-year follow-up period. Survival analysis using Cox regression with covariates was used to analyze data obtained from 604 subjects at a specialized drug treatment prison.

Results

The expected advantage of TC failed to emerge. Critical and heretofore unexamined interactions between treatment modality (TC vs. OP), inmate levels of risk, and negative effect help explain these unexpected findings.

Conclusion

The superiority of prison TC to less intensive OP counseling was not supported. The effects of TC appear to be conditioned by critical responsivity factors that have received little empirical attention.

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Notes

  1. Institutional custody levels range from community (1) to disciplinary custody (5).

  2. The six items included on the RST from the LSI-R are: (1) age at first arrest, (2) prior adult convictions, (3) sanctioned for institutional behavior, (4) violated a period of probation/parole supervision, (5) less than 12th grade education, and (6) drug problem ever.

  3. The area under the receiver operating characteristic (ROC) curve (AUC) is a widely used statistic for assessing the discriminatory capacity of predictive models. It is created by plotting the fraction of true positives out of all predicted positives (TPR = true positive rate, or sensitivity) against the fraction of false positives out of all predicted positives (FPR = false positive rate, or 1 – specificity, the true negative rate).

  4. Temperament refers to relatively stable ways of perceiving, thinking about, and behaving toward the environment and oneself. It is not the purpose of the REST to measure psychological traits nor was it the purpose of our study to do so. Instead, we wished to examine responses to treatment as measured by the REST. Our interpretation of our five-factor PCA solution, however, is consistent with current psychological theory and research (i.e., 3-factor theory of personality) and with the cognitive behavioral approach that underlies the RNR approach.

  5. The beta coefficients for the treatment effect (Program Type) tend to increase in Models 2 and 3, suggesting a suppressor effect (Cohen et al. 2003; Conger 1974; Smith et al. 1992): Treatment Completion acts as a suppressor for Program Type. For each, the beta weights in Model 2 and Model 3 far exceed their respective zero-order correlations (−.054 and .064) with the DV (Tabachnick and Fidell 2013:156). A suppressor variable suppresses variance that is irrelevant to the prediction of the DV, and is defined not by its own regression weight but by its enhancement of the effects of other variables in the set of IVs. Had a significant treatment effect been found in Model 4, the best fitting model and the one that we interpreted, we might have been concerned that the treatment was correlated with covariates and/or the randomization procedure had been compromised. In Model 4, however, we failed to reject the null hypothesis that the two treatment groups were equal. This finding, therefore, could not have benefited from chance correlations. As noted in the “Methods”, randomization procedures were carefully developed, pilot-tested, monitored, and reviewed throughout the study to ensure integrity.

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Acknowledgments

The research reported here was supported by Grant #2002-RTBX-1002 from the U.S. Department of Justice, National Institute of Justice (NIJ). Opinions expressed here are those of the authors and not necessarily of the U.S. Department of Justice. Any errors or omissions are the responsibility of the authors alone.

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  1. Department of Criminal Justice, Temple University, 5th Floor, Gladfelter Hall (025-02) 1115 Polett Walk, Philadelphia, PA, 19122, USA

    Wayne N. Welsh

  2. Justice Center for Research, Pennsylvania State University, University Park, PA, USA

    Gary Zajac

  3. Pennsylvania Department of Corrections, Office of Planning, Research & Statistics, Camp Hill, PA, USA

    Kristofer Bret Bucklen

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Correspondence to Wayne N. Welsh.

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Welsh, W.N., Zajac, G. & Bucklen, K.B. For whom does prison-based drug treatment work? Results from a randomized experiment. J Exp Criminol 10, 151–177 (2014). https://doi.org/10.1007/s11292-013-9194-z

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