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The Andrews’ principles of risk, needs, and responsivity as applied in drug treatment programs: meta-analysis of crime and drug use outcomes

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Abstract

Objectives

The purpose of the present meta-analysis was to answer the question: Can the Andrews principles of risk, needs, and responsivity, originally developed for programs that treat offenders, be extended to programs that treat drug abusers?

Methods

Drawing from a dataset that included 243 independent comparisons, we conducted random-effects meta-regression and ANOVA-analog meta-analyses to test the Andrews principles by averaging crime and drug use outcomes over a diverse set of programs for drug abuse problems.

Results

For crime outcomes, in the meta-regressions, the point estimates for each of the principles were substantial, consistent with previous studies of the Andrews principles. There was also a substantial point estimate for programs exhibiting a greater number of the principles. However, almost all the 95 % confidence intervals included the zero point. For drug use outcomes, in the meta-regressions, the point estimates for each of the principles was approximately zero; however, the point estimate for programs exhibiting a greater number of the principles was somewhat positive. All the estimates for the drug use principles had confidence intervals that included the zero point.

Conclusions

This study supports previous findings from primary research studies targeting the Andrews principles that those principles are effective in reducing crime outcomes, here in meta-analytic research focused on drug treatment programs. By contrast, programs that follow the principles appear to have very little effect on drug use outcomes. Primary research studies that experimentally test the Andrews principles in drug treatment programs are recommended.

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Notes

  1. In a recent article, Andrews et al. (2011: 738) encourage the extension of the principles beyond corrections: “The theoretical and empirical base of RNR-based human service should be disseminated widely for purposes of enhanced crime prevention throughout the justice system and beyond (e.g., general mental health services).”

  2. We limited studies to those conducted the United States and Canada in part because we thought that studies from those two nations already entailed significant heterogeneity in correctional systems and drug abuse treatment approaches and in part to keep within the cost limits of the grant.

  3. The term “comparison group” is used throughout this paper rather than “control group” since it is more inclusive of the types of groups that were compared with the treatment group in the studies coded. Although some studies did have a “control group” typical of randomized control trials, others used other types of comparison groups.

  4. The codebook can be requested from the corresponding author.

  5. In the meta-regression models that included these methods covariates, the standardized regression coefficient is not equivalent to the correlation coefficient (r), as it is in the bivariate meta-regressions.

  6. Andrews’ criterion for high crime risk was whether most participants in a study had “penetrated the judicial system at the time of the study and had a prior criminal record” (Dowden and Andrews 2000: 455).

  7. A frequency table of these services can be obtained from the corresponding author.

  8. We did not identify and analyze services intended to address “drug use needs” (but see Pearson et al. 2012) To do so would have required a detailed review of the literature to identify “needs” associated with post-treatment drug use, which was beyond the scope of the study.

  9. One study in which the C group had more criminogenic-related services than the E group (resulting in a negative value) were dropped from analysis; this only applied to the analysis on drug outcomes, not to the analysis on crime outcomes.

  10. This method of coding responsivity differs from that used by Andrews. In his meta-analyses, responsivity is a dichotomous variable based on whether or not the program used with the E group used a social learning and/or cognitive-behavioral approach (see Andrews et al. 1990b; Dowden and Andrews 1999, 2000). Although our approach seems a stronger test of the Responsivity Principle, since it captures the difference in the responsivity of the two groups, a disadvantage is that studies are lost from analysis because of a differential pattern of missing data on the responsivity variable for the E condition and the C condition.

  11. In later meta-analyses, Andrews usually examined the principles separately (e.g., Andrews and Dowden 2006; Dowden and Andrews 1999).

  12. A reviewer asked whether the findings support the NIDA treatment effectiveness principle of matching: “Treatment varies depending on the type of drug and the characteristics of the patients. Matching treatment settings, interventions, and services to an individual’s particular problems and needs is critical to his or her ultimate success in returning to productive functioning in the family, workplace, and society” (NIDA 2012: 2). Although the Andrews’ principles and the NIDA principle are both concerned with the general concept of matching, the Andrews’ principles are more specific in defining the characteristics and needs of offenders on which matching should occur. The NIDA description of matching is much more general. Given these differences, using the findings from this paper to support (or not) the NIDA principle does not seem appropriate.

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Acknowledgments

This study was funded by the National Institute on Drug Abuse, grant R01 DA016600. The contents of this report are solely the responsibility of the authors and do not necessarily represent the views of the Department of Health and Human Services or the National Institute on Drug Abuse. We greatly appreciate the contributions of Aaron Brownstein, Ph.D., Anna Hyun, Ph.D., and Stephanie Kovalchik, Ph.D., the coders on the EPT project at UCLA, of Peter Vazan, Ph.D., a coder at NDRI, and of Stacy Calhoun, M.A., research associate on the UCLA team. Kory van Unen provided assistance with preparation of the paper. We are also grateful to Associate Editor David Wilson and to three anonymous reviewers for their comments and suggestions, which improved the paper.

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Correspondence to Michael L. Prendergast.

Additional information

Studies included in each of the meta-analyses are available from the corresponding author.

Appendices

Appendix 1. Search terms

The following keywords and their combinations were used in the database searches, with the actual search strategy being adapted to each database: (substance or drug) and (abus* or misus* or use* or using or disorder* or depend* or addict*); (crack or cocain* or opiat* or heroin* or methadon* or cannabis* or marijuana or pcp or barbiturate* or benzodiazepin* or amphetamin* or methamphetamin* or polydrug*); (treatment* or rehabilitat* or intervention*); and (outcome* or result* or finding*).

Appendix 2. Coding for risk

Each study was coded for crime risk and drug use risk using the following guidelines. The examples for each risk level were intended to help anchor the categories, but coders were instructed to use any relevant baseline information to assess risk.

Crime risk

  • 1 = Low risk of committing a crime (Example 1: Less than 10 % of the subjects were in prison/jail or on parole/probation. Example 2: Less than 10 % had an arrest or a self-reported criminal act. Example 3: Less than 10 % were classified as having an antisocial personality. Example 4: Mean ASI legal composite score less than .05).

  • 2 = Medium risk of committing a crime (Example 1: 10 % to 39 % of the subjects were in prison/jail or on parole/probation, Example 2: 10 % to 39 % had an arrest or a self-reported criminal act. Example 3: 10 % to 39 % were classified as having an antisocial personality. Example 4: Mean ASI legal composite score was about .05 through .09).

  • 3 = High risk of committing a crime (Example 1: 40 % or more of the subjects were in prison/jail or on parole/probation. Example 2: 40 % or more had an arrest or a self-reported criminal act. Example 3: 40 % or more were classified as having an antisocial personality. Example 4: Mean ASI legal composite score was .10 or greater).

  • −8 = No information (or insufficient information) reported.

Drug use risk

  • 1 = Low risk of drug use (Example 1: Most subjects used an illicit drug AT MOST only 3 times per month. Example 2: Less than 10 % of the subjects had previously received treatment for drug abuse. Example 3: Mean ASI drug use composite score less than 0.05. Example 4: Used less than once a year).

  • 2 = Medium risk of drug use (Example 1: Typical subjects used an illicit drug roughly 4 to 9 times per month. Example 2: Roughly 10 % to 49 % of the subjects had previously received treatment for drug abuse. Example 3: Mean ASI drug use composite score was about .05 through .09. Example 4: Used drug for 2 or 3 years).

  • 3 = High risk of drug use (Example 1: Typical subjects used an illicit drug roughly 10 or more times per month. Example 2: Roughly 50 % to 100 % of the subjects had previously received treatment for drug abuse. Example 3: Mean ASI drug use composite score was .10 or greater. Example 4: Used drugs four or more years. Example 5: Has had a DSM diagnosis of drug abuse or dependence).

  • −8 = No information (or insufficient information) reported.

Appendix 3. Services coded as addressing criminogenic needs

Specific techniques to engage clients in treatment or motivate them for treatment

Specific “retention” techniques to keep clients in treatment

Clinically supervised sessions of positive peer/support groups

Techniques to change behavior by means of operant/reinforcement conditioning (even aversive conditioning), contingency management, contracting, and token economy programs

Techniques to change habits of thought and internal control, including self-reinforcement, cognitive skills, eliminating thinking errors, problem solving, self-instruction, self-rehearsal

Training in specific relapse prevention skills

Training to remedy deficits in education

Training to remedy deficits in vocational or employment skills

Training for parenting/child care

Specific negative consequences for specific behaviors, e.g., dirty urines causes revocation to incarceration

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Prendergast, M.L., Pearson, F.S., Podus, D. et al. The Andrews’ principles of risk, needs, and responsivity as applied in drug treatment programs: meta-analysis of crime and drug use outcomes. J Exp Criminol 9, 275–300 (2013). https://doi.org/10.1007/s11292-013-9178-z

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