Elsevier

Drug and Alcohol Dependence

Volume 96, Issue 3, 1 August 2008, Pages 271-280
Drug and Alcohol Dependence

Predictors of therapeutic engagement in prison-based drug treatment

https://doi.org/10.1016/j.drugalcdep.2008.03.019Get rights and content

Abstract

Few studies to date have examined predictors of therapeutic engagement (TE) or other indicators of responsiveness to prison drug treatment. Subjects were 347 inmates participating in a 12-month modified therapeutic community (TC) drug treatment program at a specialized treatment prison for convicted, drug-involved offenders. Data were obtained through correctional databases and the administration of the TCU Drug Screen II, the Resident Evaluation of Self and Treatment (REST), and the Counselor Rating of Client (CRC) form. Three main hypotheses were supported: (1) baseline motivation predicted therapeutic engagement net of other inmate characteristics; (2) critical dimensions of the treatment experience (e.g., peer support, counselor rapport) also predicted therapeutic engagement; and (3) dynamic predictors and programmatic characteristics became more important over time. Implications for research, theory and policy are discussed.

Introduction

Drug-involved offenders comprise a large portion of local, state and federal correctional populations. At midyear 2005, 2.2 million inmates were incarcerated in the U.S. jails and prisons, at a rate of 738 per 100,000 adults (up from 601 in 1995) (Harrison and Beck, 2006). Drug offenders accounted for 21% of sentenced prisoners under State jurisdiction in 2002, and 55% of sentenced prisoners under Federal jurisdiction in 2003 (Harrison and Beck, 2005).

In the 2004 Survey of Inmates in State and Federal Correctional Facilities, the Bureau of Justice Statistics included for the first time measures of drug dependence and abuse based on criteria specified in the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) (Mumola and Karberg, 2006). Fifty-three percent of State and 45% of Federal prisoners met DSM-IV criteria for drug dependence or abuse. Among drug dependent prisoners, 40% of State and 49% of Federal inmates took part in some type of drug abuse program including self-help groups, peer counseling, and drug education. However, the percentage who took part in treatment programs with a trained professional (15%) remained unchanged from 1997.

Prison-based therapeutic community (TC) drug treatment has been shown to be effective in breaking the cycle of relapse and recidivism among seriously drug-involved offenders (Gaes et al., 1999, Mitchell et al., 2006, Mitchell et al., 2007, Pearson and Lipton, 1999). However, little research has examined the diverse individual and programmatic factors that influence inmate responsiveness to treatment, which is theoretically and empirically related to treatment completion, relapse and recidivism (Farabee et al., 1999, Fletcher and Tims, 1992, Hiller et al., 2002a, Office of National Drug Control Policy, 1996, Office of National Drug Control Policy, 1999, Pearson and Lipton, 1999, Rosen et al., 2004, Simpson, 2001, Welsh and Zajac, 2004a, Welsh and Zajac, 2004b).

According to the Texas Christian University (TCU) Treatment Process Model (Simpson, 2001, Simpson, 2002, Simpson, 2004), variables that moderate or mediate the effects of treatment include individual offender motivation and attributes, counselor attributes and skills, program characteristics, therapeutic relationships with counselors and peers, program participation, and psychological improvement (Fig. 1). In the TCU model, individual differences and treatment processes interact to influence both intermediate goals (behavioral change and psychological improvement) and longer term outcomes such as reduced substance abuse and criminal behavior.

Client responses to treatment at each stage are influenced by elements at previous stages (Simpson, 2001). For example, in the intake phase, clients enter treatment with varying attributes that influence their responses to treatment, including levels of motivation, treatment readiness, severity of drug use, current and prior criminal history, and psychological characteristics. Psychological factors such as hostility, depression, or anxiety may constrain one's level of participation in treatment activities (Knight et al., 1994, Rosenstock, 1966, Woody et al., 1990). Experienced, skilled counselors are more likely to develop productive therapeutic relationships with inmates. Program characteristics such as consistent enforcement of rules and clear rewards and sanctions for behavior are more likely to facilitate adoption of the principles of right living (DeLeon, 2000).

Client variables such as low motivation present obstacles to therapeutic engagement (Hiller et al., 1999, Hiller et al., 2002b, Prochaska et al., 1992, Simpson, 1997, Simpson and Joe, 1993a, DeLeon, 2000). In a sample of 429 probationers in a 6-month TC, Hiller et al. (2002b) found that offender motivation and background characteristics predicted therapeutic engagement and inmate satisfaction with treatment. Desire for help and treatment readiness, controlling for other individual factors, were associated with three indicators of therapeutic engagement: personal involvement, personal progress, and psychological safety. A study of 220 Kentucky prison inmates (Rosen et al., 2004) found that motivation, measured by desire for help and problem recognition, was associated with confidence in treatment and commitment to treatment.

Social functioning is also related to responses to drug treatment (Chien, 1980, Powell and Taylor, 1992, Simpson and Joe, 1993b). High levels of hostility are often present in individuals with a history of drug abuse (Chien, 1980). Substance abusers tend to be great risk takers (Chien, 1980, Murray and Singer, 1988). Addicts often display low social conformity, a deep mistrust of others, and a Machiavellian approach to interpersonal relationships (Chien, 1980).

The treatment process itself influences individual responses to treatment. Any specific treatment program offers counselors with varied training, skills, and experience, and programmatic elements vary along dimensions such as structure and consistency (Lowenkamp et al., 2006). Client perceptions of program structure and treatment sessions are often associated with treatment participation and completion (Hiller, 1996). Mechanisms that facilitate behavioral change in TC include the nature and quality of therapeutic relationships forged with counselors and community members, active participation in treatment, and improvements in psychological and social functioning (DeLeon, 2000). Strong therapeutic relationships with both peers and counselors predict longer retention in treatment and lower levels of drug use (Simpson, 1997).

A key variable in the treatment phase is therapeutic engagement, which refers to a client's active involvement in and commitment to treatment. Higher levels of therapeutic engagement are associated with greater treatment retention (Hser et al., 1999, Joe et al., 1998, Simpson, 1979, Simpson, 1981, Simpson et al., 1995) and lower relapse and recidivism rates (DeLeon et al., 1997, Simpson and Joe, 1993a).

Broome et al., 1996a, Broome et al., 1996b found that lower levels of therapeutic engagement (as indicated by low ratings of counselor competence and peer support) were associated with higher rearrest rates in a sample of 279 probationers. Sia et al. (2000), in a sample of 500 probationers randomly assigned to readiness training v. a typical TC program, found that motivation (treatment readiness) predicted therapeutic engagement and successful completion of treatment.

The influence of motivation on therapeutic engagement appears to be critical. Even though participation in treatment in prison is technically voluntary, many inmates agree to participate in treatment because they want to get early release, work release, or parole. While coerced treatment can be effective under some conditions (Anglin et al., 1998, Collins and Allison, 1983, Hiller et al., 1998, Lurigio, 2000, Melnick et al., 2004, Salmon and Salmon, 1983, Siddall and Conway, 1988, Young, 2002), low internal motivation to change likely weakens treatment outcomes (Prochaska et al., 1992).

During the posttreatment or reentry phase, those reentering the community hopefully do so with skills, attitudes, and behaviors that enhance their personal and social adjustment, and reduce their likelihood of relapse and recidivism. Most prison TC programs emphasize relapse prevention and release planning during the final phase of prison treatment. Aftercare treatment in the community following release from prison tends to enhance posttreatment effects (Inciardi et al., 2004, Knight et al., 1999, Prendergast et al., 2004).

While the TCU treatment process model has been extensively validated in community settings (Simpson et al., 2000, Simpson et al., 1995, Simpson et al., 1997c), relatively little research has examined the generalizability of findings to prison-based drug treatment (Simpson and Knight, 2001), and little work has examined predictors or consequences of therapeutic engagement in prison-based treatment settings (Hiller et al., 2002a, Hiller et al., 1999, Rosen et al., 2004). Further research with prisoner populations can enhance our understanding of inmate responsivity to treatment, and help target individual and programmatic factors that facilitate engagement, recovery and reentry.

The present study examined three main hypotheses. First, baseline motivation should predict therapeutic engagement even after controlling for individual and programmatic factors. Second, other critical dimensions of TC (e.g., peer support, counselor rapport) are also expected to predict therapeutic engagement, net of controls. Third, the magnitude of different types of predictors is expected to change over time. Static predictors (e.g., criminal history, age, prior substance abuse) and baseline motivation should become less important over the course of treatment, while dynamic risk factors (e.g., social conformity, hostility) and programmatic characteristics (e.g., counselor rapport, peer support) should become more important. Little research has examined these hypotheses with a prison sample, and few studies have examined individual changes in response to treatment over time.

Section snippets

Participants

Participants were 347 inmates admitted to a 12-month modified therapeutic community (TC) drug treatment program at SCI-Chester, a 1200-bed specialized treatment prison for convicted offenders with a history of substance abuse. Convergent data sources supported the therapeutic integrity of the TC program at Chester prior to the beginning of the study. The TC program has consistently met American Correctional Association standards for accreditation and certification (American Correctional

Results

Descriptives (means, percentages) are shown in Table 1. Regression coefficients predicting therapeutic engagement are shown in Table 2 at time 1 (1 mo.), time 2 (6 mo.), time 3 (12 mo.), and overall (T1  T3 or T3  T1). Variables were entered using Forward Regression (P-IN = .05; P-OUT = .10). Analyses examined which variables were significant at each stage, and whether the magnitude of different predictors changed over time.

As predicted, motivation (measured by Treatment Readiness) significantly

Discussion

Few prior studies have examined predictors of therapeutic engagement in prison-based drug treatment, using a fully multivariate model that controls for competing influences. Few studies have examined changes in inmate responses to treatment over time; and fewer still have utilized both quantitative and qualitative methods. Such research can enhance our understanding of inmate responsivity to treatment, and help target individual and programmatic factors that may facilitate successful recovery

Conclusion

Results suggest that policies regarding prison-based drug treatment should focus on strengthening and enhancing therapeutic engagement, but also TC quality and implementation. Guidelines formulated by professional associations and informed by both clinical practice and research suggest that the bar could profitably be raised (DeLeon, 2000, Farabee et al., 1999, Kressel et al., 2002, Office of National Drug Control Policy, 1999, Taxman and Bouffard, 2002). Further research is also needed to

Conflict of interest

Neither author has any current or prior conflict of interest regarding any financial, personal, or other relationships with other people or organizations that were involved in the research reported in this article.

Acknowledgments

An abbreviated version of this paper was presented at the Annual Meetings of the American Society of Criminology, Atlanta, November 2007. The research reported here was supported by Grant #2002-RT-BX-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. The authors gratefully acknowledge the valuable

References (106)

  • D.D. Simpson et al.

    Client engagement and change during drug abuse treatment

    J. Subst. Abuse

    (1995)
  • American Correctional Association, 2005. Performance-Based Standards For Therapeutic Communities. ACA, Washington,...
  • American Correctional Association, 2002. Performance-Based Standards For Correctional Health Care For Adult...
  • M.P.S.R. Amoureus et al.

    The Addiction Severity Index in penitentiaries

    Int. J. Offender Ther. Comp. Criminol.

    (1994)
  • D.A. Andrews et al.

    The Psychology of Criminal Conduct

    (2006)
  • Anglin, M.D., Prendergast, M., Farabee, D., 1998. The effectiveness of coerced treatment for drug-abusing offenders....
  • H.A. Asher

    Causal Modeling

    (1983)
  • S. Belenko

    Assessing released inmates for substance-abuse-related service needs

    Crime Delinquency

    (2006)
  • D.A. Belsley et al.

    Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

    (1980)
  • P. Bentler et al.

    Linear structural equations with latent variables

    Psychometrika

    (1980)
  • J. Blankenship et al.

    Cognitive enhancements of readiness for corrections-based treatment for drug abuse

    Prison J.

    (1999)
  • K.M. Broome et al.

    Drug treatment process indicators for probationers and prediction of recidivism

    J. Subst. Abuse Treat.

    (1996)
  • K.M. Broome et al.

    Evaluating the drug-abusing probationer: clinical interview versus self-administered assessment

    Crim. Justice Behav.

    (1996)
  • R.F. Catalano et al.

    Mediating the effects of poverty, gender, individual characteristics, and external constraints on antisocial behavior: a test of the social development model and implications for developmental life-course theory

  • Chien, I., 1980. Psychological, social, and epidemiological factors in juvenile drug use. In: Lettieri, D.J., Sayers,...
  • J.J. Collins et al.

    Legal coercion and retention in drug abuse treatment

    Hospital Community Psychiatry

    (1983)
  • M. Czuchry et al.

    Drug abuse treatment in criminal justice settings: enhancing community engagement and helpfulness

    Am. J. Drug Alcohol Abuse

    (2000)
  • S.M. Dees et al.

    Implementing a readiness program for mandated substance abuse treatment

  • G. DeLeon

    The Therapeutic Community: Theory, Model and Method

    (2000)
  • G. DeLeon et al.

    Motivation and readiness for therapeutic community treatment among cocaine and other drug abusers

    Am. J. Drug Alcohol Abuse

    (1997)
  • D. Farabee et al.

    Barriers to implementing effective correctional drug treatment programs

    Prison J.

    (1999)
  • B.W. Fletcher et al.

    Methodological issues: drug abuse treatment in prisons and jails

  • J. Fox

    Regression Diagnostics

    (1991)
  • G.G. Gaes et al.

    Adult correctional treatment

  • K.A. Gnall et al.

    Assessing for success in offender reentry

    Corrections Today

    (2005)
  • E.A. Hanushek et al.

    Statistical Methods For Social Scientists

    (1977)
  • Harrison, P.M., Beck, A.J., 2006. Prison and Jail and Inmates at Midyear 2005 (NCJ 213133). U.S. Department of Justice,...
  • Harrison, P.M., Beck, A.J., 2005. Prisoners in 2004 (NCJ 210677). U.S. Department of Justice, Office of Justice...
  • L.D. Harrison et al.

    Residential Substance Abuse Treatment for State Prisoners: Implementation Lessons Learned (NCJ 195738)

    (2003)
  • Hiller, M.L., 1996. Correlates of Recidivism and Relapse for Parolees who Received in-Prison Substance Abuse Treatment...
  • M.L. Hiller et al.

    Process Assessment of Correctional Treatment (PACT) (Final Report)

    (2000)
  • M.L. Hiller et al.

    Legal pressure and treatment retention in a national sample of long-term residential programs

    Criminal Justice Behav.

    (1998)
  • M.L. Hiller et al.

    Motivation as a predictor of therapeutic engagement in mandated residential substance abuse treatment

    Criminal Justice Behav.

    (2002)
  • M.L. Hiller et al.

    Assessing and evaluating mandated correctional substance-abuse treatment

  • M. Hiller et al.

    Risk factors that predict dropout from corrections-based treatment for drug abuse

    Prison J.

    (1999)
  • Inciardi, J.A., 1994. Screening and assessment for alcohol and other drug abuse among adults in the criminal justice...
  • J.A. Inciardi et al.

    Five-year outcomes of therapeutic community treatment of drug-involved offenders after release from prison

    Crime Delinquency

    (2004)
  • J.A. Inciardi et al.

    Obstacles to the implementation and evaluation of drug treatment programs in correctional settings: reviewing the Delaware KEY experience

  • N. Jainchill et al.

    The TC Client Progress Scales (TCCPS). (Developed with funding from NIDA Grant #R01 DA 03617)

    (1987)
  • G.W. Joe et al.

    Depression and decision-making among intravenous drug users

    Psychol. Rep.

    (1991)
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