PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Subst Abuse Treat. Author manuscript; available in PMC 2012 April 1.
Published in final edited form as:
PMCID: PMC3056944
NIHMSID: NIHMS269322

Gender and treatment response in substance-use treatment mandated parolees

Jennifer E. Johnson, Ph.D., Peter D. Friedmann, M. D., M.P.H., Traci C. Green, Ph.D., Magdalena Harrington, M.A., and Faye S. Taxman, Ph.D., for the Step'n Out Research Group of CJ-DATS

Abstract

Well-controlled, randomized studies of correctional interventions examining gender effects are rare. This study examined gender main effects and gender by treatment interactions in a multisite randomized trial (N = 431) comparing a new form of correctional supervision for drug-involved offenders (Collaborative Behavioral Management; CBM) to standard parole. Outcomes included repeated measures of yes/no use of primary drug, alcohol use, and recidivism during 9 months post-release. Generalized estimating equation analyses indicated that despite using harder drugs at baseline, women were less likely than men to use their primary drug and to use alcohol during the follow-up period. No gender-related differences in recidivism were found. Treatment interacted with gender to predict alcohol use, with women in CBM reporting the best alcohol outcomes (only 5% used alcohol during the follow-up period). The clear expectations, positive reinforcement, recognition of successes, fairness, and support present in CBM may be particularly important for women parolees.

The United States has the highest per capita incarceration rate of any developed country, with 2.3 million people incarcerated in the U.S. at year-end 2007 (Mauer, 2003). Because 68% of offenders have substance abuse or dependence in the year prior to incarceration (Karberg & James, 2005) and more than 700,000 offenders leave state and federal prisons each year (West, Sabol, & Cooper, 2009), the transition of drug-involved offenders from incarceration to the community is a critical issue for public health and public safety.

Addiction treatment during the transition from incarceration back to the community can reduce substance use and criminal behavior (Inciardi, Martin, Butzin, Hooper, & Harrison, 1997), but newly released offenders may have limited motivation for treatment (Sung, Belenko, & Feng, 2001). As a result, innovations over the last two decades have sought closer coordination of community correctional supervision with addiction treatment (Taxman & Thanner, 2006). Unfortunately, drug-involved parolees often reenter the community with multiple behavioral expectations (e.g. conditions of parole) that are often unclear, unrealistic, or discrepant between parole and addiction treatment. Punishment is uneven, “blunt”, and arbitrary, and frequently experienced by clients as “unfair.” Parole officers have few tools to reinforce pro-social behavior, relying instead on negative sanctions as the only tool. The current system is thus suboptimal for facilitating lasting behavioral change in drug-involved offenders; many (35%) return to custody within 12 months of release (Messina, Burdon, Hagopian, Prendergast, 2006), often as a result of violations of supervision requirements such as failure to attend treatment or detected substance use (Langan, & Levin, 2002).

The Step'n Out Study (Friedmann et al., 2008; Friedmann, Rhodes, & Taxman, 2009) was a multisite randomized trial evaluating a model of correctional supervision (Collaborative Behavioral Management; CBM) involving parole officer and treatment counselor teams to facilitate the integration of parole and treatment services to optimize rehabilitative outcomes for drug-involved offenders (Marlowe, 2003; CSAT, 1994). In addition to combining the leverage of the criminal justice system with substance use treatment, CBM works to improve the integration, clarity, and expeditiousness of both positive and negative reinforcers for desired behavior.

Research indicates that in addition to the clarity and consistency of the transitional system serving drug-using incarcerated populations, gender may also be an important factor in community transition efforts for at least two reasons. First, drug-involved women and men differ when they enter prison. For example, large studies (Langan, & Pelissier, 2001; Messina, Burdon, & Prendergast, 2003) have found that compared with men in prison substance use treatment, women in prison substance use treatment used drugs more frequently, used harder drugs, and used them for different reasons (pain alleviation vs. euphoria) than men. Women also confronted more difficulties than men in areas linked to substance abuse such as lower levels of education, poorer vocational skills, higher levels of depression and other co-occurring disorders, more suicidality, and physical problems (Adams, Leukefled, & Peden, 2008; Messina et al., 2003; Messina et al., 2006; Pelissier, Camp, Gaes, Saylor, & Rhodes, 2003; Zlotnick et al., 2008). Women (compared with men) were much more likely to have drug use in family of origin, physical or sexual abuse as a child, a close friend with a drug problem, a spouse with a drug problem, a diagnosis of depression, and to rate their physical health unfavorably (Langan, & Pelissier; Messina et al., 2003; Messina et al., 2006; Pelissier, et al.). However, women offenders are less likely to have a prior criminal record and their prior records are less serious than those of men (Messina et al., 2006; Pelissier et al.).

Second, although both men and women face stigma and difficulties finding housing and employment as they leave prison, women leaving prison confront more stigma and discrimination, have fewer vocational skills, and experience bleaker employment prospects, in addition to being more likely to live with minor children as they are released (Langan, & Pelissier, 2001), all of which can affect re-entry. Responsibilities with children, economic barriers, and higher rates of co-occurring disorders may be gender-linked barriers to prison aftercare for women (Greenfield et al., 2007).

A recent review of the literature of gender differences in (non-correctional) substance use treatment (Greenfield et al., 2007) concluded that much of the available information on gender differences is derived from cross-sectional, descriptive, quasi-experimental, and observational studies, and that the field is in the very earliest stage of establishing a base of valid and reliable information on gender and substance use treatment outcomes. As a result, several recent reviews (Greenfield et al.; Plant, 2008; Walitzer & Dearing, 2006) have called for additional research on gender differences in response to substance use treatment. The need for studies on the effects of gender on treatment outcomes is even more profound for substance-using correctional populations because there are fewer randomized controlled studies in corrections overall, and because the vast majority of studies of criminal justice-involved substance users have primarily or exclusively included men. This situation is problematic because practice standards have called for called for gender-sensitive treatment (SAMHSA, 1999), but the outcomes literature supporting gender-sensitive treatments in corrections is sparse (Dolan, Koltjoff, Schreck, Smilanich, & Todd, 2003; Veysey, 2008). Observational studies comparing outcomes of men and women in similar treatments (Messina et al., 2006; Pelissier et al., 2003), and randomized studies comparing outcomes of women in different treatments (Messina, Grella, Cartier, & Torres, 2010) are beginning to be conducted, but randomized studies comparing outcomes of men and women across different treatments are still rare. These studies are needed to determine whether helpful treatment components differ for men and women.

The purpose of this study is to examine gender differences in response to two interventions for drug-involved offenders during the critical period of community reentry. Specifically, we examine differential alcohol, primary drug, and reincarceration outcomes at 9-months post-release for Collaborative Behavioral Management versus standard parole for men and women in the Step'n Out treatment study.

Method

Study Design

Step'n Out was a six-site randomized clinical trial to evaluate whether implementing collaborative behavioral management (CBM) among parole officer and treatment counselor teams might improve the three- and nine-month outcomes of parolees, compared to standard parole (Friedmann et al., 2008; 2009). The 6 sites which were chosen by research centers associated with the NIDA-funded Criminal Justice Drug Abuse Treatment Studies collaborative; recruitment at these sites took place from March 2005 to June 2008. The protocol was approved by institutional review boards at each institution, and complied with the special protections pertaining to behavioral research involving prisoners (OHRP, 2005). Following completion of screening, informed consent, and a baseline interview, subjects were randomized to the collaborative behavioral management intervention or to standard parole. Urn randomization (Stout, Wirtz, Carboneri, & Del Boca, 1994) ensured balance by gender, receipt of in-prison or transitional residential addiction treatment, length of incarceration more or less than 18 months, and moderate versus high risk for recidivism on the Lifestyle Criminality Screening Form (LCSF; Walters & McDonough, 1998).

Participants

The target population was parolees with pre-incarceration substance use disorders who were at moderate-to-high risk of recidivism. Inclusion criteria were: (a) at least 18 years of age; (b) English speaking; (c) probable drug dependence immediately prior to incarceration as determined by a score of 3 or higher on the TCU Drug Screen II (Knight, Simpson, & Hiller, 2002) or mandated drug treatment; (d) substance use treatment as a mandated or recommended condition of parole; (e) moderate-to-high risk of drug use relapse and/or recidivism as determined by a LCSF score of 7 or greater (Walters & McDonough, 1998) or by a history of 2 or more prior episodes of drug abuse treatment or drug-related convictions. Exclusion criteria were: (a) psychotic symptoms on a SCID screener (First, 2002); and (b) correctional or supervision conditions that prohibited participation in the study, including failure to leave prison on parole or probation; mandate to a special parole caseload; or transfer to a non-participating supervision office.

Eligible parolees (N = 476) were randomized to CBM or to standard parole and attended their first parole session. The current analysis includes participants (90%) who completed the Timeline Followback at the 3-month post-parole initiation assessment (N = 431, 354 men and 77 women). Follow-up data from months 4-9 was also available for 410 participants (95% of our sample).

Interventions

Standard parole

Participants in the control condition received standard parole supervision with traditional sanctions from a difference officer at the usual office. Standard parole included, at minimum, face-to-face contacts and drug testing (random, observed). Typical parole supervision involves week to monthly in-person contacts between the offender and parole officer (PO) in order to improve compliance with conditions of release (e.g. treatment attendance and drug abstinence). In the current study, average contacts between parolees and the parole officer ranged from 1 to 4 per month, as did frequency of required urine tests. While all parole offices had an affiliation with an outpatient substance abuse treatment program, the type of treatment offered was cognitive behavioral in four sites, and limited to alcohol and drug education in two sites.

Collaborative Behavioral Management (CBM)

The CBM treatment was based on the idea that sustained positive change is more likely to follow reinforcement of desired behavior than punishment of undesired behavior. In CBM, efforts were made to change the punitive dynamic of parole interventions by giving parole officers positive tools to shape behavior in a pro-social direction through the definition and reinforcement of incremental steps toward rehabilitation. Thus, operant conditioning and procedural justice theory, which maintains that individuals are more likely to comply with rules perceived as fair and equally applied (Tyler, 1990), provide the basis for CBM. In addition, CBM provides mechanisms for parole officers and substance abuse treatment providers to collaborate more closely in reinforcing behavior than does standard parole.

The 12-week CBM intervention involves an initial session between the parole officer, substance use counselor, and offender, followed by weekly contacts between the parole officer and offender; the treatment counselor joins these sessions at least once every other week. CBM has four major elements (Friedmann et al., 2008). First, it explicitly articulates the roles of both staff and offenders, their expectations of one another, and the consequences if offenders meet or fail to meet those expectations. Second, it negotiates a behavioral contract that specifies concrete target behaviors in which the offender is expected to engage on a weekly basis. These target behaviors include requirements of supervision and formal addiction treatment, and involvement in behaviors that compete with drug use (e.g., getting a job; enhancing non-drug social network). Third, it regularly monitors adherence to the weekly behavioral contract, and administers both reinforcers and sanctions to shape behavior. Fourth, CBM establishes a systematic, standardized, and progressive approach to reinforcement and sanctioning to ensure consistency and fairness.

Intervention providers

Intervention providers consisted of teams of parole officers and substance use counselors at each of the 6 sites. The providers for the CBM condition received 2.5 days of training in this approach; providers for the standard parole condition received no special training.

Intervention fidelity

Procedures to ensure fidelity of the CBM intervention included the preparation of a standard manual for the CBM approach, an initial uniform training of the CBM intervention teams, a booster training after a year of implementation, and study-wide procedures for monitoring delivery of the CBM intervention. The mean number of sessions attended for the CBM group was 8.7 (3.2 SD) with more than 95% of CBM participants attending at least 3 sessions. Adherence to the CBM protocol was high: overall 82% of sessions coded (84% of the induction sessions, 78% of the one-month sessions) met criteria for fidelity (Friedmann et al., 2008).

Assessments and Analyses

Personal interviews performed at baseline (pre-randomization), at 3 months, and at 9 months after the initial parole session used the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS) Intake and Follow-up instruments (CJ-DATS, 2004). The intake gathered baseline characteristics on the subject prior to the arrest that led to the most recent incarceration, while the 3- and 9-month follow-up forms captured information for months 1-9 after the initial parole session. Baseline measures evaluated frequency of drug and alcohol use (on a scale from “0 = never” to “9 = 4+ times per day”) and number of days incarcerated in the 6 months prior to the index incarceration. A TimeLine Followback (TLFB) calendar interview (Ehrman & Robbins, 1994; Miller, 1996; Sobell & Sobell, 1992) assessed substance use, arrests, and reincarceration on a daily basis during the follow-up period. Standardized procedures tracked subjects for follow-up interviews (Hall et al., 2003).

We used generalized estimating equation (GEE) analysis to predict yes/no use of primary drug and alcohol and prison recidivism monthly for the 9 months after prison release. Monthly dichotomous variables were creating using the daily substance use and incarceration information from the TLFB. GEE analysis allowed us to include all available data, rather than using listwise exclusion of participants with any monthly data missing. Participants had an average of 8.2 months of data available. An independent correlation structure provided the best fit to the data. Self-reports of drug use at the 3- and 9-month interviews were cross-checked against urine drug screens, which tested for cocaine, amphetamines, methamphetamine, THC, opiates, and benzodiazepines. Moderate agreement (Kappa=0.38) between drug use derived by self-report and by substance-positive urine screens (n=292, lower due to no urine collected, refusal, or incarceration) was found.

Separate analyses for each dependent variable (monthly alcohol use, primary drug use, or incarceration) included intervention condition, sex, and the intervention*sex interaction. The log of days in the community for each month was used as a covariate in the alcohol and drug analyses. Days using or incarcerated in the 6 months prior to the index incarceration, time, and site were also predictors in each model. Condition and gender were centered (+1/2, −1/2); analyses were run in SAS PROC GENMOD.

Results

Within the full sample of 476, there were no significant differences in gender, marital status, years of education, pre-prison frequency of alcohol use, or pre-prison frequency of use of a variety of drugs between participants who completed the 3-month Timeline Followback assessment (and were included in the current study) and those who did not. However, included participants were slightly younger, spent fewer days in jail in the 6 months prior to the index incarceration, and were more likely to be of minority status.

In the current sample of 431, 39 women and 182 men received CBM and 38 women and 172 men were assigned to standard parole. As has been found in previous studies, relative to men in our sample, women in our sample were less likely to live with a spouse or partner but more likely to live with children prior to incarceration, less likely to be employed prior to incarceration, had less serious lifetime arrest and incarceration histories, were more likely to self-report lifetime depression, and had more substance use in their close networks (i.e., partners or parents) (Table 1).

Table 1
Sample characteristics at baseline, by gender

Pre-prison gender differences in primary outcomes

Because the sample was selected for drug use, men and women who identified a primary drug were equally likely to report use of their primary drug in the 6 months prior to the index incarceration (82% for both genders; χ2 = .01, df = 1, p = 1.00) and reported similar frequency of primary drug use during this time (Mann-Whitney U = 10869.5, Z = −1.02, p = .31). However, men and women differed on categories of primary drug (χ2 = 10.55, df = 4, p = .03); women were more likely than men to report stimulants (primarily cocaine) as their primary drug; men were more likely than women to have marijuana as a primary drug (see Table 1). Men and women also differed on rates of alcohol use: men were significantly more likely to use alcohol in the 6 months prior to their index incarceration (χ2 = 14.66, df = 1, p < .001), with 63% of men vs. 39% of women reporting alcohol use during that time. However, among those who used alcohol, men and women used it with similar frequency (Mann-Whitney U = 3061.0, Z = −.80, p = .42). Men and women had similar number of days incarcerated in the 6 months prior to the index incarceration (Mann-Whitney U = 12342.5, Z = −.79, p = .43); 27% of men and 22% of women were incarcerated for at least one day during that time.

Gender differences in intervention outcome

Primary drug use

Despite reporting “harder” primary drugs, women were less likely than men to use their primary drug at each month post-release (the gender main effect on use of primary drug was significant; see Table 2). Gender differences in post-prison primary drug use could not be explained by pre-prison differences in frequency of drug use because regression analyses controlled for pre-prison frequency of primary drug use. Furthermore, even though men and women reported similar frequency of pre-prison primary drug use, we reran the analysis controlling for primary drug category to ensure that the gender difference in likelihood of post-prison drug use was not attributable to gender differences in primary drug categories at baseline,. Results indicated that those whose primary drug was a stimulant were less likely to use their primary drug during the follow-up period (B = −2.46, SE = .51, p < .001) and those whose primary drug was an opiate tended toward more use it during the follow-up period (B = .61, SE = .31, p = .05) than those who had marijuana as a primary drug. However, differences in primary drug of abuse did not account for gender differences in likelihood of primary drug use after release; the gender effect was still significant (B = −1.62, SE = .42, p < .001).

Table 2
Results of GEE Analyses Predicting Monthly Yes / No Alcohol Use, Primary Drug Use, and Prison Recidivism During Months 1-9 Post-Release

The interaction between intervention and gender was not significant in predicting primary drug use, meaning that the comparative effectiveness of the two interventions did not differ for men and women. For men, 27% of control participants and 21% of CBM participants used their primary drug at any time during the 9 months post-release. For women, 17% of the control participants and 11% of the CBM participants used their primary drug during this time (see Figure 1).

Figure 1
Percent reporting any primary drug use during 9-month follow-up.

Alcohol use

Even after controlling for differences in baseline frequency of alcohol use, female gender also predicted reduced likelihood of alcohol use at each month post-release (Table 2). Furthermore, the interaction between gender and intervention was also significant, with CBM showing a larger reduction in likelihood of alcohol use for women than for men (Figure 2). For men, 47% of the control participants and 39% of the CBM participants used alcohol at any time during the 9 months post-release. For women, 29% of the control participants and only 5% of the CBM participants used alcohol during this time.

Figure 2
Percent reporting any alcohol use during 9-month follow-up.

Reincarceration

There was no gender difference in monthly likelihood of being reincarcerated during the 9-months after release from prison (Table 2). CBM did not significantly reduce reincarceration risk more for either gender, although Figure 3 seems to indicate a slight trend toward CBM having greater effects for women. For men, 36% of the control participants and 34% of the CBM participants were reincarcerated during the 9-month follow-up. For women, 29% of the control participants and 21% of the CBM participants were reincarcerated during follow-up.

Figure 3
Percent reincarcerated during 9-month follow-up.

Discussion

In this study, female gender predicted reduced monthly likelihood of both primary drug and alcohol use in the 9 months after incarceration, even after controlling for baseline frequency of use of primary drug or alcohol. Lower rates of drug use in particular for women is notable given that women were more likely than men to report use of some “hard” drugs (cocaine or other stimulants) prior to prison. When primary drug category was controlled, gender was still a strong predictor of reduced likelihood of drug use in the 9 months after release from prison.

These findings in a sample of parolees are consistent with past findings in samples of prisoners which have indicated that women in prison substance use treatment have lower drug use rates than men in the months after being released from prison (Pelissier et al., 2003), despite having more severe and more frequent pre-prison drug use, more co-occurring mental health problems, more medical problems, higher rates of physical and sexual victimization, lower levels of education, less social support, and poorer vocational prospects than do men, in addition to being more likely than men to return to full responsibility for children (Langan, & Pelissier, 2001). In summarizing research on non-correctional substance use treatment, Fiorentine and colleagues (1997) have proposed the “gender paradox”, which refers to the fact that women in drug treatment tend to fare at least as well as do men in terms of drug use outcomes despite higher levels of many risk factors and more psychosocial impairment at treatment entry (Greenfield et al., 2007). This gender effect appears accentuated in criminal justice populations, where female drug users clearly and consistently have more impairment, but better post-prison drug use outcomes than do males. Two large studies (Pelissier et al., 2003; Messina et al., 2006) also found that factors predicting aftercare treatment completion, post-treatment drug use, and recidivism were slightly different for women than for men, suggesting the possibility of gender-specific pathways to successful community re-entry.

Our findings also support the possibility of gender-specific processes at community re-entry. In addition to gender main effects in the current study, a gender by intervention interaction was found in predicting likelihood of post-release alcohol use. CBM reduced alcohol use rates slightly (from 47% to 39%) for men, but dramatically (29% to 5%) for women. In this study, a collaborative, positive, consistent system of integrated parole and treatment services provided more treatment advantages for women than men in terms of alcohol use during the 9 months post-release. Interaction effects were not found for all outcomes assessed, but where treatment effects were strongest, treatment interacted with gender to produce better treatment gains for women than for men. This finding is important because: 1) it lends some support to the idea that optimal transitional treatments may differ for men and women, 2) it is unusual to find gender by intervention interactions in the psychosocial treatment literature, indicating that correctional supervision may constitute a special case where gender-specific responses are found, and 3) very few large-scale randomized trials of transitional interventions for drug-involved offenders have been conducted (Taxman, 2002; Young, 2002).

The ability of CBM to reduce likelihood of alcohol use among female parolees has public health significance because alcohol use is associated with a different pattern of consequences for criminal justice involved women than it is for other populations. For example, a recent study (Strong, Caviness, Anderson, Brown, & Stein, 2010) found that 83% of incarcerated women who endorsed risky drinking had gotten into a physical fight after drinking, 67% had been arrested because of drinking, 53% had been seriously injured after drinking, 49% had injured someone else after drinking, 46% had a car accident after drinking, 39% had problems parenting as a result of drinking, and 33% had an unplanned pregnancy after drinking. Furthermore, most female parolees are of child-bearing age (Hughes & Wilson, 2010), many engage in unprotected sex (Leigh, Ames, & Stacy, 2008), and approximately 7 in 10 (Greenfeld & Snell, 1999) are already mothers. Because so many female parolees may become pregnant or are already mothering, reduced alcohol use among this population may lead to reduced risk of fetal alcohol syndrome, as well as reduced risk of alcohol-related accidents, alcohol-related violence, and other risky behaviors that could negatively impact these vulnerable women and their children.

It is not clear why CBM resulted in better alcohol use outcomes for women than for men relative to standard parole, better fitting gender-specific needs of women in terms of this outcome. It is possible that women may respond better to social reinforcers, such as those emphasized in CBM. However, it is also possible that the quality of their relationship with their parole officer, which was a focus of CBM, is on average more important to women than it is to men. For example, an extensive qualitative study (Bloom, Owen, & Covington, 2003) found that men are less open about their needs and adopt a “get in and get out” mentality in their interactions with parole officers, whereas women often take more time to provide information and voice their needs. Women have higher expectations of their parole officers and are more likely to believe it when they are told at orientation that their parole officer is there to help them. Women are also more likely to develop a trusting relationship with a parole officer such that even if the woman is transferred, she will not sever ties with her original parole officer (Bloom et al.). Women parolees' comparative willingness to reach out for help to professional staff may be related to having less severe criminal histories (Pelissier et al., 2003); lower levels of psychopathy (Rogers, Jordan, & Harrison, 2007); more substance use, mental health, physical, and life problems; and less support for sobriety in their close networks on average than do male parolees (Langan & Pelissier, 2001; Pelissier et al.), or to other gender-based contributors to help-seeking. For example, a study of drug court participants found that females, especially those with mental health problems, had higher levels of problem recognition and desire for help than did males (Webster et al., 2006). In addition, some research suggests that strategies that reduce confrontation and provide choices for substance use clients have larger effect sizes in minority populations than in majority populations (Levensky, Kersh, Cavasos, & Brooks, 2008). A similar phenomenon might be true for women offenders, who have historically been stigmatized and disempowered and who seem to respond to someone taking the time to listen to them and take their concerns seriously (Johnson & Zlotnick, 2008). This literature might suggest that CBM's cooperative, positive, and fair but non-punitive approach provided a safer and more engaging environment that was especially important to women.

In conclusion, the clear expectations, positive reinforcement, recognition of successes, emphasis on consistency and fairness, and focus on overall life functioning and support present in CBM (Friedmann et al., 2008; 2009) might be particularly beneficial for women parolees (Comfort, Loverro, & Kaltenbach, 2000; Nelson-Zlupko, Dore, Kauffman, & Kaltenbach, 1996; Pelissier, 2004; Pelissier et al., 2003; Ramlow, White, Watson, & Leukefeld, 1997; Welle, Franklin, & Jainchill, 1998) who suffer from higher levels of depression, more life problems, and higher rates of violent victimization than men (Adams et al., 2008; Johnson, 2006). Including these components in correctional supervision may result in better substance-related outcomes for the more than 1,000,000 U.S. women currently under correctional supervision (Glaze & Bonczar, 2008).

Acknowledgment

Dr. Johnson is supported by K23DA021159 from the National Institute of Drug Abuse, National Institutes of Health (NIDA/NIH). The Step'n Out study was funded as part of the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS) under a cooperative agreement from NIDA/NIH, with support from the Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration (SAMHSA); the Centers for Disease Control and Prevention (CDC); the National Institute on Alcohol Abuse and Alcoholism (all part of the U.S. Department of Health and Human Services); and from the Bureau of Justice Assistance of the U.S. Department of Justice. The authors gratefully acknowledge the collaborative contributions by NIDA, the Coordinating Center (George Mason University/Virginia Commonwealth University/University of Maryland at College Park), and the Research Centers in CJ-DATS (Brown University, Lifespan Hospital; Connecticut Department of Mental Health and Addiction Services; National Development and Research Institutes, Inc., Center for Therapeutic Community Research; National Development and Research Institutes, Inc., Center for the Integration of Research and Practice; Texas Christian University, Institute of Behavioral Research; University of Delaware, Center for Drug and Alcohol Studies; University of Kentucky, Center on Drug and Alcohol Research; University of California at Los Angeles, Integrated Substance Abuse Programs; and University of Miami, Center for Treatment Research on Adolescent Drug Abuse. The contents are solely the responsibility of the authors and do not necessarily represent the views of the Department of Health and Human Services, the Department of Justice, NIDA/NIH, other CJ-DATS participants, or the Department of Veterans Affairs.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Jennifer E. Johnson, Brown University.

Peter D. Friedmann, Providence VA Medical Center, Rhode Island Hospital.

Traci C. Green, Rhode Island Hospital and Brown University.

Magdalena Harrington, Rhode Island Hospital and Brown University.

Faye S. Taxman, George Mason University.

References

  • Adams S, Leukefeld CG, Peden AR. Substance abuse treatment for women offenders: A research review. Journal of Addictions Nursing. 2008;19:61–75.
  • Bloom B, Owen B, Covington S. Gender-responsive strategies: Research, practice, and guiding principles for women offenders. 2003. (National Institutes of Corrections accession number 018017). Retrieved 05/21/2010, from http://nicic.org/downloads/pdf/2003/018017.pdf.
  • Center for Substance Abuse Treatment (CSAT Combining substance abuse treatment with intermediate sanctions for adults in the criminal justice system. Treatment improvement protocol (TIP) no. 12. Substance Abuse and Mental Health Services Administration; Rockville, MD: 1994. (DHHS Pub. no. (SMA) 94-3004 ed.).
  • CJ-DATS CJ-DATS Core Instruments. 2004. Retrieved June 12, 2007, from http://cjdats.org/ka/ka-2.cfm?folder/id=269.
  • Comfort M, Loverro J, Kaltenbach K. A search for strategies to engage women in substance abuse treatment. Social Work in Health Care. 2000;31(4):59–70. [PubMed]
  • Dolan L, Kolthoff K, Schreck M, Smilanich P, Todd R. Gender specific treatment for clients with co-occurring disorders. GAINS Center; Delmar, NY: 2003.
  • Ehrman RN, Robbins SJ. Reliability and validity of 6-month timeline reports of cocaine and heroin use in a methadone population. Journal of Consulting and Clinical Psychology. 1994;62:843–850. [PubMed]
  • Fiorentine R, Anglin MD, Gil-Rivas V, Taylor E. Drug treatment: Explaining the gender paradox. Substance Use and Misuse. 1997;32(6):653–678. [PubMed]
  • First MB. The DSM series and experience with DSM-IV. Psychopathology. 2002;35(2-3):67–71. [PubMed]
  • Friedmann PD, Katz EC, Rhodes AG, Taxman FS, O'Connell DJ, Frisman LK, Burdon W, Fletcher BS, Litt M, Clarke J, Martin S. Collaborative Behavioral Management for Drug-Involved Parolees: Rationale and Design of the Step'n Out Study. Journal of Offender Rehabilitation. 2008;47(3):290–318. [PMC free article] [PubMed]
  • Friedmann PD, Rhodes AG, Taxman FS, for the Step'n Out Research Group of CJDATS Collaborative Behavioral Management: Integration and Intensification of Parole and Outpatient Addiction Treatment Services in the Step'n Out Study. Journal of Experimental Criminology. 2009;5:227–244. [PMC free article] [PubMed]
  • Glaze LE, Bonczar TP. Probation and Parole in the United States, 2007 Statistical Tables (NCJ 224280) Bureau of Justice Statistics; Washington, D.C.: 2008.
  • Greenfield SF, Brooks A, Gordon S, Green C, Kropp F, McHugh R, Lincoln M, Hien D, Miele G. Substance abuse treatment entry, retention, and outcome in women: A review of the literature. Drug and Alcohol Dependence. 2007;86(1):1–21. [PMC free article] [PubMed]
  • Greenfeld LA, Snell TL. Women Offenders (NCJ 175688) Bureau of Justice Statistics; Washington, D.C.: 1999.
  • Hall EA, Zuniga R, Cartier J, Anglin MD, Danila B, Ryan R, Mantius K. Staying in Touch: A Fieldwork Manual of Tracking Procedures for Locating Substance Abusers in Follow-up Studies. 2 nd Edition UCLA Integrated Substance Abuse Programs; Los Angeles, CA: 2003.
  • Hughes T, Wilson DJ. Re-entry Trends in the United States. Bureau of Justice Statistics; Washington, D.C.: 2010. Retrieved 5/20/2010, 2010, from http://bjs.ojp.usdoj.gov/content/reentry/reentry.cfm.
  • Inciardi JA, Martin SS, Butzin CA, Hooper RM, Harrison LD. An effective model of prison-based treatment for drug-involved offenders. Journal of Drug Issues. 1997;27(2):261–278.
  • Johnson H. Drug use by incarcerated women offenders. Drug and Alcohol Review. 2006;25:433–437. [PubMed]
  • Johnson JE, Zlotnick C. A pilot study of group interpersonal psychotherapy for depression in substance-abusing female prisoners. Journal of Substance Abuse Treatment. 2008;34(4):371–377. [PubMed]
  • Karberg JC, James DJ. Substance dependence, abuse, and treatment of jail inmates 2002 (NCJ 209558) Bureau of Justice Statistics; Washington, D.C.: 2005.
  • Knight K, Simpson DD, Hiller ML. Screening and referral for substance abuse treatment in the criminal justice system. In: Leukefeld CG, Tims FM, Farabee D, editors. Treatment of drug offenders: Policies and issues. Springer; New York: 2002. pp. 259–272.
  • Langan NP, Pelissier BMM. Gender differences among prisoners in drug treatment. Journal of Substance Abuse. 2001;13(3):291–301. [PubMed]
  • Langan PA, Levin DJ. Redicivism of prisoners released in 1994. U.S. Department of Justice, Bureau of Justice Statistics; Washington, DC: 2002. (Publication No. NCJ-193427).
  • Leigh B, Ames SL, Stacy AW. Alcohol, drugs, and condom use among drug offenders: An event-based analysis. Drug and Alcohol Dependence. 2008;93:38–42. [PMC free article] [PubMed]
  • Levensky ER, Kersh BC, Cavasos LL, Brooks JA, Fisher JE. Motivational interviewing. In: O'Donohue WT, editor. Cognitive behavior therapy: Applying empirically supported techniques in your practice. 2nd ed. John Wiley & Sons Inc; Hoboken, NJ: 2008. pp. 357–366.
  • Marlowe DB. Integrating substance abuse treatment and criminal justice supervision. Science and Practice Perspectives. 2003;2:4–14. [PMC free article] [PubMed]
  • Mauer M. Comparative International Rates of Incarceration: An Examination of Causes and Trends. Report of the Sentence Project presented to the U.S. Commission on Civil Rights. 2003. Accessed February 10, 2009 at http://www.sentencingproject.org/Admin/Documents/publications/inc_comparative_intl.pdf.
  • Messina N, Burdon W, Hagopian G, Prendergast M. Predictors of prison-based treatment outcomes: A comparison of men and women participants. The American Journal of Drug and Alcohol Abuse. 2006;32:7–28. [PubMed]
  • Messina NP, Burdon WM, Prendergast ML. Assessing the needs of women in institutional therapeutic communities. Journal of Offender Rehabilitation. 2003;37(2):89–106.
  • Messina N, Grella CE, Cartier J, Torres S. A randomized experimental study of gender-responsive substance abuse treatment for women in prison. Journal of Substance Abuse Treatment. 2010;38(2):97–107. [PMC free article] [PubMed]
  • Miller WR. Form 90: A structured assessment interview for drinking and related behaviors: Test Manual. U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism; Washington DC: 1996.
  • Nelson-Zlupko L, Dore MM, Kauffman E, Kaltenbach K. Women in recovery: Their perceptions of treatment effectiveness. Journal of Substance Abuse Treatment. 1996;13:51–59. [PubMed]
  • Office of Human Research Protections (OHRP Code of federal regulations: Part 46 protection of human subjects. 2005. Retrieved May 29, 2007, from http://www.hhs.gov/ohrp/humansubjects/guidance/45cfr46.htm#skip.
  • Pelissier B. Gender differences in substance use treatment entry and retention among prisoners with substance use histories. American Journal of Public Health. 2004;94(8):1418–1424. [PubMed]
  • Pelissier BMM, Camp SD, Gaes GG, Saylor WG, Rhodes W. Gender differences in outcomes from prison-based residential treatment. Journal of Substance Abuse Treatment. 2003;24(2):149–160. [PubMed]
  • Plant ML. The role of alcohol in women's lives: A review of issues and responses. Journal of Substance Use. 2008;13(3):155–191.
  • Ramlow BE, White AL, Watson DD, Leukefeld CG. The needs of women with substance use problems: An expanded vision for treatment. Substance Use and Misuse. 1997;32:1395–1404. [PubMed]
  • Rogers R, Jordan MJ, Harrison KS. Facets of psychopathy, Axis II traits, and behavioral dysregulation among jail detainees. Behavioral Sciences and the Law. 2007;25:471–483. [PubMed]
  • SAMHSA Substance abuse treatment for women offenders: Guide to promising practices. U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment; Rockville, MD: 1999.
  • Sobell LC, Sobell MB. Time line follow-back: A technique for assessing self-reported alcohol consumption. In: Allen RLJ, editor. Measuring alcohol consumption. Humana Press; Totowa, NH: 1992. pp. 41–72.
  • Stout RL, Wirtz PW, Carbonari JP, Del Boca FK. Ensuring balanced distribution of prognostic factors in treatment outcome research. Journal of Studies on Alcohol Supplement. 1994;12:70–75. [PubMed]
  • Strong D, Caviness C, Anderson B, Brown RA, Stein M. Assessing the severity of hazardous drinking and related consequences among incarcerated women. Alcoholism: Clinical and Experimental Research. 2010;34(5):907–914. [PubMed]
  • Sung HE, Belenko S, Feng L. Treatment compliance in the trajectory of treatment progress among offenders. Journal of Substance Abuse Treatment. 2001;20(2):153–162. [PubMed]
  • Taxman FS. Supervision -- Exploring the dimensions of effectiveness. Federal Probation. 2002;66:14–27.
  • Taxman FS, Thanner M. Risk, need, and responsivity (rnr): It all depends. Crime and Delinquency. 2006;52(1):28–51. [PMC free article] [PubMed]
  • Tyler T. Why people obey the law: Procedural justice, legitimacy, and compliance. Yale University Press; New Haven, CT: 1990.
  • Veysey BM. Specific needs of women diagnosed with mental illnesses in U.S. jails. In: Levin B, editor. Women's mental health services: A public health perspective. Sage; Thousand Oaks, CA: 2008. pp. 368–389.
  • Walitzer KS, Dearing RL. Gender differences in alcohol and substance use relapse. Clinical Psychology Review. 2006;26(2):128–148. [PubMed]
  • Walters GD, McDonough JR. The lifestyle criminality screening form as a predictor of federal parole/probation/supervised release outcome. Legal and Criminological Psychology. 1998;3:173–181.
  • Webster JM, Rosen PJ, Krietemeyer J, Mateyoke-Scrivner A, Staton-Tindall M, Leukefeld C. Gender, mental health, and treatment motivation in a drug court setting. Journal of Psychoactive Drugs. 2006;38(4):441–448. [PubMed]
  • Welle D, Falkin GP, Jainchill N. Current approaches to drug treatment for women offenders. Journal of Substance Abuse treatment. 1998;15:151–163. [PubMed]
  • West HC, Sabol W, Cooper M. Prisoners in 2008 (NCJ 228417) Bureau of Justice Statistics; Washington, D.C.: 2009.
  • Young D. Impacts of perceived legal pressure on retention in drug treatment. Criminal Justice and Behavior. 2002;29:27–55.
  • Zlotnick C, Clarke JG, Friedmann PD, Roberts MB, Sacks S, Melnick G. Gender differences in comorbid disorders among offenders in prison substance abuse treatment programs. Behavioral Sciences and the Law. 2008;26(4):403–412. [PMC free article] [PubMed]