The Moderating Effect of Substance Abuse Treatment Engagement on the Connection Between Support From Program Participants and Substance-Related Recidivism for Justice-Involved Women

Abstract

This study examines the prediction of substance-related technical violations and arrests from (a) a three-dimensional measure of substance abuse treatment engagement—treatment satisfaction, treatment participation, and counselor rapport—and (b) support from peers in the treatment program. The study focuses on 204 women on probation or parole who attended a substance abuse treatment program in the first 9 months of supervision. Data were collected in face-to-face interviews and from official records of violations and arrests. Generalized linear mixed-effects modeling was used to assess the main effects and the interaction effect of within-program peer support and other indicators of engagement as predictors of substance-related technical violations and arrests. Peer support was positively related to violations/arrests when treatment engagement was low. Findings suggest that for women who do not score high in treatment engagement, support from peers is related to increased recidivism, and group treatment may be contraindicated.

Keywords

women in the criminal justice system substance abuse treatment peer support treatment engagement

Introduction

There is a well-established relationship between substance use and crime (Bennett & Holloway, 2009; Bennett, Holloway, & Farrington, 2008; Exum, 2002; Lurigio & Swartz, 1999; Office of National Drug Control Policy, 2013). For example, a high proportion of prison inmates have reported being under the influence of a drug at the time that the offense was committed and/or committing crimes to obtain money for drugs (Mumola & Karberg, 2006). For justice-involved women, substance-dependency is especially common. Women, in comparison with men, report more frequent substance use, abuse of substances which are more detrimental to one’s health, and differing reasons for substance use (Guerino, Harrison, & Sabol, 2011; Harlow, 1999; Langan & Pelissier, 2001; Mumola & Karberg, 2006). Especially for women, negative interpersonal relationships characterized by childhood physical and sexual abuse and abuse from intimate partners are often precursors to women’s substance abuse, which in turn contributes to illegal behavior (Blanchette & Brown, 2006; Cobbina, Huebner, & Berg, 2012; Grella, Stein, & Greenwell, 2005; Harlow, 1999; Kreis, Gillings, Svanberg, & Schwannauer, 2016; Leverentz, 2006). Considering justice-involved women’s high and unique involvement in substance abuse, it is important that their experiences in substance abuse treatment programs and their posttreatment outcomes are considered in research.

In an effort to address justice-involved individuals’ substance abuse problems, judges and probation and parole agents require or advise many women under correctional supervision to attend substance abuse treatment programs. In fact, the criminal justice system is the second largest referral source for treatment admission to state substance abuse treatment agencies, only outnumbered by individual/self-admissions (Smith & Strashny, 2016). This advisement strategy is not misguided. Substance abuse treatment programming has been shown to be effective in reducing the rate at which substance-abusing individuals reoffend and use substances (Dowden & Blanchette, 2002; Gossop, Trakada, Stewart, & Witton, 2005; Griffith, Knight, Joe, & Simpson, 1998; Matheson, Doherty, & Grant, 2011; Pérez, 2009; Prendergast, Podus, Chang, & Urada, 2002; Stanton-Tindall et al., 2007; Strauss & Falkin, 2001; Yang et al., 2013). However, there are aspects of the treatment experience that require further examination. In comparison with the assessment of the effects of treatment attendance on posttreatment outcomes, studies assessing the effects of treatment process variables (e.g., rapport with the counselor in treatment and peer support from other participants) on posttreatment outcomes are limited.

Treatment process research is valuable in identifying the specific features of treatment that explain the effect of substance abuse treatment on continued use and other illegal behavior. Attending treatment programs may increase individuals’ vulnerability to interactions with substance abusing peers who are not committed to abstaining from substance use. This peer aggregation effect has been recognized for interventions with adolescents for some time (Dishion, McCord, & Poulin, 1999) and more recently has been highlighted by scholars who argue against mixing low-risk justice-involved individuals with those at greater risk of reoffending in correctional programs (Lowenkamp & Latessa, 2004). In contrast to the potential for crime-producing processes within group-oriented treatment programs, there is substantial literature that identifies treatment engagement as an important treatment process measure that predicts desired outcomes (Broome, Knight, Hiller, & Simpson, 1996; Griffith et al., 1998; Simpson, Joe, Rowan-Szal, & Greener, 1995). Thus, it is important to examine peer support within substance abuse treatment programs independently from other indicators of treatment engagement. This study therefore tests the main and interaction effects of a composite of three dimensions of treatment engagement (i.e., treatment satisfaction, counselor rapport, and treatment participation) and of peer support from program participants on substance-related technical violations and crimes for a sample of 204 female probationers and parolees.

Literature Review

Substance Abuse Treatment Engagement

Substance abuse treatment engagement is a dynamic process that involves the experiences of program participants and their perceptions of the way that treatment is delivered (McLellan, Chalk, & Bartlett, 2007). Based on a federally funded nine-site study designed to facilitate the use of evidence-based practices with drug-involved individuals who have committed a crime, scholars built on prior work and new research to refine the conceptualization of treatment engagement (Wexler & Fletcher, 2007). In the resulting conceptualization, the dimensions include treatment satisfaction (i.e., access to treatment services and counselors), treatment participation (i.e., psychological engagement and treatment attendance), counselor rapport (i.e., client/counselor relationship), peer support (i.e., supportiveness of other clients), and family support (i.e., people close to you aid the rehabilitative process) (Simpson, 2006; Simpson & Knight, 2004). In this study, we focus on the intra-program dimensions of engagement, though we recognize that family support for treatment is likely to have an independent effect on outcomes.

Research shows that treatment engagement is positively related to treatment completion (Drieschner & Verschuur, 2010; Joe, Simpson, & Broome, 1999; Simpson, Joe, Rowan-Szal, & Greener, 1997) and is negatively related to illegal activities and substance use (Broome et al., 1996; Griffith et al., 1998; Simpson et al., 1995). In addition to the predictive capacity of treatment engagement as a single composite measure, some of the subscales have demonstrated importance in understanding the outcomes of the treatment process. For example, counselor rapport, which in some studies is indicated by the development of a therapeutic alliance between clients and their counselors, is an important predictor of outcomes during and after treatment (Broome et al., 1996; Joe, Simpson, Dansereau, Rowan-Szal, 2001; Simpson & Joe, 2004; Simpson et al., 1997).

Some studies include peer support from other treatment participants as part of a composite measure of treatment engagement (Garner, Knight, Flynn, Morey, & Simpson, 2007; Rowan-Szal, Joe, Simpson, Greener, & Vance, 2009; Simpson, 2006; Simpson & Knight, 2004). In other research, support from other program participants has been treated as a separate indicator of treatment engagement (Yang et al., 2013) or as a component of the social network (Joe, Broome, Rowan-Szal, & Simpson, 2002). This second approach is consistent with the possibility that peers in substance abuse treatment may support either prosocial or antisocial behavior. Suggesting a desired effect, Yang et al. (2013) found a weak negative correlation of peer support with rearrest (–.08). Similarly, Broome and colleagues (1996) found that for probationers, a two-item measure of peer support (“helpfulness of other clients” and “similarity to other clients”) was weakly but significantly related to rearrest. These low correlations may occur because for some study participants, there is a peer aggregation effect. As noted above, this peer aggregation effect has been recognized for interventions with adolescents for some time (Dishion et al., 1999; Dodge, Dishion, & Lansford, 2006), and more recently it has been highlighted by scholars who argue against mixing low-risk offenders with those at greater risk in correctional programs (Lowenkamp & Latessa, 2004). Although negative peer influences have rarely been considered in programs for adults (Barnes et al., 2010; Richards, 2011), it is possible that peer involvement would have undesired influences on adult treatment program participants. There is considerable evidence that indicators of treatment engagement other than peer support had desired effects. Thus, we were interested in the direct effects of engagement and peer support as well as their combined effects. We wanted to know whether peer support in the absence of treatment engagement might lead to negative outcomes, whereas high engagement and peer support might promote positive outcomes.

Research Focus

This study examines the connections of within-treatment experiences with indicators of continued substance use. The analyses tested for the effects of a composite measure of three dimensions of the substance abuse treatment experience—treatment participation, treatment satisfaction and counselor rapport—and a separate measure of peer support within the program on substance-related technical violations and arrests. The following hypotheses were tested:

Hypothesis 1 (H1): Treatment engagement is negatively related to substance-related technical violations and arrests.

Hypothesis 2 (H2): Peer support is negatively related to substance-related technical violations and arrests.

Hypothesis 3 (H3): The association between peer support and substance-related technical violations and arrests is moderated by treatment engagement.

H3a: For individuals with high treatment engagement, peer support is negatively related to substance-related technical violations and arrests.

H3b: For individuals with low treatment engagement, peer support is positively related to substance-related technical violations and arrests.

Method

Data

Data are from a subsample of women who participated in a study of women on probation and parole. For the present analyses, data were from multiple sources, including two in-person interviews with the women, official records of their substance-related technical violations and arrests maintained by probation and parole agents, and police records of criminal history. The longitudinal design allowed for an examination of the relationships between both the engagement of women in substance abuse treatment and their relationship with other program participants in the first 6 months of community supervision and the outcome, the number of substance-related technical violations, and arrests in the first 18 months of supervision. All of these data were quantitative. The university-approved institutional review board (IRB) protocols were followed throughout the study.

Study Sample

A statewide system of probation and parole agents who specialize in the supervision of women with felony convictions allowed for a nested approach to sampling. First, the study principal investigator or a co-principal investigator recruited 73 agents in the 16 Michigan counties within 1½ hr of the research office. These counties included rural, suburban, and small city areas, and the two largest cities in the state (Detroit and Grand Rapids). Other areas of the state were not included due to the expense and time required for travel. The proportion of agents and clients recruited from each county corresponded to the population of each county. A principal investigator met with each agent to review that agent’s caseload, with names omitted, to determine which women were eligible for the study. Probation and parole agents aided in the recruitment process by (a) providing eligible women with project cards and flyers, (b) requesting permission from eligible women to share their contact information with a project interviewer, and (c) with their consent, introducing eligible women to on-site project interviewers. Eligibility criteria for the participants included information that agents had about each of their clients to determine: (a) one or more felony convictions, (b) a history of drug or alcohol involvement, and (c) a supervised period of 2 to 3 months with the same agent. A total of 846 women were eligible for the study. Not all took part, because they reported to the office when research staff was not on site and they neither responded to flyers nor gave agents permission to share contact information. There were no statistically significant differences between participants and nonparticipants in official records of substance use, violations, arrests, misdemeanor convictions, and felony convictions in a 12-month period. Slightly more of the women who did not participate were incarcerated by the end of 12 months, so the sample is somewhat biased to exclude those women.

Interviewers hired and trained for the research project reviewed human subjects’ protocol and protection with the women who did agree to contact, and if they consented in writing to take part in the study (402 of 846 women), scheduled interviews. Consent was explicitly provided to collect data from the Michigan State Police, as well as the Department of Corrections, regarding new arrests and violations of conditions of supervision. In total, 402 women participated in an initial interview for the study. The present analysis includes women who were retained after the initial interview for the 6-month follow-up interview (n = 379, 94.3%) and who responded “yes” when asked, “Since you began this time on probation or parole, did you go to a drug or alcohol program other than AA or NA?” The 379 women retained through the follow-up interview were not statistically different from the 23 who were not retained on several measures, including age, probation versus parole status, having a high school diploma, having children under 18 years residing with them, having full-time employment, subsisting on income less than US$10,000, number of public assistance benefits needed, and scales indicating substance abuse and depression/anxiety. A slightly higher proportion of White than other race women were retained. However, the 379 retained women are racially diverse (48% White, 32.2% Black, 17.9% multiracial or Hispanic, 1.3% unclear, and 0.5% Native American) and ranged from 18 to 60 years of age (M = 33.9, SD = 10.6). Of the 379 retained women, 205 had participated in a substance abuse treatment program, and except for one women, were included in the present investigation of treatment engagement and peer support within the treatment program. One woman refused to answer questions about treatment, so we focus the analyses on the other 204 women.

The 204 women ranged in age from 18 to 60 (M = 34.04, SD = 10.25) years. Most of the sample was White and not Hispanic (57.4%, n = 117), Black and not Hispanic (23.5%, n = 48), or Hispanic or multiracial (18.1%, n = 37). Two women did not provide information about their race/ethnicity. Just over two thirds of women (n = 140, 68.9%) identified between 8 to 11 indicators of substance abuse history on a scale that could range from 0 to 11 indicators (M = 7.75, SD = 2.98, range: 0-11). Many women had multiple prior convictions (M = 5.35, SD = 3.89, range: 1-22). The 204 women were supervised by 64 different agents, and each of these agents supervised from one to eight of the women. Also, 77.9% (n = 159) of the women were on probation and 22.1% were on parole (n = 45). Most of the 204 women (n = 184, 90.2%) indicated that participating in substance abuse treatment was a condition of supervision; the remainder of the women took part in treatment even though it was not a requirement.

Procedure

Between 2011 and 2012, the first interview with each woman took place in private areas of probation and parole offices, public settings (e.g., libraries and restaurants), or the participants’ homes. At that interview, data were collected regarding women’s demographics and substance abuse history. The follow-up interview, when women responded to items measuring program process, took place approximately 6 months after the initial interview. If they attended more than one program, they answered questions about the most helpful treatment experience. Incentives were a US$30 gift card for the first interview and US$75 for the follow-up interview. The interviewer entered information from the study participants into a data-entry program in a laptop computer during the interview. To ensure confidentiality, identifiable data were not entered into the computer during the interviews. Instead, identification numbers were used to match data from the initial and follow-up study. Interview data were later joined to official data on criminal history and recidivism.

Measurement

Dependent variable

Trained research assistants reviewed the probation and parole case records for 18 months after the start of supervision. After demonstrating reliable data entry capabilities (verified with 10 cases), they were responsible for entering counts of substance-related technical violations and arrests in a database for the 18 month period following the start of supervision (M = .74, SD = 1.57, range: 0-14). The probation and parole agents entered the reasons for technical violations and arrests into a database, for example, “drug test positive for cocaine,” “admitted to using marijuana,” and “arrest for retail fraud.” One of the authors coded these reasons as either drug- or alcohol-related (as in the first two examples) or not related to drugs and alcohol (as in the last example). Substance-related technical violations are not new crimes, but are violations of supervision requirements including refusal to participate in a drug screening, positive drug screening tests, or admissions of substance use. Drug-related arrests include possession, manufacturing, and selling drugs or arrests for driving under the influence (DUI). The dependent variable is a count of the number of substance-related technical violations plus arrests. Most women (67.5%, n = 137) had no substance-related technical violations or arrests. Below, we refer to this dependent variable as substance-related recidivism.

Predictor variables

The complete Texas Christian University (TCU) Criminal Justice (CJ) Client Evaluation of Self and Treatment (CEST) is a multidimensional assessment tool designed to measure justice-involved individuals’ needs and performance in substance abuse treatment programs (Texas Christian University Criminal Justice-Client Evaluation of Self and Treatment Assessment Fact Sheet [TCU CJ-CEST AFS], 2005). It includes 14 subscales that reflect four domains (i.e., treatment motivation, psychosocial functioning, therapeutic engagement, and social network; TCU CJ-CEST AFS, 2005). The four therapeutic engagement subscales of the TCU CJ-CEST that were utilized for this study were designed to help researchers understand the successful treatment process for justice-involved individuals (Simpson, Knight, & Dansereau, 2004). Understanding this process was the focus of the present analysis. The four subscales measure therapeutic engagement (i.e., treatment satisfaction, counselor rapport, treatment participation, and support from peers in the program). Data collection from more than 3,000 substance abuse treatment clients who attended 26 corrections-based programs yielded measures of internal consistency for the subscales ranging from .81 to .94 (TCU CJ-CEST AFS, 2005).

In the TCU CJ-CEST assessment tool, treatment participation is a 12-item scale which measures participants’ involvement with treatment and asks questions related to their willingness to talk about their feelings during counseling sessions, the participants’ progress with drug and alcohol problems, and acquiring knowledge during treatment to analyze and plan ways to solve their problems. Example items are “You are willing to talk about your feelings during counseling” and “You give honest feedback during counseling.” Treatment satisfaction is a seven-item scale which measures participants’ perceptions regarding the convenience of the counseling session schedule, the organization and overall functioning of the treatment program, and employee efficiency. Items include “This program is organized and run well” and “You are satisfied with this program.” Counseling rapport is a 12-item scale including questions related to the participants’ trust in their counselors, the counselors’ sensitivity to participants’ problems, and counselors’ helpfulness in assisting the participants in developing self-confidence. Typical items are “Your counselor is easy to talk to” and “Your counselor respects you and your opinions.” Peer Support is a five item-scale including questions related to peers in the treatment program caring about the participant and her problems, being helpful, and sharing similar substance abuse problems, and the participant’s ability to build positive and trusting relationships. Examples include “Other clients in this program are helpful to you” and “There is a sense of family (or community) in this program.” Response options for each item are on a 5-point Likert-type scale ranging from 1 (disagree strongly) to 5 (agree strongly).

In this study, treatment engagement responses were collected during the second interview. The average inter-item correlation among the three variables comprising a composite measure of engagement (counselor rapport, satisfaction, and participation) was .654, and Cronbach’s alpha was .85. Thus, there was strong evidence that the three indicators measured the same underlying construct and a composite measure would be a more reliable measure of treatment engagement than the single measures.¹ For this composite measure, M = 13.77, SD = 1.68, range: 3.08-15.00. This three-dimensional measure of treatment engagement was the sum of the mean values of items that indicated counselor rapport, treatment participation, and treatment satisfaction. Peer support (a = .86) is included as a single scale in the analyses (M = 3.93, SD = 1.03, range: 1.00-5.00). It was created by calculating the mean value for the items.

Control variables

Although the finding is not consistent across studies, some researchers have shown that increased intensity of supervision is positively associated with the numbers of technical violations (Drake & Aos, 2012; MacKenzie & Brame, 2001; Olson & Lurigio, 2000; Petersilia & Turner, 1993). As supervision intensity may account for substance-related recidivism, it is included as a control variable. As was done for the measure of substance-related recidivism, trained research assistants reviewed case records to obtain a count of in-person supervision contacts for the 18 months following the start of supervision (M = 24.35, SD = 13.81, range: 3-72). Another control variable, substance abuse history, was measured with an 11-item Women’s Risk Needs Assessment (WRNA) scale developed to indicate women’s seriousness of substance use in the 6 months prior to the initial interview (Van Voorhis, Bauman, & Brushett, 2013; a = .83). On average, more than seven indicators of prior substance use were reported (M = 7.75, SD = 2.98, range: 0-11). The final control variable, criminal history, is a count of prior arrests before the start of supervision as recorded in official police data (M = 5.35, SD = 3.89, range: 1-22).

Analytic Strategy

Multilevel negative binomial regression was used to predict substance-related recidivism. Necessitating the use of multilevel analysis, the test of an unconditional multilevel negative binomial model indicated significant level-two variance due to women being nested in agents’ caseloads (b = −.796, SE = .209, z = −3.806, p = .000). Negative binomial regression is the appropriate statistical technique because the dependent variable is a count with a high proportion of zero values and a mean (M = .74) lower than its variance (s² = 2.46). The analysis was conducted with the lme4 package accessible through the Comprehensive Archive Network (CRAN) (Bates, Maechler, Bolker, & Walker, 2015). Independent variables included measures of substance abuse treatment engagement and peer support within the program. Control variables included substance abuse history, criminal history, and supervision intensity. The model also included the interaction between the three-dimensional measure of treatment engagement and support from peers in the program. Identification of a significant interaction was followed by simple slopes analysis examining the effects of the moderated variable (support from peers in the program) for high and low scores on the three-dimensional indicator of treatment engagement, defined as ±1SD from the mean. For the multivariate analysis, the variance inflation factors (VIFs) are all below 1.4, which is considerably lower than the recommended critical level of 4.0 (Fisher & Mason, 1981). Robust standard errors were used for all Wald tests of the significance of estimated coefficients. For the multivariate analysis, all continuous variables were grand-mean centered to avoid problems with multicollinearity (Aiken & West, 1991).

Results

Correlations and Descriptive Statistics

Table 1 presents the correlations for the study variables. Some of the correlations between study variables were statistically significant. A positive and moderate correlation was observed between the three-dimensional measure of substance abuse treatment engagement and peer support. Similarly, there was a positive and moderate correlation between supervision intensity and substance-related recidivism. Finally, there was a positive and weak correlation between criminal history and substance abuse history. Notably, the measures of treatment engagement and of peer support were not significantly related to substance-related recidivism.

Table 1.

Correlations for the Study Variables.

	Treatment engagement	Peer support	Substance history	Criminal history	Supervision intensity
Treatment engagement
Peer support	.503*
Substance history	−.114	.074
Criminal history	−.119	−.011	.188*
Supervision intensity	−.017	−.015	.062	.076
Substance-related recidivism	.004	.100	.133	.063	.419*

p < .01.

Prediction of Substance-Related Recidivism

Table 2 displays the estimated coefficients, robust standard errors, and incident ratio rates (also referred to as exponentiated coefficients) for an analysis predicting the number of substance-related recidivism incidents from the control and substance abuse treatment process variables. There were no significant main effects for the three-dimensional measure of substance abuse treatment engagement or peer support predicting substance-related recidivism (H1 and H2). However, there was a statistically significant interaction effect between the two treatment process variables (see Figure 1 and Note 1). The simple slopes analysis revealed that when the three-dimensional indicator of substance abuse treatment engagement is high (i.e., one standard deviation above the mean), peer support is not significantly associated with substance-related recidivism (b = −.127, SE = .229, z = −0.578, p = .578, incidence rate ratio [IRR] = 0.881; H3). But, when the three-dimensional measure of substance abuse treatment engagement is low (i.e., one standard deviation below the mean), peer support is significantly positively associated with substance-related recidivism (b = .663, SE = .239, z = 2.769, p = .006, IRR = 1.940) (see Note 2).

Table 2.

Negative Binomial Generalized Linear Mixed-Effects Model of Treatment Process Variables on Substance-Related Recidivism.

	Coefficient	SE	IRR
Intercept	−.728	.173	0.483**
Substance abuse treatment peer support	.268	.143	1.307
Substance abuse history	.046	.048	1.047
Criminal history	.030	.030	1.031
Supervision intensity	.055	.009	1.056**
Substance abuse treatment engagement	−.051	.093	0.950
Substance abuse treatment engagement × Substance abuse treatment peer support	−.234	.110	0.791*
Log-likelihood	−204.2
Dispersion^a	1.212
Residual deviance^b	408.5
df	195

Note. IRR = incidence rate ratio.

Negative binomial regression dispersion parameter.

Chi-square statistics for the residual deviance goodness-of-fit test.

p < .05. **p < .001.

Figure 1.

Plot of the interaction between treatment engagement and peer support on substance-related recidivism where low and high are defined as ± 1 SD from the mean.

The IRR, or exponentiated coefficient, for peer support indicates that a one-unit increase in the score for peer support is related to a 94% increase in the odds for an instance of substance-related recidivism, when the three-dimensional measure of treatment engagement is low and the control variables are held constant. Note that if we look at the effects of engagement for high and low peer support, what we find is that when peer support is low, the effect of engagement is positive but not statistically significant (b = .191, p = .202), but when peer support is high, the effect of engagement is negative and statistically significant (b = −.293, p = .042).

Supervision intensity, the only statistically significant control variable, is positively related to supervision-related recidivism (b = .055, SE = .009, z = 5.943, p < .000, IRR = 1.056). Ten additional contacts with a supervising agent is associated with 56% increased odds for substance-related recidivism. This finding could be the result of increased detection for those in contact with agents more frequently or more crime-involved women being supervised more intensely.

Discussion

The purpose of this study was to examine two key aspects of the substance abuse treatment process (i.e., treatment engagement and peer support) for a sample of justice-involved women. Treatment process research has the potential to identify specific areas of a treatment experience that are problematic and to suggest actionable solutions (McLellan et al., 2007). Prevention and health promotion programs are often assumed to be helpful or to have no significant effect on the target population, and to rarely or never produce negative effects (Werch & Owen, 2002). However, unanticipated adverse treatment effects have historically plagued various criminal justice intervention strategies (Braga, 2016; Welsh & Rocque, 2014; Werch & Owen, 2002). For example, Braga (2016) highlighted the negative pre-1970 and the mixed contemporary effects of gang street worker programs. Instead of disrupting gang violence, gang intervention programs were associated with increased gang violence.

This study raises similar concerns about possible negative effects of substance abuse treatment for some justice-involved women. We found no significant association between either treatment engagement (H1) or peer support (H2) and recidivism. However, consistent with H3, the association between peer support and substance-related recidivism was moderated by the three-dimensional measure of treatment engagement. When the three-dimensional indicator of treatment engagement was low, the perception of peer support during the treatment process was positively related to increased odds for substance-related recidivism. These findings point to the complexity of the connection between treatment process variables and treatment outcomes. Building positive relationships with other treatment group members could have unintended negative consequences.

Prior research has reported significant connections between treatment engagement, peer support, and desirable treatment outcomes (Broome et al., 1996; Griffith et al., 1998; Simpson et al., 1995). This was not true for the current research which focuses exclusively on justice-involved women, most of whom were required to attend treatment. These findings suggest the importance of anticipating the conditions under which substance abuse treatment is best suited to fit the needs of women. Specifically, for those who are disengaged in the treatment experience, developing strong peer relations may increase the risk of continued substance use. It is also possible that the mandatory nature of substance abuse treatment for many of the women created a mix of highly and weakly motivated women in the treatment setting, which led some women to be especially affected by peer influences that promoted increased lawbreaking.

Limitations and Future Research

Despite the longitudinal research design, the availability of four highly reliable TCU CJ-CEST measures that are key elements of the treatment process (Simpson & Joe, 2004), and the unique examination of the interaction effects of the treatment engagement and peer support from other program participants, there are some limitations of the present study: (1) data collection occurred in a single state and may not generalize to other regions. (2) Because information on the quality of programming (i.e., treatment modality, intensity, and length of stay) and more exhaustive treatment process measures (e.g., treatment motivation, psychosocial functioning, and social networks; Simpson, 2004; Simpson et al., 2004) are not available, findings are suggestive, but they do require replication in research that includes these measures. (3) Treatment engagement data are self-report and information on treatment quality and dose are not available, thus results should be interpreted with caution. (4) The treatment process measure of social support from peers outside of the treatment program is omitted, and it has been shown to be a significant predictor of posttreatment outcomes (Broome, Simpson, & Joe, 2002; Griffith et al., 1998; Knight & Simpson, 1996; Simpson, Joe, Greener, Rowan-Szal, 2000). (5) Only quantitative data are considered in the present analysis. Qualitative research would be a useful supplement for documenting the experiences of women who do not engage in the treatment program and who are negatively affected by peers. More specifically, qualitative research could shed light on whether peer contagion occurs for those women, or some other mechanism explains how when there is no treatment engagement, peer support within the program is connected to recidivism. (6) Because women were asked about the most helpful program they attended, for women who attended more than one program, results cannot be generalized to women in programs that they viewed as less helpful than others they attended. Regarding this sixth limitation, future research should ask women to identify the programs they have taken part in, and if they participated in multiple programs, should either randomly select the one to be reported on or should ask questions about each program.

In addition, the treatment process measures were taken 9 months after the start of supervision, and treatment may not have ended for all women. Replication of findings with a design that provides an assessment of treatment process at the time individuals leave a substance abuse treatment program and then follows them for a period of time to measure recidivism would provide a stronger design. Collecting data on the treatment experience at multiple time points, and including qualitative data, could also inform how treatment engagement and peer support changes throughout the treatment process. Finally, the focus on women on probation and parole filled a gap in the research literature. At the same time, it limits the generalizability of findings, in part because most of the women were required to attend treatment. However, research on justice-involved women’s substance abuse treatment experiences is limited. A growing body of research has identified the underlying experiences that commonly precede substance use (i.e., physical and sexual abuse) for women, but offers limited information on the recovery process for the substance-involved population. Replication of this study with diverse samples will be important for clarifying the role of treatment engagement and peer support within community-, prison-, and jail-based programs for justice-involved women, and for men. Furthermore, researchers should consider testing the effects of mandated substance abuse treatment, in comparison with treatment that is not mandated.

Implications for Research and Practice

Findings from the study have two key implications for practice. First, the finding that peer support positively predicted substance-related recidivism when treatment engagement was low suggests that not only is the direct effect of treatment engagement important to substance abuse treatment outcomes, but the combined effect of low treatment engagement with high support from program peers can have deleterious effects. Program staff should be aware of this possibility and should develop interventions that reduce this negative effect. Treatment preparation programs have been shown to increase treatment engagement (McMurran & Ward, 2010). Our finding suggests that such programs might be even more effective if they address the potential for peer relationships and related support to have either positive or negative effects on recovery, and the strategies of treatment engagement that can reduce negative effects. One example of a program that aims to ensure treatment engagement is the Treatment Readiness and Induction Program (TRIP; Knight et al., 2016). TRIP is an 8-week induction tool designed to improve cognitive and treatment engagement indicators for a population of crime-involved adolescents in a residential substance use treatment setting. Specifically, participants were engaged in interactive modules and tasks that strengthened problem recognition skills and thoughtful decision-making. In comparison with participants who received standard operating practices (SOPs) at the treatment facility, participants receiving SOP and TRIP reported better problem recognition, decision-making, and treatment engagement (Knight et al., 2016). The technique of motivational interviewing, which has increasingly been used in correctional settings, would be another approach to stimulating treatment engagement (Armstrong, Atkin-Plunk, & Gartner, 2016; Carroll et al., 2006). Motivational interviewing increases motivations to change behaviors that harm health or lead to other negative outcomes.

The second implication for practice pertains to peer interactions during the substance abuse treatment experience. It is common for therapeutic programs to engage participants in communities which allow for interactions among clients. However, considering the potential negative effects of peer support, a strategic pairing of clients has the potential to promote positive treatment outcomes. One approach could be to pair early stage participants with successful late-stage participants. Sowards, O’Boyle, and Weissman’s (2006) research on justice-involved women in a mandated treatment setting suggested that such pairing could foster treatment engagement and hope that lead to positive treatment outcomes among early stage participants, and it could avoid any negative influences of peers in the program.

In regard to research implications, the authors encourage scholars to be mindful of the internal consistency of the subscales comprising treatment engagement as a single measure. Specifically, the measure of peer support needs to be disentangled from measures of treatment engagement. Failure to independently assess dimensions of treatment engagement could result in missed opportunities to understand how specific aspects of the treatment experience independently affect or moderate outcomes. Furthermore, future research on peer support in substance abuse treatment settings could further clarify the nature of peer interactions that conflict with substance abuse treatment goals. It would be useful to measure not only perceived support from peers but also the peers’ attitudes toward treatment and continued substance use, as these additional factors may affect the influence of peer support on substance abuse treatment outcomes.

Conclusion

The current research provides a unique contribution to the study of substance abuse treatment measures and posttreatment outcomes for women in community-based substance abuse treatment programs. Contradicting prior research, the main effects of substance abuse treatment engagement did not yield statistically significant reductions in substance-related recidivism. Instead, the key finding highlights the risk of undesired effects of perceived positive support from peers on recidivism for women who are not engaged in the substance abuse treatment program.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research for this article was supported by Grant No. 1126162 from the National Science Foundation and by the Michigan State University Foundation.

ORCID iD

Marva V. Goodson

Notes

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