Prison Addiction Program and the Role of Integrative Treatment and Program Completion on Recidivism

Abstract

This study examines whether there is variability between the effects of three different drug rehabilitation programs operating in the Israeli Prison Service (IPS) on completers’ recidivism. By performing comparative analysis, this study attempts to address the problem of assessing the role of participants’ motivation. The study uses a rich administrative data obtained from the IPS system to develop a propensity score matching (PSM) approach where the treatment groups consist of only those who completed the programs, and the comparison groups consist of drug-addicted prisoners who have not taken part in any drug rehabilitation program. After matching, prisoners in the treatment and comparison groups are found to be similar on all known characteristics. Findings show that the only rehabilitation program that promised significant and positive outcomes for its completers was the more comprehensive one operating at Hermon Prison. Prisoners who completed the treatment were incarcerated and arrested less than their comparison group. The “golden strategy” for rehabilitating drug-using prisoners, then, will be twofold. The program should be based on the promising components of rehabilitation, that is, cognitive behavioral therapy, therapeutic community, long duration, intensity, and positive social climate. The program should also succeed in retaining its participants through completion.

Keywords

drug rehabilitation programs recidivism Israeli Prison Service completers propensity score matching

Introduction

Addiction to drugs is known to have a range of serious adverse medical consequences (Bouchery, Harwood, Sacks, Simon, & Brewer, 2011; Chandler, Fletcher, & Volkow, 2009). Moreover, people who are addicted to drugs tend to suffer from behavioral and psychological problems (Grant et al., 2004; Murdoch & Ross, 1990). In addition to public health concerns, there is also a strong correlation between addiction and criminality, as addicted individuals are overrepresented as offenders and as inmates in prisons, primarily in drug-related crimes or by committing offenses while under the influence of drugs (Inciardi, Martin, & Butzin, 2004; Wexler, Falkin, & Lipton, 1990).

With drug abuse being so closely linked to crime, it does not come as a surprise that such a large proportion of the prison population in the world suffers from addiction (Hiller, Knight, & Simpson, 1999; Mitchell, Wilson, & MacKenzie, 2012; Pernanen, Cousineau, Brochu, & Sun, 2002). Assessments in the United States, based on official criminal records, show that more than half of state prisoners are drug-dependent (Bronson, Stroop, Zimmer, & Berzofsky, 2017). Crime and recidivism rates among drug addicts along with high detainment and incarceration costs and overcrowded conditions in U.S. prisons raised the need to reassess and formulate new strategies for dealing with addicts (Prendergast & Wexler, 2004).

As a result, many incarceration facilities turned to therapeutic approaches to deal with prisoners who suffer from addiction (Turley, Thornton, Johnson, & Azzolino, 2004). The goal of most addiction programs is to provide the prisoner with decision-making skills and pro-social values and the ability to cope with pressure, triggers, and stigmatization and to increase the sense of personal development and motivation to participate in therapy (Chandler et al., 2009; Wexler, Falkin, Lipton, & Rosenblum, 1992). Besides, the programs seek to reduce the relapse of prisoners into drug use and lessen the likelihood of recidivism (Mitchell, Wilson, Eggers, & MacKenzie, 2012; Mitchell, Wilson, & MacKenzie, 2007).

Due to limited success that has been found regarding the effectiveness of drug rehabilitation programs, an attempt was made to identify the key factors that may help in reducing, even in a moderate way, the rates of recidivism among treated prisoners. One of the most prominent elements mentioned in the literature in this context is the type of treatment given, including the program features and characteristics. To date, the therapeutic framework that is considered the most promising includes a combination of strong therapeutic components (especially cognitive behavioral therapy), functioning as a therapeutic community, and a positive social climate (Bahr, Masters, & Taylor, 2012; Chandler et al., 2009; Mitchell et al., 2012; Ross, Diamond, Liebling, & Saylor, 2008). For example, Mitchell and his colleagues (Mitchell, Wilson, Eggers, & MacKenzie, 2012) found in their meta-analysis that prisoners who participated in programs combining group counseling and support were less likely to recidivate. Furthermore, three systematic reviews found that therapeutic communities are effective interventions for reducing recidivism and drug use among prisoners (Aslan, 2018; De Andrade, Ritchie, Rowlands, Mann, & Hides, 2018; Magor-Blatch, Bhullar, Thomson, & Thorsteinsson, 2014).

Another element that the literature considers a key to success is completion of the treatment (Brorson, Arnevik, Rand-Hendriksen, & Duckert, 2013; Dalsbø et al., 2010). This element is of special relevancy in drug rehabilitation programs because they are characterized by high attrition rates (Evans, Li, & Hser, 2009; Gerstein & Lewin, 1990; Henggeler, Pickrel, Brondino, & Crouch, 1996).

A recent study published in Israel (Hasisi, Weisburd, Shoham, Haviv, & Zelig, 2018)¹ examined the three main drug rehabilitation programs operating in the Israeli Prison Service (IPS) using a propensity score matching (PSM) method.² The programs that were evaluated differ in terms of length, intensity, resources, and prison climate. The study used the more rigorous “intention to treat” approach, that is, including all participants who began the program. It found no statistically significant findings between treatment and comparison groups in all programs examined in the matter of recidivism rates.

The current study raises the opportunity of examining the effects of each of the three mentioned Israeli programs (Hasisi et al., 2018) when considering only the participants who completed the program (i.e., excluding the dropouts). In other words, the purpose of this analysis is to examine whether there is variability between the effects of different programs (which are distinguished by the therapeutic components they include) on completers regarding recidivism. To do so, we used a PSM approach where the treatment groups consist of only those who completed the programs, and the comparison groups consist of drug-addicted prisoners who have not taken part in any drug rehabilitation program.

Drug Rehabilitation Programs in Prisons—Do They Work?

Since the mid-1980s, many Western institutions have adopted rehabilitation- and recovery-based methods for drug addicts (Turley et al., 2004). The prison system provides an opportunity for the addicted prisoner to recover, having much less access to substances and much more time to focus on treatment and introspection inside prison walls. Therefore, in most of today’s Western detention centers, different types of drug rehabilitation programs, in a variety of forms, play a vital and integral role in prisons (Bahr et al., 2012; Mitchell et al., 2012).

The goal of these programs is to provide the prisoner with decision-making skills, pro-social values, and the ability to cope with pressure, triggers, and stigmatization and increase the sense of personal development and motivation to participate in therapy (Chandler et al., 2009; Wexler et al., 1990). The programs seek to reduce prisoners’ relapse into drugs and lessen the likelihood of recidivism (Mitchell et al., 2007; Mitchell et al., 2012)

Recidivism, measured by repeated arrests or incarceration, is the most popular measure to examine program effectiveness (Mitchell et al., 2012; Turley et al., 2004). In this regard, a wide body of literature deals with the question of what works for addicted prisoner rehabilitation, trying to understand the main key components of a successful program.

For example, a meta-analysis based on 74 studies (Mitchell et al., 2012) examined the effectiveness of prison drug rehabilitation programs in reducing recidivism. The study indicated that, beyond mere involvement in a program, the type of rehabilitation program plays a major role in reducing recidivism among addicted prisoners. Therapeutic community programs and programs combining group counseling and support (e.g., 12-step, Alcoholics Anonymous/Narcotics Anonymous [AA/NA], and drug education programs in a communal context) were found to have a moderate positive effect. Specifically, prisoners who participated in programs operating in a therapeutic community setting or programs based on counseling and support were found to be less likely to recidivate (about 17% reduction in recidivism). All other types of programs were found to have mixed findings or no positive effect.

Three recent systematic reviews confirmed the effectiveness of therapeutic communities in reducing recidivism and drug relapse (Aslan, 2018; De Andrade et al., 2018; Magor-Blatch et al., 2014).

Although some studies found evidence of promise, especially in community-based therapy programs (Hiller et al., 1999; Martin, Butzin, & Inciardi, 1995; Martin, Butzin, Saum, & Inciardi, 1999; Wexler et al., 1990) and in programs based on cognitive behavioral therapy (Bahr et al., 2012; Dutra et al., 2008), according to researchers, insufficient studies have analyzed drug rehabilitation programs in the prison setting, and further examinations are needed to consider them promising. Moreover, most of the studies evaluating these programs suffer from methodological difficulties and poor research quality, threatening the validity of the findings (Pearson & Lipton, 1999).

Furthermore, as known from the literature, released offenders with drug abuse problems face challenges and difficulties upon reentry to society, such as housing, employment, and education. Due to these challenges, an essential component for their rehabilitation is a continuum of treatment after their release from prison (Chandler et al., 2009; Farabee et al., 1999; Fletcher & Chandler, 2006; Inciardi et al., 2004; Knight, Simpson, & Hiller, 1999). Unfortunately, “the connection between rehabilitation efforts in prison and the process of integration into society after release is probably one of the most feeble links in the criminal justice system” (Inciardi et al., 2004, p. 91).

Which Components Improve Success in Rehabilitation Programs?

Thus far, the attempt to understand how prison rehabilitation programs help reduce the rates of crime and recidivism has shown only limited success. If so, it is necessary to understand key components that increase the chances of a drug rehabilitation program being effective and leading to a reduction in recidivism rates among addicted prisoners (Mitchell et al., 2012). We will now elaborate on two main elements that might reduce recidivism among treated addicted prisoners: (a) the role of program completion and (b) the nature of the program itself (community-based therapeutic programs, cognitive behavioral therapy, and the prison climate).

Role of Program Completion

Studies show that treated patients in drug rehabilitation programs tend to drop out at particularly high rates, as high as 80% (Dalsbø et al., 2010; Evans et al., 2009; Gerstein & Lewin, 1990; Henggeler et al., 1996). Several studies have found that dropping out from a therapeutic program can lead to negative consequences for the patient who did not complete the program and can sometimes even worsen his condition. This deterioration can be expressed by the risk of relapse, legal aspects, financial aspects, and health (Alterman, McKay, Mulvaney, & McLellan, 1996; Brewer, Catalano, Haggerty, Gainey, & Fleming, 1998).

Furthermore, it has been found that the length of time the patient stays in therapy is essential to success, especially when it comes to drug users (Simpson, 1981). It appears that effective treatment lasts at least 90 days and that graduates have higher success rates than nongraduates from the program (Fletcher & Chandler, 2006; Gerstein & Lewin, 1990; Wexler et al., 1992). In this regard, many studies show that the most consistent factor in predicting the effectiveness of drug rehabilitation programs is treatment completion (Brorson et al., 2013; Dalsbø et al., 2010). Patients who complete the therapeutic program are characterized by lower crime rates and fewer relapses to drug use (Prendergast, Hall, Wexler, Melnick, & Cao, 2004; Wexler, Melnick, & Cao, 2004).

However, the problem of sampling bias that might occur in quasi-experimental studies, in which only the most motivated prisoners enter the treatment program, is aggravated when considering only the completers of the program. In this matter, the evaluations that compare treated patients who completed the treatment program with a control group could be even more “contaminated” by the “creaming effect,” which characterizes quasi-experimental studies. This is because “it is difficult to know whether the lower drug use (or in our case, recidivism) of the treatment group is due to treatment (or in our case, treatment completion) or to pretreatment characteristics such as motivation” (Bahr et al., 2012, p. 156).

For ethical and operational reasons, there is a lack of evaluations examining the effectiveness of drug rehabilitation programs relying on double-blind experimental research that could minimize bias (Boyum & Kleiman, 2002). Although the current article is also subject to this type of bias (as a quasi-experiment), using an alternative approach, it tries to address the acute problem of selection bias regarding motivated prisoners. This is done by simultaneously examining the completers from three drug rehabilitation programs. Assuming that the completers of the various programs have a relatively high level of motivation—at least compared with those who started the program but dropped out and those who never joined—this assessment may help to understand the interaction between the type of program being offered and the completion of a program and its effect on recidivism.

Nature of the Treatment: An Integrative Approach

One explanation for the modest results in prison addiction programs could be the mono-dimensional feature of the most common treatment programs, whereas the common addicted offender needs integrative and diverse supportive treatment within the program, as in the case of domestic violence offenders (Hasisi, Shoham, Weisburd, Haviv, & Zelig, 2016). Day, Chung, O’leary, and Carson (2009) argued that integrating and combining several successful approaches increases the chances of program success. When trying to rehabilitate addicted prisoners, as in the case of tobacco cessation (Howerter, Floden, Matthews, & Muramoto, 2016), the integrated approach, in our view, should combine the main components that had a positive effect in the literature, including a therapeutic community, cognitive behavioral therapy, and positive prison climate.

Community-Based Therapeutic Programs

As noted, the most promising treatment in reducing recidivism rates among addicted prisoners is a therapeutic community (Mitchell et al., 2007; Mitchell et al., 2012). The therapeutic community model varies between programs, but there are several core elements: most of them are long-term (between 15 and 24 months; Gerstein & Lewin, 1990; Melnick & De Leon, 1999), intense, and share a treatment philosophy attributing drug addiction to personality disorders, therefore focusing on disorders beyond addiction (De Leon, 1984; Uchtenhagen & Zimmer-Höfler, 1987).

As part of community therapy and rehabilitation attempts, one of the goals is developing the ability for “right living.” Right living is a commitment to values of a therapeutic community, including positive social values, such as work ethic, social productivity, and community responsibility, as well as positive personal values, such as honesty, responsibility, self-discipline, and responsibility toward significant others (Pearson & Lipton, 1999). As a result, therapeutic communities often combine strong elements of treatment within the framework, including group therapy and individual meetings. In this framework, veteran patients sometimes serve as role models for new patients. Hierarchical stages distinguish between patients according to their progress, thus granting them authority in the group (De Leon & Wexler, 2009; Dye, Ducharme, Johnson, Knudsen, & Roman, 2009). In this regard, the patients themselves can lead the treatment sessions and informally supervise their group members, while they help the group with following the program guidelines and maintaining the treatment unit. Community therapy provides patients with a structured environment, which emphasizes personal development, empowerment, and a sense of responsibility.

Although many researchers have found that the therapeutic community method is effective in rehabilitating addicted prisoners (Hiller et al., 1999; Inciardi et al., 2004; Mitchell et al., 2012), it is important to emphasize that applying community care elements in a prison (an intense and total institution) suffers from many problems impairing treatment effectiveness (Farabee, Prendergast, & Anglin, 1998).

Cognitive Behavioral Therapy

Cognitive behavioral therapy belongs to a group of intervention programs that share the assumption that mental disorders and abnormal behaviors result from cognitive factors and thinking distortions (Butler, Chapman, Forman, & Beck, 2006). This philosophy argues that irrational thinking patterns cause emotional distress and in turn cause behavioral problems. Such patterns of thinking include distorted beliefs about the environment, oneself, society, and the future. The cognitive behavioral therapy method proposes to intervene against such distorted thinking patterns with an intervention that is expected to reduce the emotional distress and behavioral problems from which patients suffer. In the context of addiction, cognitive behavioral therapy aims to correct thinking distortions when the emphasis is placed on strengthening self-efficacy and motivation for drug rehabilitation, increasing the ability to cope with frustrations and eliminating excessive expectations regarding the negative effects of abstinence from drugs. Thus, cognitive behavioral therapy seeks to change the cognitive process of the addicted patients, their feelings and, finally, the way they react (Moos, 2007; Morgenstern & Longabaugh, 2000).

Prison Climate and Rehabilitation Approach

Although prison is an opportunity to treat addicted prisoners, one of the main criticisms in this context is that the prison environment is not ideal for rehabilitation and that therapists face many difficulties in this framework (Toch, 1977; Zellerer, 2003). The prison climate is a concept that refers to the social, emotional, organizational, and physical characteristics of a corrective institution. Studies suggest that the prison climate has a significant influence on recidivism and on the ability to rehabilitate prisoners (Ross et al., 2008).

Liebling and Arnold (2004) identified some features that might contribute to a more positive prison climate and help to create a supportive environment for rehabilitation. Such features include staff/prisoner relations, the level of trust, the degree of support, the humanity of the regime, the perceived fairness, decency, and respect shown to prisoners, the prisoner’s social life, the extent of family contact, the level of well-being, opportunities for personal development, the degree of order, and the meaning attached to the penal experience.

Drug Programs Within the IPS

According to a survey conducted by the IPS, 1,859 prisoners are considered addicts, constituting 36.2% of total prisoners, and another 805 are considered drug consumers, which is 15.6% of all prisoners (Walk, Ben Zvi, Spivak, & Cohn, 2013). Every drug addict has the right to begin treatment. Prisoners diagnosed as drug users and who show motivation are referred to the rehabilitation and treatment centers of the IPS. The IPS operates three relevant drug rehabilitation frameworks. Hermon Prison, a national rehabilitation and recovery center, is considered the most intensive drug rehabilitation program in the IPS. In addition, special departments are operating in different prisons: Magash (Hebrew abbreviation for “Recovery and Rehabilitation Centers” [RRC]) and Lev Room (Lev, Hebrew for “heart,” which is also an abbreviation for “Rehab in Prison”), within nonassigned departments. These frameworks share similar elements of psychological and rehabilitative treatment but differ in intensity, duration, allocation of resources, and the prison climate in which they operate. Hermon Prison and RRCs are longer (between 9 and 12 months), whereas the Lev Room program lasts 4 to 6 months. Due to the differences in program duration, a prisoner who wishes to join the Hermon or RRC program must have at least 1 year remaining on his or her sentence, whereas a prisoner who wishes to join the Lev Room program must have at least 5 months remaining. All other admission criteria for the three programs are almost identical.

Treatment programs for addicts in Hermon Prison

Hermon Prison was established in 1998 in Northern Israel and is named after its former commissioner, Dr. Zvi Hermon. Hermon Prison has a clear therapeutic orientation and is considered the drug rehabilitation center of the IPS (Santo & Rahav, 2008). Hermon Prison houses three drug rehabilitation departments, each with about 40 patients (as defined by the staff of the program as part of their orientation), operating a therapeutic community framework (Hasisi et al., 2018). As part of the comprehensive programs, prisoners participate in therapeutic groups led by social workers or rehabilitation counselors and in NA/AA groups and other self-help groups, and they are integrated into education or employment and undergo the 12-step program.

The prison, designed by architect Shmuel Shiloh, is in a natural environment amid a rural, mountainous Mediterranean landscape. It is full of lawns and gardens cultivated by the prisoners and is built in the form of a campus. It is not surrounded by walls and towers characteristic of medium-security prisons (IPS website, 2015). All these conditions play a vital role. The cells, called rooms, accommodate one or a maximum of two detainees (tenants) and facilitate a sense of personal space to ease rehabilitation (Hasisi et al., 2016).³

Treatment programs for addicted prisoners: RRC

The RRC is a treatment framework for addicted prisoners usually detained in high-security centers. Today, such programs operate at Dekel Prison, Zalmon Prison, Ayalon Prison (since 2015), and Hasharon Prison (for protective custody). These departments are called “drug-free” and operate according to therapeutic community principles. The departments include 40 prisoners living in double rooms or in rooms of four (varies between centers). The duration of the treatment, like the program running in Hermon, is about 9 months. The RRCs also maintain a busy schedule and include early wake-ups, employment or study, treatment groups, anger management workshops, and individual meetings with social workers.⁴ Although the intensity and duration of the RRC program are about the same as in the program running in Hermon, it lacks the positive social climate and environment that characterizes Hermon Prison.

The drug rehabilitation program for addicted prisoners at Lev Room

This project, implemented in various high-security prisons, houses prisoners in one or several rooms in drug-free wings within regular departments to receive rehabilitation and recovery treatment. The program is intended for short-term imprisonments, for prisoners who, due to their short-term sentence, cannot take part in extensive programs, such as the program in Hermon or the RRCs. One of the main goals of the program is to have the prisoners acquire awareness of the need for drug education with the help of rehabilitated prisoners who have “been there” (Nathan, 2011). It should be noted that no special resources or staff are allocated to these programs, and they operate as part of the general department.

In summary, the three rehabilitation programs running in the IPS could be ranked by how well their characteristics align with the literature of what works. The program that includes the most promising features is the program operating in Hermon Prison and is therefore ranked first. The Magash program can be ranked second because it consists of promising therapeutic components and has the same duration. However, it lacks the positive climate and atmosphere that exists in Hermon Prison. The Lev Room program is considered the weakest program out of the three, as it is a short-term program and lacks a positive climate.

The Study

A previous study has examined the effectiveness of the three mentioned drug rehabilitation programs running in the IPS and found no evidence of success in reducing recidivism rates. The current study aims to evaluate the effectiveness of the three drug rehabilitation programs operating in the IPS previously described while examining only completers of the programs, ignoring those patients who began the program without completion. Although the study examines only completers of the programs, which might lead to the “creaming effect,” examining the completers of multiple programs operating in the IPS can give us more knowledge regarding the influence of the interaction between the type of the program and completion of the program on recidivism.

Considering the high dropout rates from drug rehabilitation programs (Evans et al., 2009; Gerstein & Lewin, 1990; Henggeler et al., 1996), this analysis is crucial for two reasons. First, it may indicate whether completion of prisoners within a given program has a positive effect on recidivism (Ball, Carroll, Canning-Ball, & Rounsaville, 2006; Cahill, Adinoff, Hosig, Muller, & Pulliam, 2003; Simpson & Joe, 1993). Second, as the evaluation is being conducted on three different types of programs, the analyses might give us more knowledge regarding the effect of the interaction between the key characteristics of a program and the completion of the program on recidivism. In other words, this evaluation examines whether the effect on program completers regarding recidivism varies between different types of drug rehabilitation programs. The hypothesis is that the program will be more effective for those who complete it, if the program is comprehensive and of sufficient length, provides integrated therapy, and takes place in a positive prison climate.

In the current study, high dropout rates were observed in each of the three examined programs, as follows: 34.8% completed the Hermon Prison drug rehabilitation program (65.2% dropout rate), 42% completed the RRC program (58% dropout rate), and only 15.3% completed the Lev Room program (85% dropout rate).

Research Method

Our research was based on a data file containing the records of all criminal prisoners released from IPS facilities in the years 2004 to 2012, which comprises 61,824 prisoners. It is important to note that information regarding recidivism for these prisoners is updated only to July 2015. The file includes extensive information obtained from the IPS data system (Tzohar), such as the sociodemographic characteristics of the prisoners and previous and current imprisonments.

The main challenge of quasi-experimental research lies in the ability to match a proper comparison group to the intervention group. Matching a comparison group can be divided into two stages. First, prisoners who do not meet admission requirements to the various programs and prisoners who have been treated in other rehabilitation programs are filtered from the file. The filtered file now consists of individuals who would otherwise be eligible for treatment but did not receive treatment. This includes prisoners who did not choose to take part in the programs or prisoners who the IPS excluded due to security reasons or due to infirmity. Potential issues with selection bias might arise and these issues are addressed later in the discussion. Then, using the PSM method, each prisoner from the intervention group is matched to a “twin” from the filtered comparison group, who is similar to the treated prisoner in different aspects yet did not undergo the examined treatment program.

Step 1: Initial Screening of Comparison Groups

To evaluate the drug rehabilitation programs, we conducted two screening processes. First, 46,727 prisoners with no indication of being addicted to drugs or alcohol and without having received any treatment were excluded from the general prison file. After screening, 15,097 prisoners remained in the file, of whom 1,287 of participated in the drug rehabilitation program at Hermon Prison, 600 participated in the RRC program, and 1,218 participated in the Lev Room program.

Because of differences in remaining sentencing time, the second screening process served to omit prisoners who did not have enough time to serve to be given a place in a treatment program. Therefore, to evaluate the drug rehabilitation program at Hermon Prison and the RRC programs, the prisoners with less than 9 months to serve were omitted from the comparison group. Moreover, 5,488 prisoners remained in the comparison group after omission. In the case of the Lev Room program, prisoners with less than 5 months to serve were removed from the comparison group, while 7,172 prisoners remained after filtering. In addition to this screening, in line with our research question, we omitted all prisoners who did not complete the treatment programs from the treatment groups. We narrowed the sample to 448 out of 1,287 who completed the Hermon drug rehabilitation program, 252 out of 600 who completed the RRC program, and 186 out of 1,218 who completed the Lev Room program.

Matching of Comparison Groups Using PSM

After the initial screening of comparison groups, we now turned to a suitable comparison group for prisoners who participated in drug rehabilitation programs. We chose to use PSM, which is borrowed from the medical field where it was conducted by P. R. Rosenbaum and Rubin (1983). This quasi-experimental method is very suitable for analyzing retrospective data and is based on the use of logistic regression, where the dependent variable is exposure or the lack of exposure to treatment (Austin, 2008).⁵ The method is intended to minimize bias in the selection process, so that subjects in the comparison group will be as similar as possible to the participants (except for the fact of being in the intervention group; Austin, 2008; Jordan, 2012).

The first step in calculating the propensity score of each prisoner, treated or untreated, is to select the variables. The score aims to reflect the prisoners’ chances of participating in a program. These included the prisoners’ sociodemographic characteristics, criminal background, profile, and current offense characteristics. Using those variables, the score was calculated using a statistical model predicting the propensity for entering treatment. Thus, each prisoner received a score ranging from 0 to 1 where a score of 0 expresses a zero probability of participating in the program and 1 expresses a 100% probability of participating in the program.

After calculating the probability of participation in the program, each treated prisoner was automatically assigned (using the STATA program) to the prisoner with the closest score (the “twin”) from the nonparticipant group (after filtering). As the intervention group was large enough, we used a matching method called the nearest neighbor, which included matching one participant in the comparison group to each prisoner in the intervention group (single match approach). We used a bandwidth (caliper) of 0.01, which means that the differences between the treated prisoner and the matched twin of entering the treatment program do not exceed 1%, based on their scores. After this process, with two matched groups, the intervention and the comparison group, a test was designed to ensure that the model provided balanced samples and that there were no statistical or consistent differences between the groups regarding the variables used in the selection process and introduced into the model. We compared the tendency of participants of the IPS programs to recidivate with that of the addicted prisoners who did not participate in these programs.

Matching comparison group and intervention group: Drug rehabilitation program at Hermon Prison

Those who completed the drug rehabilitation program at Hermon Prison included 448 prisoners prior to matching with a score of 0.11 (SD = 0.07, minimum = 0.01, maximum = 0.60). The comparison group (nonparticipants) included 5,488 prisoners with an average propensity score of 0.07 (SD = 0.06, minimum = 0.00, maximum = 0.81). After matching, the intervention group included 393 prisoners with an average score of 0.11 (SD = 0.07, minimum = 0.01, maximum = 0.54). The comparison also included 393 prisoners with an average propensity score of 0.11 (SD = 0.07, minimum = 0.01, maximum = 0.53).

Table 1 presents a comparison between the group of prisoners who completed drug rehabilitation treatment at Hermon Prison, before and after matching. The differences were examined using a chi-square test (χ²) for nominal variables and a t-test for continuous variables.

Table 1.

Graduates of the Hermon Drug Rehabilitation Program and Comparison Groups Before and After Propensity Score Matching.

	Before matching (n = 5,936)		Bias before (%)	After matching (n = 786)		Bias after (%)
	Treatment group (n = 448)	Comparison group (n = 5,488)	Bias before (%)	Treatment group (n = 393)	Comparison group (n = 393)	Bias after (%)
Sociodemographic
New immigrant	24.3%	24.4%	−0.2	23.9%	24.7%	−1.8
Married	25.7%	28.0%	−5.2	25.7%	26.0%	−0.6
Ethnicity	63.6%	65.0%	−3	63.4%	61.8%	3.2
Age	34.4	33.9	5.4	34.9	35.8	−9.5
Level of Education	9.5	9.4	3.5	9.5	9.4	4.8
Criminal background
Prior incarcerations	3.5**	3.1**	15.4	3.7	3.9	−6.8
Age at first incarceration	24.1*	25.0*	−13.4	24.1	24.2	−1.1
Prisoner profile and offense
Violence by law	10.7%*	15.2%*	−13.3	9.7%	8.9%	2.3
Violence by IPS	4.4%	5.9%	−6.4	4.6%	5.1%	−2.3
Incarceration length (months)	27.6***	18.7***	69.8	25.9	25.0	7.5
Sex charge	1.3%	2.2%	−6.7	0.5%	0.3%	1.9
Violent charge	36.6%	40.1%	−7.2	35.4	31.8	7.3
Property charge	57.4%***	47.8%***	19.3	59.0%	63.6%	−9.2
Drug charge	49.3%*	44.1%*	10.5	49.4%	50.1%	−1.5
Drug dealer	14.1%	14.7%	−1.8	15.5%	14.6%	−0.7
Year of release	2008	2007	26.5	2008	2008	−0.5
Alcohol abuse	3.1%**	7.7%**	−20.4	2.8%	3.3%	−2.3

Note. IPS = Israeli Prison Service.

p < .05. **p < .01. ***p < .001.

Table 1 shows that, prior to matching the groups with the PSM method, there were significant differences in the seven variables, and after matching, there were none. In addition, the standard differences index appearing in the PSM tables as the “percentage bias” does not seem to be significantly different in both groups. In fact, after matching the groups, this index is less than 20 for all variables introduced into the model, indicating that the groups are also consistent with the index (Duwe & Clark, 2014). Thus, after matching, two groups of prisoners were created with very similar characteristics. The standard differences index (calculation) is as follows:

Bias = \frac{100 ({\bar{X}}_{t} - {\bar{X}}_{c})}{\sqrt{\frac{(S_{t}^{2} + S_{c}^{2})}{2}}} .

Matching comparison and intervention groups: Recovery and rehabilitation center program

The prisoner group who completed the RRC program prior to matching included 252 prisoners with an average propensity of 0.10 (SD = 0.09, minimum = 0.00, maximum = 0.74). The comparison group of nonparticipants consisted of 5,488 with an average propensity of 0.04 (SD = 0.05, minimum = 0.00, maximum = 0.65). Postmatching, the intervention group included 212 prisoners with an average propensity score of 0.09 (SD = 0.07, minimum = 0.00, maximum = 0.57), whereas the comparison group with 212 prisoners scored 0.09 (SD = 0.07, minimum = 0.00, maximum = 0.57). Table 2 compares prisoners participating in an RRC program before and after matching, using a chi-square test for nominal variables and a t-test for continuous variables.

Table 2.

Graduates of Recovery and Rehabilitation Centers Drug Rehabilitation Program and Comparison Groups Before and After Propensity Score Matching.

	Before matching (n = 5,740)		Bias before (%)	After matching (n = 424)		Bias after (%)
	Treatment group (n = 252)	Comparison group (n = 5,488)	Bias before (%)	Treatment group (n = 212)	Comparison group (n = 212)	Bias after (%)
Sociodemographic
New immigrant	21.0%	24.4%	−8.1	20.8%	21.7%	−2.3
Married	30.6%	28.0%	5.7	31.1%	30.2%	2.1
Ethnicity	61.9%	65.0%	−6.5	61.8%	63.2%	−2.9
Age	32.3**	33.90**	−17.7	33.5	33.8	−3
Level of education	9.4	9.4	−0.6	9.4	9.7	−11.8
Criminal background
Prior incarcerations	3.61**	3.08***	17.7	4.0	4.0	−0.5
Age at first incarceration	22.9***	25.0***	−31.6	23.1	23.5	−4.8
Prisoner profile and offense
Violence by law	10.7%	15.2%	−13.3	10.8%	8.5%	7
Violence by IPS	7.1%	5.9%	5.1	8.0%	8.0%	0
Incarceration length (months)	33.3***	18.7***	81.4	28.1	27.4	3.8
Sex charge	4.0%	2.2%	10.1	1.9%	0.9%	5.4
Violent charge	37.7%	40.1%	−4.9	34.9%	33.5%	2.9
Property charge	57.1%**	47.8%**	−18.8	60.4%	63.2%	−5.7
Drug charge	56%***	44.1%**	23.9	57.1%	57.1%	0
Drug dealer	12.7%	14.7%	−5.8	13.7%	12.3%	4.1
Year of release	2009	2007	62.6	2009	2009	−2.6
Alcohol abuse	4.7%	7.7%	−12.4	4.2%	4.7%	−2

Note. IPS = Israeli Prison Service.

p < .05. **p < .01. ***p < .001.

Table 2 shows that, prior to matching the groups, there were significant differences in six variables, and after matching, there were no significant differences. Thus, two groups of prisoners were created, which were similar in many characteristics. As shown in the standard differences index, the value of all variables was less than 20 after matching.

Matching comparison group and intervention group: Lev Room program

Before matching, those that completed the Lev Room program included 186 prisoners with an average score of 0.12 (SD = 0.16, minimum = 0.00, maximum = 0.84), whereas the comparison group, with 7,172 prisoners, had an average propensity score of 0.02 (SD = 0.04, minimum = 0.00, maximum = 0.80). Postmatching, the intervention group consisted of 132 prisoners with an average of 0.10 (SD = 0.11, minimum = 0.00, maximum = 0.81). The comparison group consisted of 132 prisoners with an average score of 0.10 (SD = 0.11, minimum = 0.00, maximum = 0.81). Table 3 compares participants in a Lev Room program prior to and after matching, using a chi-square test for nominal variables and a t test for continuous variables.

Table 3.

Graduates of Lev Room Drug Rehabilitation Program and Comparison Groups Before and After Propensity Score Matching.

	Before matching (n = 7,358)		Bias before (%)	After matching (n = 264)		Bias after (%)
	Treatment group (n = 186)	Comparison group (n = 7,172)	Bias before (%)	Treatment group (n = 132)	Comparison group (n = 132)	Bias after (%)
Sociodemographic
New immigrant	20.4	24.4%	−9.6	21.2%	19.7%	3.6
Married	24.7%	27.7%	−6.8	25.8%	26.5%	−1.7
Ethnicity	52.7%***	65.6%***	−26.6	52.3%	46.2%	12.4
Age	31.8**	33.9	−21.7	32.5	32.5	−0.1
Level of education	9.2	9.5	9.3	9.1	8.9	9
Criminal background
Prior incarcerations	3.4	2.9	13.5	3.8	3.9	−2.6
Age at first incarceration	23.8**	25.4**	−21.8	23.5	22.7	9.4
Prisoner profile and offense
Violence by law	12.9%	16.2%	−9.4	13.6%	12.1%	4.3
Violence by IPS	8.6%	5.9%	10.3	9.8%	7.6%	8.8
Incarceration length (months)	46.6***	16.1***	109.5	33.9	33.3	2.3
Sex charge	8.0%***	1.9%***	28.6	4.5%	6.0%	−7
Violent charge	47.8%*	39.9%*	16	47.7%	43.2%	9.2
Property charge	50.0%	45.8%	8.4	56.1%	61.4%	−10.6
Drug charge	43.0	43.1%	−0.2	43.2%	43.9%	−1.5
Drug dealer	12.9%	14.0%	−3.3	15.9%	21.2%	−15.5
Year of release	2009	2007	91.4	2009	2009	4.3
Alcohol abuse	5.3*	7.9%*	−10.2	5.3%	3.0%	9.2

Note. IPS = Israeli Prison Service.

p < .05. **p < .01. ***p < .001.

Table 3 shows that, prior to matching the groups, there were significant differences in six variables, and after matching, there were no significant differences. Thus, two groups of prisoners were created, which are similar in many characteristics. As shown in the standard differences index, the value of all variables was less than 20 after matching.

After defining the three study groups and three comparison groups, the efficacy of the program was examined by measuring recidivism. Prisoners were examined from release up to 5 years postrelease (or less for prisoners who were released in recent years). A comparison was made between the rates of the intervention and comparison groups. When statistically significant differences were found, Cohen’s d was calculated to examine the effect size. This allows us to examine the question of statistically significant differences and understand what the size of the effects found are. In this matter, Cohen’s d = 0.2 effect is considered small. The effect size of Cohen’s d = 0.5 is considered medium, and Cohen’s d = 0.8 is considered a large effect (Cohen, 1988). Cohen’s index is calculated as follows:

Cohen’s d = \frac{\bar{X} t - \bar{X} c}{\sqrt{\frac{SD t^{2} + SD c^{2}}{2}}} .

Findings

For each evaluated program, we will report whether a significant difference has been found using the chi-square test. In the case that a statistically significant difference is found, we will also report the standardized effect size using Cohen’s d. Average recidivism rates of the treatment and comparison groups were examined using the following measures: repeated incarcerations and repeated arrests. As far as the follow-up of a particular group is concerned, the number of prisoners for one group should not be changed throughout the entire follow-up period: after 1, 2, 3, 4, and 5 years.

Moreover, as we present the cumulative recidivism rate for each group for each year, it is not reasonable that the rate will be decreasing over time. However, our data file includes prisoners released between 2004 and 2012 and, as noted in the method section, information about recidivism is included only until July 2015. Therefore, for prisoners who were released before July 2010, we have a full follow-up of 5 years, whereas we have only partial information for prisoners who were released in the advanced years of the data file. Thus, theoretically, there may be a situation in which recidivism rates are decreasing, and groups are becoming smaller.

Re-Incarceration: Drug Rehabilitation Program Graduates at Hermon Prison

Table 4 and Figure 1 show re-incarceration rates of graduates from the drug rehabilitation program at Hermon Prison and their comparison group. Throughout the follow-up years, re-incarceration rates among program graduates were significantly lower than in the comparison group. In the first year after release, graduates were 26.4% less likely to recidivate compared with the comparison group, 16.8% less likely in the second year, 12.3% less likely in the third year, 12.3% less likely in the fourth year, and 13% less likely in the fifth year. Effect sizes were found to be small but stable throughout the follow-up years.

Table 4.

Cumulative Re-Incarceration Rates for Graduates of the Drug Rehabilitation Program at Hermon Prison and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 393 20.6%	n = 393 34.1%	n = 384 41.1%	n = 332 47.6%	n = 281 52%
Comparison	n = 393 28%	n = 393 41%	n = 390 46.9%	n = 352 54.3%	n = 296 59.8%
Chi-square	5.81**	3.96*	2.62^a	3.04*	3.6*
Cohen’s d	0.17	0.14	0.12	0.13	0.16

p < .05. **p < .01. *** p < .001.

Marginally significant.

Figure 1.

Cumulative re-incarceration rates for graduates of the drug rehabilitation program at Hermon Prison and the comparison group prisoners.

Rearrest: Drug Rehabilitation Program Graduates at Hermon Prison

Table 5 and Figure 2 show rearrest rates of graduates from the drug rehabilitation program at Hermon Prison and their comparison group. Throughout the follow-up years, rearrest rates among program graduates were significantly lower than in the comparison group. The analysis shows rearrest rates in the graduate group were significantly lower than in the comparison group. The rates were lower by 20.5% in the first year after release, 18.8% in the second year, 12.4% in the third year, 9.2% in the fourth year, and 11.9% in the fifth year. Effect sizes were found to be small to medium throughout the follow-up years.

Table 5.

Cumulative Rearrest Rates for Graduates of the Drug Rehabilitation Program at Hermon Prison and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 393 34.6%	n = 393 50.4%	n = 384 60.2%	n = 332 67.5%	n = 281 70.8%
Comparison	n = 393 43.5%	n = 393 62.1%	n = 390 68.7%	n = 352 74.4%	n = 296 80.4%
Chi-square	6.55**	10.94***	6.19**	4.03*	7.21**
Cohen’s d	0.18	0.24	0.18	0.15	0.22

p < .05. **p < .01. ***p < .001.

Figure 2.

Cumulative rearrest rates for graduates of the drug rehabilitation program at Hermon Prison and the comparison group prisoners.

Re-Incarceration: RRC Program Graduates

Table 6 and Figure 3 show re-incarceration rates of prisoners who completed the treatment at the RRC drug rehabilitation program, compared with re-incarceration rates in the comparison group. Except for the third year following discharge, no significant differences were found between the groups. However, in the third year following discharge, the re-incarceration rates among graduates were significantly lower at 15.4% relative to the comparison group.

Table 6.

Cumulative Re-Incarceration Rates for Graduates of the Recovery and Rehabilitation Centers Drug Rehabilitation Program and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 212 23.1%	n = 212 35.4%	n = 209 41.1%	n = 180 47.2%	n = 139 51.1%
Comparison	n = 212 24.5%	n = 212 35.4%	n = 208 48.6%	n = 171 54.4%	n = 132 59.1%
Chi-square	0.12	0	2.31^a	1.8	1.76
Cohen’s d	0.03	0	0.15	0.14	0.16

p < .05. **p < .01. ***p < .001.

Marginally significant.

Figure 3.

Cumulative re-incarceration rates for graduates of the recovery and rehabilitation centers’ drug rehabilitation program and comparison group prisoners.

Rearrest: RRC Program Graduates

Table 7 and Figure 4 show rearrest rates of prisoners who completed the treatment at RRC drug rehabilitation program, compared with rearrest rates in the comparison group. No significant differences were found between the two groups.

Table 7.

Cumulative Rearrest Rates for Graduates of the Recovery and Rehabilitation Centers’ Drug Rehabilitation Program and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 212 36.3%	n = 212 51.9%	n = 209 61.7%	n = 180 68.9%	n = 139 75.5%
Comparison	n = 212 42.5%	n = 212 58%	n = 208 65.4%	n = 171 73.1%	n = 132 79.5%
Chi-square	1.67	1.61	0.6	0.75	0.62
Cohen’s d	0.1	0.12	0.07	0.09	0.1

p < .05. **p < .01. ***p < .001.

Figure 4.

Cumulative rearrest rates for graduates of the recovery and rehabilitation centers’ drug rehabilitation program and comparison group prisoners.

Re-Incarceration: Lev Room Program Graduates

Table 8 and Figure 5 show re-incarceration rates among prisoners who completed the Lev Room drug rehabilitation project compared with re-incarceration rates in the comparison group. No significant differences were found between the groups during the follow-up period.

Table 8.

Cumulative Re-Incarceration Rates for Graduates of the Lev Room Drug Rehabilitation Program and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 132 32.6%	n = 132 46.2%	n = 126 57.1%	n = 100 56%	n = 72 59.7%
Comparison	n = 132 28%	n = 132 39.4%	n = 130 48.5%	n = 102 53.9%	n = 76 52.6%
Chi-square	0.65	0.2	1.94	0.09	0.76
Cohen’s d	−0.1	−0.13	−0.17	−0.04	−0.14

p < .05. **p < .01. ***p < .001.

Figure 5.

Cumulative re-incarceration rates for graduates of the Low Room drug rehabilitation program and comparison group prisoners.

Rearrest: Lev Room Program Graduates

Table 9 and Figure 6 present rearrest rates among graduates of the Lev Room program compared with rearrest rates in the comparison group. No significant differences were found between the groups during the follow-up period.

Table 9.

Cumulative Rearrest Rates for Graduates of the Lev Room Drug Rehabilitation Program and Comparison Group Prisoners.

	1 Year	2 Years	3 Years	4 Years	5 Years
Treatment	n = 132 47.7%	n = 132 66.7%	n = 126 73.8%	n = 100 75%	n = 72 79.2%
Comparison	n = 132 45.5%	n = 132 58.3%	n = 130 70%	n = 102 73.5%	n = 76 73.7%
Chi-square	0.14	1.956	0.46	0.06	0.76
Cohen’s d	−0.04	−0.17	−0.08	−0.03	−0.12

p < .05. **p < .01. ***p < .001.

Figure 6.

Cumulative rearrest rates for graduates of the Low Room drug rehabilitation program and comparison group prisoners.

Sensitivity Analysis for Average Treatment Effects (Mantel and Haenszel [MH] Bounds Test): Drug Rehabilitation Program Graduates at Hermon Prison

As is the case with other observational data analysis methods, PSM faces similar constraints, such as the degree to which variables that differentiate selection factors are identifiable. In this regard, a strong “ignorability” assumption can only be made through experimental designs (Boruch, 2007; Weisburd, 2010). Simultaneously, when many relevant covariates have been identified, it is reasonable to assume that the groups are equivalent (Shadish, 2013; Shadish, Cook, & Campbell, 2002). Nevertheless, there has been increasing concern that validity concerning PSM models may be overstated, most notably in cases where the data sources of the covariates are considered weak (Loughran, Wilson, Nagin, & Piquero, 2015; D. P. Rosenbaum, Lawrence, Hartnett, McDevitt, & Posick, 2015).

One approach that provides a means of assessing the sensitivity of the study results to selection, resulting from the excluded key measures in PSM model development, has already been provided by P. R. Rosenbaum (2002). Based on Rosenbaum’s approach, in cases where the outcome measure is binary, the MH bounds test provides an overall estimate of the sensitivity of the model to bias in the measurement of gamma (Aakvik, 2001; Mantel & Haenszel, 1959). When gamma equals 1, this indicates the absence of hidden bias, whereas an increasing gamma means that unobserved variables that are potentially influencing results may be present. This test makes no statement regarding the extent or degree to which unobserved variable bias exists in model estimates; rather, it refers only to the sensitivity of the study to unobserved variables.

Two different scenarios are estimated when running the MH bounds test. The first scenario, defined as Qmh+, refers to a situation in which a treatment effect has been overestimated. The second possible situation, defined as Qmh−, refers to a situation in which a treatment effect has been underestimated (Caliendo & Kopeinig, 2005). Essentially, this means that Qmh+ is used when people who are more likely to be treated are also more likely to have higher values on the outcome variable, whereas Qmh− is used when people who are more likely to be treated are more likely to have lower values on the outcome variable (Schwarze, Erasmi, Priess, & Zeller, 2009). In our case, we use Qmh− because our findings suggest that the work release program reduces the recidivism rate. In our study, we only performed the sensitivity test for the program that showed significant positive results, that is, the completers of the drug rehabilitation program in Hermon Prison. Using a marginal significance threshold of 0.10, our results generally stay significant with gamma values between 1.1 and 1.2 for re-incarceration and between 1.2 and 1.4 for rearrests. These findings suggest that the issue of bias may arise only if there is an unobserved variable that increases the odds of entering the treatment by 10% to 20% or 20% to 40%, respectively (Table 10). “There is no clear definition of what thresholds are required for a model to meet a strong ignorability assumption” (Weisburd, Hasisi, Shoham, Aviv, & Haviv, 2017, p. 15). However, the results of the sensitivity test in this study are consistent with other published studies in criminology and criminal justice (e.g., see Kirk & Hardy, 2014; Lee & Thompson, 2008).

Table 10.

Mantel and Haenszel Bounds for the Treatment Effect for Different Follow-Ups.

	Re-incarcerations		Rearrests
	Gamma (Q_mh–)	P critical (p_mh–)	Gamma (Q_mh–)	P critical (p_mh–)
Re-incarcerations
Recidivism 1 year (incarcerations)	1.1	.03	1.1	.03
Recidivism 1 year (incarcerations)	1.2	.10	1.2	.10
Recidivism 2 years (incarcerations)	1.0	.02	1.3	.07
Recidivism 2 years (incarcerations)	1.1	.10	1.4	.18
Recidivism 3 years (incarcerations)	1.0	.06	1.1	.03
Recidivism 3 years (incarcerations)	1.1	.18	1.2	.11
Recidivism 4 years (incarcerations)	1.0	.04	1.1	.08
Recidivism 4 years (incarcerations)	1.1	.14	1.2	.19
Recidivism 5 years (Incarcerations)	1.0	.03	1.2	.04
Recidivism 5 years (Incarcerations)	1.1	.10	1.3	.10

p < .05. **p < .01. ***p < .001.

Discussion and Conclusion

Drug addicts make up the “hard core” population faced by law enforcement (Chandler et al., 2009; Hughes, Payne, Macgregor, & Pockley, 2014; Inciardi et al., 2004; Wexler et al., 1990; Wexler et al., 1992). Facing the many dangers of addiction in general and among prisoners in particular (who are overrepresented by addicts), prisons offer different kinds of programs for rehabilitation and recovery aimed at reducing return to abuse and criminal activities of prisoners once released (Mitchell et al., 2007; Mitchell et al., 2012).

Due to the deep complexity of this problem, it does not come as a surprise that the literature raises doubts regarding the effectiveness of drug rehabilitation programs. Even the programs that are considered the most effective in reducing addicts’ recidivism rates, operating as a therapeutic community and integrating strong therapeutic components, show only a small effect, if any, according to the literature. A previous study conducted by Hasisi and his colleagues (2018) examined the same programs evaluated in the current study. They found that these programs were not significantly effective in reducing recidivism rates for program participants. As noted, one key element that may affect the success of a treatment program is its completion. Therefore, an explanation for the poor results found in Hasisi et al. (2018) may be related to the high attrition rate of the programs. In the current study, we, therefore, wanted to examine the extent to which completion of the program plays a role in the success of prisoners in various addiction programs. That is, we conducted a follow-up analysis of the efficacy of the various programs for those prisoners who completed the programs and did not drop out.

The study showed that the only rehabilitation program that indicated significant and positive outcomes for its completers was the one at Hermon Prison, whereas the other two programs have demonstrated ineffectiveness. Prisoners who completed the treatment at Hermon prison were incarcerated and arrested less often than their comparison group. Completing the treatment plays a key role in the success and increases the chances of true rehabilitation and lower recidivism. As noted, no similar positive effects were found in the rest of the programs, which means that completion of the program independently is insufficient when trying to reduce recidivism rates of addict prisoners. This finding suggests that only completion of a long-term comprehensive program combining promising treatment components, such as cognitive behavioral therapy, and operation in a therapeutic community with a positive social climate, will lead to ideal results.

Regarding program completion, it should be noted that many researchers link the dropout and lack of success of participants to their low level of motivation (Ball et al., 2006; Cahill et al., 2003; Simpson & Joe, 1993). In this study, our treatment groups included only participants who completed the program. Therefore, one might argue that the evaluation conducted in this study could be biased due to the high motivation of the participants. However, if this were the case, we would expect to see positive outcomes in all three evaluated programs. As the results indicate otherwise, we argue that motivation by itself cannot explain the decrease in recidivism rates. In this matter, our results are highly valuable, as they may indicate how people with supposedly high motivation react to different kinds of drug rehabilitation programs (Ball et al., 2006; Cahill et al., 2003; Simpson & Joe, 1993). With reference to our research, only interaction between a good treatment program and a highly motivated individual could produce ideal results. However, a limitation of this study is that it does not explore how motivation of completers might vary between the three programs. Nevertheless, the sensitivity analysis conducted suggests that the results of this study are reasonably valid and reliable.

Considering the study results, it is important for further studies to examine the inability of drug rehabilitation programs operating within prisons to lead to a reduction in recidivism rates. We wish to raise two main issues in this context. First, the analysis indicates a remarkably high dropout rate among addicts in each of the three evaluated programs. Dropping out is a major obstacle in making treatment accessible to addicts, which in turn increases the chances of re-involvement in the consumption of drugs and crime. This reinforces our belief that one of the main challenges to success lies in preventing participants from dropping out of drug rehabilitation programs. Therefore, finding ways to help them finish is vital. Further research on the phenomenon of attrition from such programs might help us discern what factors that led to program completion contribute to success in reducing recidivism.

Our study was based on a quasi-experimental design using a statistical method suitable for retrospective data (PSM). The wealth of data also enabled us to track the re-incarceration and rearrests of prisoners in the treatment and comparison groups. However, the study is based on secondary data that may sometimes contain missing values or coding failures. Even so, it is reasonable to assume that these biases are random and are divided equally between treatment and comparison groups.

Another limitation relates to the fact that the quasi-experimental research we conducted is limited in its ability to control only the variables existing in the database. For example, we lack data on the drug types used by the prisoners who participated in the programs. Our assumption was that the various types were randomly divided among the addicts. This assumption was reinforced in our meetings with the program operators before starting the study, but it is advisable that future researchers examine the effects of the types of drugs used by prisoners on treatment success.

The main conclusion of this study is related to the combination of the findings as shown by Hasisi et al. (2018) and those in the current research. Hasisi and his colleagues examined the effectiveness of the three drug rehabilitation programs operating in the IPS while using the “intention to treat” approach. They found no statistically significant differences between the treatment and the comparison groups in all three examined programs. These findings might indicate that promising components alone are not enough to achieve an effective program. However, the current research, by examining completers of the same three programs, found that completion alone cannot ensure positive results. This is demonstrated by showing that the Magash program and Lev Room program were not effective as well even for program completers. The only combination that has been evaluated and found to be effective was the completers of the program operating in Hermon.

The important contribution of this study is that it reveals that the effectiveness of the three drug rehabilitation programs operating in the IPS depends on both the quality of the program and the participant’s completion of the program. The negative findings found in the Magash and Lev Room programs, even for the completers, raise the question of whether it is worthwhile for prison systems to operate programs lacking key components. Instead, should policy-makers invest financial and therapeutic resources in intensive programs such as Hermon as well as trying to encourage patients to complete the program? In this regard, future studies should continue to examine the effectiveness of various drug rehabilitation programs while attempting to crack the black box, that is, understanding what are the key components that are most effective. Also, future studies should evaluate these programs while focusing on other outcome measures that reflect successful reentry such as employment, health, and drug relapse in an attempt to understand the effectiveness of the programs. If so, the “golden strategy” for rehabilitating drug-using prisoners will be twofold. First, the program should be comprehensive and based on the promising components and principles described above: cognitive behavioral therapy, therapeutic community, long duration, intensity, and positive social climate. Second, the program should succeed in retaining its participants through completion.

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Noam Haviv

Notes

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