The Role of Motivation in Predicting Addiction Treatment Entry Among Offenders With Substance Use Disorders Under Probation Supervision

Abstract

Many offenders with a substance use disorder (SUD) do not enter addiction treatment. The aim of this study was to examine predictors of addiction treatment entry and to get more insight in the predictive value of treatment motivation. A total of 83 male offenders with a SUD under probation supervision in the Netherlands were assessed at the start of probation supervision and at 12-month follow-up. A total of 38 offenders (45.5%) entered addiction treatment in the follow-up period. Offenders with any mandated treatment (p = .028) and higher treatment motivation (p = .005) were more likely to enter treatment. Multiple logistic regression analysis showed that treatment motivation predicts addiction treatment entry in the first year of probation (OR = 2.215, p < .01). This emphasizes the relevance of treatment motivation for addiction treatment entry among offenders with a SUD. Pretreatment motivational interventions are therefore recommended for offenders with low motivation for treatment in probation settings.

Keywords

motivation for treatment addiction treatment entry offenders mandated treatment

Introduction

In this artcile, the effect of treatment motivation on addiction treatment entry is evaluated among criminal offenders with a substance use disorder (SUD) under probation supervision in the Netherlands. SUD is between 4 and 9 times more prevalent among offenders than in the general population (Fearn et al., 2016). Substance use and SUD increases the risk of criminal recidivism: The odds of offending are 3 to 4 times greater for substance users than non-substance users, and the frequency of criminal behavior inclines with the level of substance use (Bennett, Holloway, & Farrington, 2008; Gottfredson, Kearley, & Bushway, 2008; White & Gorman, 2000). Treating offenders with SUD therefore provides an excellent opportunity to decrease substance use and at the same time reduce associated criminal behavior. Addiction treatment has proven to be effective in reducing SUD and associated criminal behavior (Belenko, Hiller, & Hamilton, 2013; Chandler, Fletcher, & Volkow, 2009; Harvey, Shakeshaft, Hetherington, Sannibale, & Mattick, 2007; Prendergast, Pearson, Podus, Hamilton, & Greenwell, 2013; Prendergast, Podus, Chang, & Urada, 2002).

There is a lack of research on addiction treatment for offenders under community supervision (i.e., probation), especially outside the United States. A review by Belenko et al. (2013) on addiction treatment interventions used in the criminal justice system found that the majority of the studies focus on populations that are imprisoned in the United States, with addiction treatment interventions offered in prison. One meta-analysis of 15 studies on European addiction treatment programs compared treatment outcomes for offenders in prisons or jails with treatment programs under community supervision (Koehler, Humphreys, Akoensi, Sánchez de Ribera, & Lösel, 2014). This meta-analysis found that both types of programs (i.e., prison/jail- and community-based) were almost equally effective in reducing substance use and crime.

Despite the well-established link between substance use and crime and the positive effects of addiction treatment, many offenders who meet the criteria of SUD do not enter addiction treatment (Taxman, Perdoni, & Harrison, 2007). There are several challenges to treatment for offenders with SUD under probation supervision, such as issues of treatment availability, quality of services, and staff training (Chandler et al., 2009; Farabee et al., 1999; Taxman et al., 2007). Often substance abuse education is provided without treatment to offenders and many offenders get connected to support groups such as Alcoholics Anonymous and Narcotic Anonymous (Taxman et al., 2007). Other issues include, among other things, the little use of reinforcement techniques to encourage treatment participation and the limited time allocated for treatment within the correctional program (Taxman et al., 2007). In addition to these system-based challenges, however, there is also an important person-based barrier to treatment, namely offenders’ lack of motivation for treatment (Chandler et al., 2009).

In general, lower levels of motivation have been identified for individuals with an SUD treated in the criminal justice system, compared with individuals with an SUD treated in community settings (De Leon, Melnick, Thomas, Kressel, & Wexler, 2000; Melnick, De Leon, Thomas, Kressel, & Wexler, 2001). Lower levels of motivation to quit substance use and lower readiness for treatment were also observed for individuals who were legally mandated to treatment (compared with voluntary admission) within both residential and community-based services (Melnick, Hawke, & De Leon, 2014). Addiction treatment may have a smaller effect on those offenders who have not yet decided that substance use is a problem (precontemplators) or on those who have not decided what they want to do about their substance use (contemplators). For those offenders, treatment entry might be guided more by external factors—such as legally mandated admission—dictated at the point of arrest or sentence than by an intrinsic personal motivation (Klag, O’Callaghan, & Creed, 2005; Wild, 2006).

Prior studies on the predictive value of motivation for treatment among offenders assessed motivation at treatment entry instead of at the start of probation supervision. However, to evaluate the importance of implementing motivation-enhancing interventions during probation supervision, it is important to assess motivation for addiction treatment at the start of probation instead of at treatment entry. In addition, more research on probation-based treatment from outside the United States would increase the knowledge on the impact of contextual factors. For example, in the Netherlands the obligation to undergo treatment may be imposed as a condition attached to a suspended sentence. In practice, a suspended sentence with this condition attached is generally not imposed without consent of the sentenced person. In case the sentenced person does not consent, treatment will generally not be imposed as a condition to the suspended sentence (Flore, Bosly, Honhon, & Maggio, 2012). Therefore, in contrast to findings in the United States (Melnick et al., 2014), there may be a positive association between addiction treatment motivation and the legal mandate for treatment in the Netherlands.

The purpose of our study is to examine predictors of addiction treatment entry among offenders with a SUD under probation supervision. Secondary, we aim to get more insight in the predictive value of treatment motivation at the start of the probation. Using self-reported addiction treatment entry data, we address the following research questions: (a) What factors at start of probation (T₁) are associated with addiction treatment entry at 12-month follow-up (T₂)? and (b) To what extent is motivation for treatment at start of probation (T₁) associated with addiction treatment entry at 12-month follow-up (T₂)? We hypothesize that compared with those who have entered addiction treatment at T₂, those who have not entered treatment at T₂ will have a lower likelihood of mandated treatment and demonstrate a lower treatment motivation level at T₁.

Method

Study Design

The present study is part of a larger multisite, cluster-randomized controlled trial (CRT) in which the effectiveness of a brief motivation-enhancing intervention for offenders with SUDs was assessed (see Shaul, Koeter, & Schippers, 2016 for additional information). The participants in the CRT were 220 offenders with SUDs under probation supervision who received either supervision augmented with the intervention or supervision as usual. Offenders participating in the CRT were allocated to the study conditions by cluster randomization, with probation officer as the cluster variable. In total, 73 probation officers of six probation offices were randomized to one of the two conditions: supervision as usual (control condition) or supervision augmented with the motivational enhancement intervention (intervention condition). Offenders were allocated to a supervisor following the usual allocation procedure of the probation office. To control for a potential bias of the motivation-enhancing intervention, only the data of offenders from the control condition—that received supervision as usual and no intervention—was included in the present study.

Recruitment and Assessment Procedures

Between May 2010 and August 2012, offenders from six addiction probation offices in the Netherlands, were invited by their probation officer to participate in the CRT if they met the following criteria: (a) sufficient command of the Dutch language to understand interview questions and questionnaires; (b) male; (c) at least one prior sentence; (d) regular use of alcohol and/or illicit drugs, that is, using the substance at least 3 days a week, and additionally for alcohol use: consuming at least five or more glasses per day; (e) currently under a court-order supervision executed by an addiction probation service in a noncustodial setting. Exclusion criteria were: (a) a history of neurological problems or severe psychiatric disorders like schizophrenia, psychotic disorder, or bipolar disorder; (b) only convicted for driving under influence; (c) illegal stay in the Netherlands.

Eligible offenders received a short introduction and a brochure about the study from their probation officer. Those who wished to participate in the study were scheduled for a baseline assessment. Of the eligible offenders approached for participation in the CRT, 220 offenders (42%) agreed to participate and completed a baseline assessment at T₁. Of the 220 offenders, 160 (73%) participated a second time and completed a follow-up assessment (T₂), on average 14.4 months (SD = 3.76) after baseline assessment. Of the participants that completed both assessments at T₁ and T₂, 83 offenders (52%) were allocated to the control condition and 77 offenders (48%) to the intervention condition of the CRT. Offenders were paid €15 at baseline and €20 at follow-up for participation. Written informed consent for the offender’s study participation was obtained prior to baseline assessment. The CRT was approved by the Medical Research Ethics Committee of the Academic Medical Centre, University of Amsterdam.

Setting and Participants

The foundation for Social Rehabilitation of Addicted Offenders (Stichting Verslavingsreclassering or SvG) is a nonprofit national probation organization in the Netherlands that specializes in providing care and supervision to offenders with SUDs (Van Kalmthout & Tigges, 2008). Offenders are referred to the SvG by the judicial system as (part of) their sentence. All participants were under probation supervision of the SvG at T₁.

The current study included the 83 offenders that were allocated to the control condition of the CRT and that completed both T₁ and T₂ assessments. Participants were all male offenders, their mean age was 38 years (SD = 11, range 18-58) and 67% was born in the Netherlands. Highest educational achievement for the majority of the offenders (90%) was primary education or less, 85% was unemployed, and 60% had a permanent place to live in the past 30 days. The most common primary substances reported were alcohol (43%), cocaine (32%), marijuana (14%), heroin (6%), and methamphetamine (5%). The mean duration of primary substance use was 9 years (SD = 8.2). About 78% met the criteria for a SUD at T₁ assessment, 37% had completed a prior addiction treatment, and for approximately 58% of the participants a mandatory addiction treatment was included in their verdict. The main types of crime in the verdict were violent crimes (44%), acquisitive crimes (41%), and drug crimes (15%). The mean number of arrests in the year prior to T₁ is 2.3 (SD = 2.5) and the mean probation period is 22.5 months (SD = 9.9).

Measures

Baseline assessment included a larger battery of instruments including a semi-structured baseline interview based on the MATE-crimi (Schippers, Broekman, & Buckholz, 2011), containing 200 items regarding lifetime, 12 months, and 30-day information from offenders about their substance use, treatment history, criminal history, housing, education, and employment.

Treatment motivation was measured at baseline with the Dutch version of the Motivation for Treatment (MfT) scale, a 22-item questionnaire that assesses treatment motivation (De Weert-Van Oene, Schippers, De Jong, & Schrijvers, 2002). Each item is rated on a 5-point Likert-type scale, with response options ranging from “strongly disagree” to “strongly agree.” Higher scores on the scale indicate greater motivation.

Mandated addiction treatment was defined as the attached obligation to undergo an addiction treatment in the verdict. Mandated addiction treatment is a dichotomous variable derived from the digital database IRIS used by the addiction probation offices.

Treatment entry was defined at 12-month follow-up assessment (T₂) as entry into addiction treatment during the follow-up period (yes/no; self-reported by participants).

Statistical Analysis

Independent samples t-tests for continuous variables and a chi-square tests or Fisher’s exact tests for categorical variables were used to compare demographic (e.g., age, education level, employment), substance use (e.g., primary substance used, SUD, any mandated addiction treatment, history of completed addiction treatment), criminal behavior (e.g., crime type, history of arrests, probation period), and treatment motivation variables at baseline assessment (T₁) for those that did and did not enter addiction treatment at 12-month follow-up assessment (T₂). Next, multiple logistic regression analysis was conducted in two steps. For Model 1, the treatment motivation variable was entered as a predictor, with follow-up duration as a confounder variable. In Model 2, the Model 1 variables plus other baseline variables that were (nearly) significant (p < .10) between groups were entered. The (pseudo) explained variance of both models was assessed with the Nagelkerke R² measure. We compared the fit of the two models with the −2 log likelihood tests to assess the relative importance of the motivation variable (Model 1 vs. Model 2) in predicting addiction treatment entry. All analyses were conducted using SPSS version 21.0 (SPSS Inc., Chicago, IL, USA). p values < .05 were considered statistically significant.

Results

Table 1 shows the baseline characteristics of offenders stratified by treatment entry. A total of 83 offenders were included in the analysis. The sample was divided into two groups according to self-reported addiction treatment entry at follow-up assessment (T₂). Mean follow-up duration was 14.4 months (SD = 3.76). Thirty-eight offenders (46%) entered treatment for their problematic substance use in the follow-up period and 45 offenders (54%) did not. Follow-up duration was longer for offenders that entered addiction treatment during follow-up period than for those that did not, 15.4 months (SD = 4.7) versus 13.6 months (SD = 2.5), t(81) = 2.217, p = .041.

Table 1.

Characteristics of Offenders, Total Sample, and by Addiction Treatment Entry Status (Entry vs. No Entry).

Variable, % (n) or M(SD)	Total (n = 83)	Entry (n = 38)	No entry (n = 45)	χ², t	p value
Demographics
Age, M (SD)	37.9 (10.8)	36.6 (10.0)	39.0 (11.4)	0.986	.327
Born in the Netherlands, % (n)	67.1 (53)	69.4 (25)	65.1 (28)	0.166	.811
Primary education or less, % (n)	90.4 (75)	92.1 (35)	88.9 (40)	0.245	.721
Unemployed, % (n)	85.4 (70)	86.5 (32)	84.4 (38)	0.068	1.000
Permanent place to live, % (n)	60.2 (50)	63.2 (24)	57.8 (26)	0.249	.658
Substance abuse and treatment history
Primary problematic substance, % (n)				2.669	.636^a
Alcohol	42.5 (34)	40.5 (15)	44.2 (19)
Cocaine	32.5 (26)	29.7 (11)	34.9 (15)
Marijuana	13.8 (11)	18.9 (7)	9.3 (4)
Heroin	6.3 (5)	8.1 (3)	4.7 (2)
Methamphetamine, % (n)	5.0 (4)	2.7 (1)	7.0 (3)
Primary substance use, M (SD) years	9.4 (8.2)	9.9 (8.0)	9.0 (8.5)	0.501	.606^b
Problematic use at baseline^c, % (n)	78.3 (65)	84.2 (32)	73.3 (33)	1.435	.290
Prior completed addiction treatment, % (n)	37.0 (30)	48.6 (18)	27.3 (12)	3.938	.065
Mandated addiction treatment, % (n)	57.8 (48)	71.1 (27)	46.7 (21)	5.024	.028^*
Criminal involvement
Type of crime				0.098	1.000
Violent, % (n)	54.2 (45)	55.3 (21)	53.3 (24)
Property, % (n)	31.3 (26)	31.6 (12)	31.1 (14)
Drug, % (n)	14.5 (12)	13.2 (5)	15.6 (7)
No. of arrests, past 12 months, M (SD)	2.3 (2.5)	2.1 (2.1)	2.4 (2.9)	0.378	.692^b
Probation period, M (SD) months	22.5 (9.9)	23.6 (10.5)	21.6 (9.4)	0.896	.384^b
Treatment motivation, M (SD)	3.0 (1.0)	3.2 (1.0)	2.7 (0.9)	2.900	.005**
Follow-up duration, M (SD) months	14.4 (3.8)	15.4 (4.7)	13.6 (2.5)	1.173	.041^b*

Note. MATE = Measurements in the Addictions for Triage and Evaluation; CIDI = Composite International Diagnostic Interview.

Fisher’s exact test because expected cell counts <5.

bootstrapped p value of t test to account for skewed distributions.

Substance abuse and dependence established with the MATE-Crimi questionnaire based on the CIDI 2.1 (Diagnostic and Statistical Manual of Mental Disorders–IV [DSM-IV] criteria).

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

Treatment entry was positively associated with mandated addiction treatment in verdict (X² = 5.024, p = .028) and treatment motivation, t(80) = 2.900, p = .005. There was a positive trend toward an association between treatment entry and self-reported lifetime history of completed addiction treatments (X² = 3.938, p = .065). Demographic characteristics, substance use, or criminal involvement were not associated to addiction treatment entry at follow-up (T₂).

The multiple regression results are presented in Table 2. The main effects of Model 1 and Model 2 are shown. In Model 1, treatment motivation and follow-up duration were predictive factors of treatment entry. This model showed a significant, though limited amount of explained variance (likelihood ratio [LR]: χ² = 96.5, df = 2, p = .001) with Nagelkerke R² = .21. The Hosmer and Lemeshow (2000) goodness-of-fit test statistic was not significant (χ² = 4.5, df = 8, p = .809) indicating that the model fitted the data reasonably well. Offenders with higher levels of treatment motivation were 2 times as likely to enter addiction treatment compared with those with lower levels of treatment motivation, OR = 2.21, confidence interval (CI) = [1.29, 3.80], p = .004, and the likelihood of addiction treatment entry was increased by longer time to follow-up assessment (OR = 1.19, CI = [1.02, 1.38], p = .031). Model 2 also demonstrated that the likelihood of treatment entry was increased by treatment motivation and that the other predictors in the regression (i.e., prior completed treatment and treatment mandate) were not significantly associated with treatment entry in this model. With a Nagelkerke R² of .27, Model 2 accounted for 27% of the (pseudo) variance in treatment entry (LR: χ² = 92.2, df = 4, p = .001). Compared with Model 1, Model 2 showed no significant improvement in the amount of explained variance (p = .116). Finally, we have checked whether controlling for additional sociodemographic and clinical factors (i.e., age, education level, employment status, type of substance used, type of crimes committed) affects our results. We have found that none of these factors individually or in combination significantly impacted the reported findings.

Table 2.

Associations of Motivation, Mandate, and Prior Treatment With Treatment Entry.

Model/step	Variables	OR	p value	95% CI	–2 log likelihood	R ²	p-value step
1					96.505	.214	.001**
	Follow-up duration	1.186	.031*	[1.016, 1.384]
	Motivation	2.212	.004**	[1.288, 3.799]
	(Intercept)	0.007	.001**
2					92.199	.273	.116
	Follow-up duration	1.198	.036*	[1.012, 1.418]
	Motivation	1.870	.031*	[1.059, 3.301]
	Mandate	2.039	.170	[0.737, 5.638]
	Prior treatment	2.291	.118	[0.810, 6.480]
	(Intercept)	0.005	.001**

Note. OR = odds ratio; CI = confidence interval.

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

Discussion

The purpose of this study was to examine predictors of addiction treatment entry among offenders with a SUD under probation supervision and to get more insight in the predictive value of treatment motivation at the start of the probation. Congruent with our hypotheses, offenders who entered addiction treatment at 12-month follow-up (T₂) had higher levels of motivation at the start of probation (T₁) and were more often mandated to treatment than offenders who did not enter addiction treatment at T₂. In addition, it appears that treatment is more appealing to offenders with a lifetime history of addiction treatment, since a trend was observed for history of addiction treatment having a positive effect on current addiction treatment entry. With regard to the predictive value of treatment motivation, our study shows that treatment motivation is the strongest predictor of subsequent addiction treatment entry among male offenders with a SUD.

Implications

Prior studies on the predictive value of motivation assessed motivation at the point of treatment entry to predict addiction treatment outcome (Linn-Walton, & Maschi, 2015; Melnick et al., 2001; Olver, Stockdale, & Wormith, 2011). To the best of our knowledge, our study is the first to assess treatment motivation at the start of probation supervision to examine how motivation is related to the prediction of addiction treatment entry within the first year of probation supervision.

A recent UK study by Jones, Hayhurst, and Millar (2017) concluded that the success of addiction treatment in offenders with or without a legal mandate to treatment is unlikely to be impaired by lower levels of motivation at the point of treatment entry. The authors hypothesized that the potential lower motivation among those with a legal mandate to treatment may now be recognized and addressed within the criminal justice system. Jones et al. argued that lower levels of motivation may, indeed, exist at the point of arrest, but that motivation may be elevated at the time of treatment entry. Our study adds to this that offenders with a higher level of motivation at the start of probation supervision are more inclined to enter addiction treatment. Addressing offenders’ lack of motivation during probation supervision could thus be effective for both addiction treatment entry and success of treatment.

It remains to be tested whether the level of motivation at start of probation is associated with offenders’ perceived coercion to treatment instead of legal mandate. Offenders who perceive themselves as coerced may do so because they have been diverted from the criminal justice system into addiction treatment too early in their own process of change (Klag et al., 2005; Wild, 2006). Moreover, levels of perceived coercion may reflect differences in judicial systems and the application of mandatory referrals between countries.

Jones et al. (2017) highlight that concerns around lower levels of motivation are better focused on those who perceive themselves as coerced rather than on those whose referral—on objective grounds—carries a level of legal condition. Perceived coercion and motivation were shown to be different, but correlated constructs. Prendergast, Greenwell, Farabee, and Hser (2009) found that offenders who expressed a high level of perceived coercion tended to score lower on motivation, while those who felt that they were under low coercion (i.e., felt a sense of choice and autonomy) to enter treatment tended to score high on motivation. Future studies on offenders’ treatment motivation and on predictors of addiction treatment entry should include measures of perceived coercion.

In probation settings where addiction treatment is encouraged, the results of the current study suggest that motivational interventions designed to enhance offenders’ motivation for addiction treatment may increase the likelihood of addiction treatment entry. This corroborates findings from previous research into motivational pretreatment programs for offenders that showed that it is beneficial to address lack of motivation prior to offender treatment programs for behavior change (Anstiss, Polaschek, & Wilson, 2011; Marshall, & Moulden, 2006). Ensuring treatment availability to offenders is important and requires the cooperation and coordination between the criminal justice system and the addiction treatment system. Addressing offending as a public health-related behavior promotes the idea that offending can be adjusted through interventions and services that are tailored to the unique risks and needs of the individual (Taxman, & Marlowe, 2006). As noted by Taxman (2014) there is a need for more service-related research to broaden our understanding of how to improve individual-, program-, and system-level health and justice outcomes.

Future studies on factors promoting treatment entry during probation should take treatment motivation into account by assessing it at the start of probation, because motivation may fluctuate and higher motivation has been related to better addiction treatment outcomes (Taxman, Walters, Sloas, Lerch, & Rodriguez, 2015). Empirical knowledge of internal and external factors that promote and/or restrict treatment motivation among offenders with SUDs could facilitate the development of more effective motivational intervention strategies. Previous research on factors that influence motivation in psychiatry and the addiction treatment field show the following key factors: client characteristics (recognition of problem severity, self-efficacy), therapist (staff) characteristics, therapeutic (staff–offender) relationship, client–service matching, and environmental support (Luborsky, Mclellan, Woody, O’brien, & Auerbach, 1985; Miller, 1985; Najavits, & Weiss, 1994). Finally as mentioned above, more service-related research would provide knowledge on how to effectively implement interventions and treatment programs for offenders that serve both individual health and community safety needs (Taxman, 2014).

Strengths and Limitations

Our study has several strengths. First, it is one of the few randomized control trials (RCTs) on treatment entry among offenders under community supervision outside the United States. Second, to the best of our knowledge, our study is the first to assess treatment motivation at the start of probation supervision to examine how motivation is related to the prediction of addiction treatment entry within probation supervision. Prior studies on the predictive value of motivation assessed motivation at the point of treatment entry to predict addiction treatment outcome (Linn-Walton, & Maschi, 2015; Melnick et al., 2001; Olver et al., 2011). Thus, in contrast to prior studies, our study looked at the predictive value of treatment motivation among offenders under probation supervision and not only at treatment motivation of offenders at the start of addiction treatment.

Our study has also several limitations. First, we only evaluated male repeat offenders and thus, our findings may not generalize to female or first offenders. Second, the small sample size of the treatment entry status groups may have limited our power and thus our ability to identify whether other offender characteristics relate to addiction treatment entry as well. Third, in recent studies, perceived coercion has been related to treatment motivation (Jones et al., 2017; Opsal, Kristensen, Vederhus, & Clausen, 2016) and perceived coercion may therefore also be predictive of treatment entry. We did not measure perceived coercion, and thus, our study does not provide information on how perceived coercion may have interacted with treatment motivation in our sample of repeat offenders. Fourth, except for the official records obtained on mandated addiction treatment, participant data are based on self-report. However, the instruments and procedures used in this study have been validated (Schippers, Broekman, Buchholz, Koeter, & Van Den Brink, 2010), and blinding of professionals to the responses of participants was warranted, as the researchers were not affiliated with the Dutch probation organization, SvG.

Conclusion

In probation settings where addiction treatment is encouraged lies an opportunity to enhance addiction treatment entry for offenders with a SUD. This study shows that treatment motivation predicts addiction treatment entry among repeated male offenders with a SUD under probation supervision. This study therefore emphasizes the importance of treatment motivation and implementation of motivation-enhancing interventions in probation settings to enhance addiction treatment entry by offenders with a SUD.

Footnotes

Acknowledgements

We thank the staff and clients at the participating addiction probation offices for their cooperation in the study.

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: This research was supported by the NWO—ZonMw (Grant 31160207).

ORCID iD

Lilach Shaul

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