Predicting Attrition and Engagement in the Treatment of Young Offenders

• DOI: 10.1177/0306624X19877593
• Published date: 01 March 2020
• Date: 01 March 2020
• Subject Matter: Articles

https://doi.org/10.1177/0306624X19877593

International Journal of

Offender Therapy and

Comparative Criminology

2020, Vol. 64(4) 355 –374

© The Author(s) 2019

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DOI: 10.1177/0306624X19877593

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Article

Predicting Attrition and

Engagement in the Treatment

of Young Offenders

Lena C. Carl1, Martin Schmucker1,

and Friedrich Lösel1,2

Abstract

Premature treatment termination in offender treatment is linked to negative

consequences for clients, practitioners, and the criminal justice system. Therefore,

identifying predictors of treatment attrition is a crucial issue in offender rehabilitation.

Most studies on this topic focus on adult offenders; less is known about adolescent

offenders. In our study, therapy attrition and engagement were predicted via logistic

and linear regression to examine the link between pretreatment variables, engagement,

and treatment failure in 161 young offenders treated in a social-therapeutic unit

in Germany. Engagement could be predicted by motivation, disruptive childhood

behavior, low aggressiveness, and higher age. In turn, low motivation, substance abuse,

and young age predicted attrition, but their impact diminished when engagement was

added to the model with only substance abuse remaining significant. The effect of

substance abuse on attrition disappeared, when the offender’s initial motivation was

high. Implications for assessment and treatment planning are discussed.

Keywords

offender treatment, young offenders, social-therapeutic treatment, treatment

attrition, dropout, engagement, motivation

Introduction

There is widespread agreement that offender treatment has made substantial progress (e.g.,

Cullen, 2013; Lösel, 2012). Intervention concepts that adhere to the risk-need-responsivity

1Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

2University of Cambridge, UK

Corresponding Author:

Lena C. Carl, Lehrstuhl für Psychologische Diagnostik, Methodenlehre & Rechtspsychologie, Friedrich-

Alexander-Universität Erlangen-Nürnberg, Nägelsbachstraße 49c, Erlangen 91052, Germany.

Email: lena.carl@fau.de

877593IJOXXX10.1177/0306624X19877593International Journal of Offender Therapy and Comparative CriminologyCarl et al.

research-article2019

356 International Journal of Offender Therapy and Comparative Criminology 64(4)

(RNR) model (Bonta & Andrews, 2017) have demonstrated desirable effects. There are

also sound extensions of the RNR model to staff, context, and other features (Andrews,

Bonta, & Wormith, 2011), although some of these issues need more replication (Lösel,

2017). Various influences may contribute to variation in outcomes, and treatment dropout

is an important one of these. Premature treatment termination is consistently linked to

negative consequences. For instance, studies showed higher recidivism rates for treatment

noncompleters than for completers (e.g., Edwards et al., 2005; Loeb, Waung, & Sheeran,

2015; Olver, Stockdale, & Wormith, 2011; Seabloom, Seabloom, Seabloom, Barron, &

Hendrickson, 2003; Wormith & Olver, 2002). It has also repeatedly been found that non-

completers are even more likely to reoffend than untreated controls (Hanson & Bussière,

1998; McMurran & Theodosi, 2007; Olver & Wong, 2009). The meta-analysis by Olver

et al. (2011) showed that attrition in offender rehabilitation programs is a frequent problem.

The respective rates range from 20% for prison-based treatment of adults to about 60% for

inpatient juvenile offender treatment. Offenders dropping out from treatment are not only

at an elevated risk of reoffending, but may also loose motivation for any behavioral change

or become stigmatized in the criminal justice system (Olver et al., 2011).

Dropout has different reasons, for example, lack of motivation, noncompliance,

misbehavior, relocation to another institution, or getting employment in the commu-

nity. In addition to these individual factors, premature treatment termination may also

be an indicator of problems in program implementation and quality assurance (Beyko

& Wong, 2005; Koehler, Lösel, Akoensi, & Humphreys, 2013). This can have a nega-

tive impact on staff motivation and prison climate (Howells & Day, 2007). Last but not

least, treatment dropout must also be viewed from a financial perspective of proper

investment in the criminal justice system.

For these and other reasons, it is highly important to avoid the dropout of offenders

from rehabilitation programs. Accordingly, many programs contain eligibility criteria

to target the most suitable clients and avoid dropout, but in routine practice such crite-

ria are not always fully met (Maguire, Grubin, Lösel, & Raynor, 2010). To keep drop-

out as low as possible it is essential to determine relevant predictors of attrition to

identify clients with a high risk of dropout, to adapt therapeutic programs, and to

develop strategies to reduce premature treatment termination in a long-term perspec-

tive (Steketee, 1992).

There are various studies on this topic, but most of them focus on adult offenders

(Olver et al., 2011). Less is known about treatment attrition in adolescent offenders,

although predictors of dropout are likely to differ from those found for adults. Juveniles

are usually more reliant on their family for guidance and support than adults; there-

fore, parental issues such as divorce, psychiatric disorders, or interfamilial violence

may be relevant risk factors in adolescents but not in adult offenders (Loeb et al.,

2015). Also, less maturity that is visible in youth-related substance abuse or other dis-

ruptive behavior may be linked to problematic behavior in the therapeutic setting and

interfere with treatment completion. As adolescents have the highest attrition rates

within the field of offender rehabilitation (Olver et al., 2011), it is particularly impor-

tant to investigate dropout risks in this population. Research revealed various risk

factors predicting treatment attrition in young offenders, but the findings are