Trajectories of Dynamic Risk Factors During Forensic Treatment: Growth Trajectory of Clinical Risk Factors in a Sample of Dutch Forensic Patients

• Date: 01 November 2020
• Author: Carlo Garofalo,Marinus Spreen,Eva Billen,Elien De Caluwé,Eric Blaauw,Stefan Bogaerts,Robin Van der Linde
• DOI: 10.1177/0306624X20909219
• Published date: 01 November 2020
• Subject Matter: Articles

https://doi.org/10.1177/0306624X20909219

International Journal of

Offender Therapy and

Comparative Criminology

2020, Vol. 64(15) 1491 –1513

© The Author(s) 2020

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DOI: 10.1177/0306624X20909219

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Article

Trajectories of Dynamic

Risk Factors During

Forensic Treatment: Growth

Trajectory of Clinical Risk

Factors in a Sample of

Dutch Forensic Patients

Robin Van der Linde1, Stefan Bogaerts1,2,

Carlo Garofalo1, Eric Blaauw3,4, Elien De Caluwé1,

Eva Billen1, and Marinus Spreen5

Abstract

In this study, growth trajectories (from admission until unconditional release) of

crime-related dynamic risk factors were investigated in a sample of Dutch forensic

patients (N = 317), using latent growth curve modeling. After testing the unconditional

model, three predictors were added: first-time offender versus recidivist, age, and

treatment duration. Postanalyses were chi-square difference tests, t tests, and

analyses of variance (ANOVAs) to assess differences in trajectories. Overall, on scale

level, a decrease of risk factors over time was found. The predictors showed no

significant slope differences although age and treatment duration differed significantly

at some time points. The oldest age group performed worse, especially at later time

points. Treatment duration effects were found at the second time point. Our results

that forensic patients show a decrease in crime-related risk factors may indicate that

treatment is effective. This study also found differences in growth rates, indicating the

effect of individual differences

1Tilburg University, the Netherlands

2Fivoor Science and Treatment Innovation, Rotterdam, the Netherlands

3Verslavingszorg Noord Nederland, Groningen, the Netherlands

4Hanze University of Applied Sciences, Groningen, the Netherlands

5Stenden University of Applied Sciences, Leeuwarden, the Netherlands

Corresponding Author:

Stefan Bogaerts, Department of Developmental Psychology, Tilburg University, Prof. Cobbenhagenlaan

225, Mailbox 90153, 5000 LE Tilburg, the Netherlands.

Email: s.bogaerts@uvt.nl

909219IJOXXX10.1177/0306624X20909219International Journal of Offender Therapy and Comparative CriminologyVan der Linde et al.

research-article2020

1492 International Journal of Offender Therapy and Comparative Criminology 64(15)

Keywords

forensic psychiatry, HKT-R, risk factors, latent growth analysis

Introduction

In many countries, forensic psychiatric patients are admitted to secure forensic institu-

tions because they have committed a violent crime caused by severe mental disorders.

The main goal of staying in low, medium, or high secure services is to receive treat-

ment for offense-related disorders or risk factors, such as impulsivity and hostility, and

to allow these patients to reintegrate into society on condition that there has been a

change in the severity of risk factors that justify a return to society (Bogaerts et al.,

2018). Studies aimed at obtaining longitudinal insights into the changeability of clini-

cal reversible risk factors are very scarce. Within the broader context of treatment

outcomes, longitudinal research on the changeability of problematic criminally ori-

ented behavior characterized by severe offense-related dynamic risk factors is rarely

done because the length of stay in forensic settings is often very long what makes

longitudinal follow-up very time-intensive and time consuming. Furthermore, because

of the specificity of high-risk forensic psychiatric patients staying in high secure ser-

vices, it’s difficult to meet the assumption of sufficient power.

The Dutch forensic psychiatric context is quite exceptional compared with other

countries. All patients in this study were sentenced with a TBS order (“terbeschik-

kingsstelling”; meaning involuntary admission by order of the state), which is a Dutch

criminal law measure. A TBS order means that patients are not responsible for their

behavior, which can vary from fully accountable to completely irresponsible (full

responsibility, slightly diminished responsibility, diminished responsibility, severely

diminished responsibility, and total absence of responsibility). Prior to compulsory

treatment, a prison sentence is first imposed by the court (De Ruiter & Trestman,

2007). A TBS order is a mandatory admission to a high-security forensic psychiatric

center (FPC) for mandatory treatment by order of the state because of mental disorder

that is related to the committed crime (De Ruiter & Trestman, 2007). The offense com-

mitted must have a criminal threat of at least 4 years. The goal of a TBS order is the

protection of society and the rehabilitation of patients into society.

Numerous studies have shown that the presence of risk factors and a lack of protec-

tive factors have moderate to strong associations with recidivism (Beech et al., 2002;

Bogaerts et al., 2018; Mulder et al., 2010). However, only a few studies show whether

risk factors can actually be reduced and reinforced longitudinally during a stay in high

security institutions, such as FPCs (Van der Veeken et al., 2018). Most studies only use

a cross-sectional research design and examine the predictive contribution of these risk

factors in the prediction and occurrence of recidivism, but do not address the course of

these risk and protective factors over time during treatment.

For many years, the forensic domain has focused on risk and protective factors,

which are empirically related to the risk of recidivism. To construct fitting assessment

and treatment, the risk-need-responsivity (RNR) model is developed (Andrews &

Bonta, 2006; Andrews et al., 1990). This theoretical model is one of the leading mod-

els and has been developed within a general personality and cognitive social learning