Financial Problems and Debt as Predictive Factors for Recidivism

• Published date: 01 September 2023
• DOI: http://doi.org/10.1177/00938548231177708
• Author: Gercoline van Beek,Vivienne de Vogel,Dike Van de Mheen
• Date: 01 September 2023
• Subject Matter: Articles

CRIMINAL JUSTICE AND BEHAVIOR, 2023, Vol. 50, No. 9, September 2023, 1341 –1360.

DOI: https://doi.org/10.1177/00938548231177708

Article reuse guidelines: sagepub.com/journals-permissions

© 2023 International Association for Correctional and Forensic Psychology

1341

FINANCIAL PROBLEMS AND DEBT AS

PREDICTIVE FACTORS FOR RECIDIVISM

GERCOLINE VAN BEEK

VIVIENNE DE VOGEL

University of Applied Sciences Utrecht

DIKE VAN DE MHEEN

Tilburg University

This study aimed to examine the unique predictive validity of debt regarding recidivism and what elements are specifically

predictive. This was done based on a Dutch sample of 250 people on probation using an explorative research tool, the

Finances, Debt, and Offending Scale (FDOS). Cox survival regression and receiver operating characteristics analyses were

conducted on the total FDOS and its individual items as predictors and diverse recidivism criteria. The average follow-up

duration was 5.41 years. The results show that debt moderately predicts recidivism (adjusted for other predictors). The FDOS

significantly predicted recidivism on all three levels of severity, and regarding the type of crime, it predicted recidivism in

property and drug-related crime. Earlier debt and probation officers’ indications of whether finances are criminogenic were

especially predictive. These insights may help frontline service providers better understand the role of finances in recidivism,

measure financial problems in risk assessment, and select interventions.

Keywords: financial problems; debt; crime; recidivism; predictive factor

INTRODUCTION

Many criminological and forensic psychological studies into desistance from crime have

paid substantial attention to crime risk factors and ways to prevent repeated crime. These

studies have shown that reducing several risk factors for criminal behavior contributes to

desistance (e.g., Laub & Sampson, 2001, 2003; Moffitt, 1993, 2012). In their work about

the psychology of criminal conduct, Bonta and Andrews (2017) distinguished factors related

to the biological basis of criminal behavior, antisocial personality patterns, the role of pro-

criminal associates and attitudes, substance abuse, and the social context relating to family,

relationships, school, work, leisure or recreation, and neighborhood as major risk factors in

AUTHORS’ NOTE: The authors would like to thank the Dutch Probation Service for its participation in this

research project and permission to use data from the standard risk assessment instrument and client files and

also thank the steering committee of this project for its invaluable feedback during the research process. The

authors declare that they have no relevant or material financial interests related to the research described in

this article. Correspondence concerning this article should be addressed to Gercoline van Beek, Research

Group Working with Mandated Clients, Research Centre for Social Innovation, University of Applied Sciences

Utrecht, Padualaan 101, 3584 CH Utrecht, The Netherlands; e-mail: gercoline.vanbeek@hu.nl.

1177708CJBXXX10.1177/00938548231177708Criminal Justice and Behaviorvan Beek et al. /

research-article2023

1342 CRIMINAL JUSTICE AND BEHAVIOR

criminal conduct. An important model on which many intervention methods within the

forensic field are based is the risk-needs-responsivity model (RNR model) of Bonta and

Andrews (2017). This model states that interventions should focus on and be in line with the

risk type, needs, and responsivity of the involved person. Interventions based on the RNR

model principles appear to be the most successful in reducing the risk of recidivism

(Andrews, 2012).

MACROECONOMIC PERSPECTIVE

Knowledge concerning risk factors for (repeated) offending has dramatically increased

over the last 25 years, and methods to assess and manage risks have been developed and

improved (e.g., Cullen & Gendreau, 2001; Douglas & Otto, 2021; Durnescu, 2012).

However, to date, relatively little attention has been paid to financial problems and debt as

potential predictive factors for (re)offending. For example, Bonta and Andrews (2017) did

not include finances as one of the main criminogenic factors that they identified (the so-

called “big eight”), and Gendreau et al. (1996) did not include financial problems either in

their meta-analysis of the predictors of adult offender recidivism. Moreover, in exploring

the relationship between debt and crime, research has mainly focused on macroeconomic

factors, such as poverty (Comanor & Phillips, 2002; Galloway & Skardhamar, 2010; Hsieh

& Pugh, 1993), the economic situation of neighborhoods (Leventhal & Brooks-Gunn,

2001), and unemployment (Bjerk, 2007; Phillips & Land, 2012; Skardhamar & Savolainen,

2014). In addition, there is a growing body of research on the relationship between court

related fees and crime (Bannon et al., 2010; Link, 2021; Montes et al., 2021). However,

several studies have demonstrated that individual debt may be a better indicator of worsen-

ing financial situations than macroeconomic factors (see Aaltonen et al., 2013). The finan-

cial situation of the individual may thus yield valuable knowledge about the relationship

between debt and crime. In addition, insight into individual debt enables frontline service

providers working with justice-involved people to make adequate risk assessments and help

clients with their finances to prevent recidivism. Nevertheless, few studies have investi-

gated the relationship between debt and crime at this individual level.

THEORETICAL EVIDENCE

Three criminological theories on persistence in and desistance from criminal behavior in

general can provide specific insights into the relationship between debt and crime: (1) the

strain theory, (2) the developmental taxonomic theory, and (3) self-control theories (van

Beek et al., 2020b). First, the strain theory explains criminal behavior by the strain between

needs and the abilities to satisfy these needs (Agnew, 1985, 2006a; Merton, 1938). Applying

this theory to debt, it can be stated that the fact that people who have debt have less access

to material goods might lead to crime as a response to the stress that debt causes (Drentea,

2000; Felson et al., 2012) or more directly income-generating crime aiming to satisfy mate-

rial needs (Becker, 1968).

A second theory of criminal behavior, the developmental taxonomic theory posed by

Moffitt (1993), makes a distinction between two types of people committing crimes based

on their criminal trajectory over their life-course. The first group includes people whose

antisocial behavior is restricted to the adolescence and who often have relatively unprob-

lematic backgrounds and are mainly influenced by antisocial peers. The second group