Sociodemographic and psychopathological predictors of criminal behavior in women with gambling disorder
Introduction
The commitment of a crime by women, understood as unpermitted behaviors from a legal and criminal standpoint, has undergone a substantial increase in the past two decades (Mendoza and Guzmán, 2002, Staton Tindall et al., 2015). This progressive integration of women into the world of crime has become evident through their participation in a wide range of illegal acts, contrary to previous trends when infanticide or prostitution were the most frequent serious crimes reported in this population (Gartner & McCarthy, 2014). Although the increasingly greater heterogeneity in typologies of criminal behavior has been observed in numerous countries, crime statistics show that women have a higher tendency to commit non-violent offenses in comparison with men (Rossegger et al., 2009, Thornton et al., 2012). Within the specific context of gambling-related crimes, petty theft, fraud and forgery are among the most commonly reported criminal offenses in this population (Laursen, Plauborg, Ekholm, Larsen, & Juel, 2016).
Both sexes reach their highest incidence of criminal behavior between the ages of 15 and 30, following the well-known age-crime curve theory (Farrington, 1986). However, women show an additional second increase in criminal behavior between the ages of 40 and 54 and tend to be first-time offenders (Mendoza & Guzmán, 2002). Several studies also highlight that female offenders show are approximately twice as likely to present severe psychopathology in comparison with men (Kimonis et al., 2010, Teplin et al., 1997). This greater vulnerability to mental health issues, especially depressive symptomatology and mood disorders (Teplin et al., 1997), may interfere with treatment protocols that do not take possible comorbidities into account (Jauregui, Estévez, & Urbiola, 2016). However, the complex interplay between criminal behavior and psychopathology is not entirely clear empirically, since many other factors may be playing an pivotal role in this association, such as childhood trauma (Driessen, Schroeder, Widmann, Von Schönfeld, & Schneider, 2006), a pattern of substance abuse (Abram, Teplin, & McClelland, 2003) or the age of onset of these disorders (Hoeve et al., 2014).
Likewise, different researchers have demonstrated that both sexes share common risk factors for criminal behavior, such as substance abuse, low education levels or lack of financial resources (Freudenberg et al., 2005, Herbst et al., 2016, Warren et al., 2005).
Gambling disorder (GD) is a psychiatric disorder categorized in the last version of the Diagnostic and Statistical Manual of Mental Health Disorders (DSM-5; APA, 2013) as a non-substance-related addiction. This disorder is characterized by recurrent and persistent problematic gambling behavior leading to clinically significant distress and it is often associated with cognitive distortions, certain personality traits and high psychopathology levels (Ciccarelli et al., 2017, Jiménez-Murcia et al., 2017).
In addition to these clinical factors, the DSM-IV-TR also included the presence of gambling-related crimes such as theft, counterfeiting or other fraudulent acts carried out in order to obtain funding to continue maladaptive gambling behavior or to solve financial problems arising from it as a diagnostic criterion for the disorder (APA, 2000). However, after a extensive debate in scientific community, this eighth criterion was removed in DSM-5 (APA, 2013) since the presence of a criminal record was thought to better reflect disorder severity than an accurate diagnostic criterion (Granero et al., 2014, Petry et al., 2013, Stinchfield et al., 2005).
The few gender-specific studies on gambling behaviors have elucidated demographic and psychological differences in risk factors. In comparison to men, women with gambling problems are generally older at GD onset and present higher levels of psychopathology (Granero et al., 2009, Hing et al., 2016). In terms of personality traits, high problem gambling severity in both male and female gamblers appears to be associated with higher scores on neuroticism, and with lower scores on conscientiousness and agreeableness (Brunborg, Hanss, Mentzoni, Molde, & Pallesen, 2016). Other studies using large samples of treatment-seeking gamblers have identified high levels of harm avoidance to be a key distinguishing trait in women with gambling problems compared to their male counterparts (Álvarez-Moya et al., 2007, Granero et al., 2016). These findings, in addition to other studies highlighting differences in indicators of emotional distress between men and women (Delfabbro, Thomas, & Armstrong, 2017), can lead one to postulate that gender differences between men and women who have committed illegal acts for gambling-related reasons are also present. Studies taking gender into account in GD patients with a criminal record are scarce and to the best of our knowledge, few studies to date have been published exploring these factors. Using a two-step clustering procedure, one study identified that women who reported having committed a gambling-related illegal act were more likely to present a comorbid psychopathological disorder and to present higher levels of gambling problems (Granero et al., 2014). More empirical studies are needed however to identify the key characteristics that distinguish female gamblers with a history of illegal acts from those without.
In this study, we aim to explore the clinical, personality and psychopathological differences between treatment-seeking women with GD with and without a history of criminal behavior. Our second goal was to ascertain which variables best predicted the presence of a criminal record in this population.
We hypothesized that GD women with a history of criminal acts would present higher levels of psychopathology, greater GD severity and a more dysfunctional personality profile than those without a criminal record.
Section snippets
Participants and procedure
The sample consisted of 273 women with a diagnosis of GD who were being treated at the Gambling Disorder Unit at a public University Hospital. Patients were derived to the Unit through general practitioners or via another healthcare professional. Moreover, although the treatment was not compulsory, some patients were derived from prison health services.
Experienced psychologists and psychiatrists conducted two face-to-face clinical interviews before a diagnosis was given and only patients who
Characteristics of the sample
Table 1 includes a description of the sociodemographic variables in the sample. Most participants were born in Spain (90.8%), had finished primary school (62.6%), were unemployed (51.3%) and pertained to the low socioeconomic level group (66.7%). Mean chronological age was 49.6 years (SD = 12.3). Significant differences in age between participants who reported illegal acts were found, with patients with a history of illegal acts being younger than the other group (T = 12.9, df = 271, p < 0.001).
Comparison of clinical characteristics
Table 2
Discussion and conclusions
The present study analyzed clinical and personality differences in a sample of treatment-seeking women with GD who reported committing illegal acts to those who did not, identifying the factors that best predicted criminal behavior.
In concordance with other studies exploring criminal behavior in different psychiatric populations, women with GD who reported having committed gambling-related illegal acts were significantly younger than those without a criminal history (Carlsen et al., 2017,
Contributors
GMB, TS, FFA, RG, JMM and SJM designed the experiment based on previous results and the clinical experience of MTT-N, AC, MB, LM, APG, NA, MGP, CVA, TM-M and NMB. RG, GMB, TS, FFA and SJM conducted the experiment, analyzed the data, and wrote a first draft of the manuscript. SJM, TS, GMB, RG, PM and FFA further modified the manuscript.
Funding
This manuscript and research were supported by grants from Instituto de Salud Carlos III (ISCIII) (FIS PI14/00290) and cofounded by FEDER funds/European Regional Development Fund (ERDF), a way to build Europe. CIBERobn and CIBERSAM are an initiative of ISCIII. This work was also supported by the Ministerio de Economía y Competitividad (PSI2015-68701-R). G.M.B. is supported by an AGAUR predoctoral grant (2017FI_B1 00145). TMM and CVA are supported by a predoctoral Grant of the Ministerio de
Conflict of interest
None.
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Shared first authorship.