The Predictive Accuracy of the LSI-R in Female Forensic Inpatients—Assessing the Utility of Gender-Responsive Risk Factors

Viviane Wolf (), Juliane Mayer, Ivonne Steiner, Irina Franke, Verena Klein, Judith Streb and Manuela Dudeck
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Viviane Wolf: Department of Psychiatry and Psychotherapy, Medical Faculty, LVR-Clinic Duesseldorf, Heinrich Heine University Duesseldorf, 40629 Duesseldorf, Germany
Juliane Mayer: Department of Forensic Psychiatry and Psychotherapy, kbo-Isar-Amper-Clinic Taufkirchen (Vils), 84416 Taufkirchen (Vils), Germany
Ivonne Steiner: Department of Forensic Psychiatry and Psychotherapy, kbo-Isar-Amper-Clinic Taufkirchen (Vils), 84416 Taufkirchen (Vils), Germany
Irina Franke: Psychiatric Services of Grisons, 7000 Chur, Switzerland
Verena Klein: Department of Forensic Psychiatry and Psychotherapy, kbo-Isar-Amper-Clinic Taufkirchen (Vils), 84416 Taufkirchen (Vils), Germany
Judith Streb: Department of Forensic Psychiatry and Psychotherapy, Ulm University, 89312 Guenzburg, Germany
Manuela Dudeck: Department of Forensic Psychiatry and Psychotherapy, Ulm University, 89312 Guenzburg, Germany

IJERPH, 2023, vol. 20, issue 5, 1-14

Abstract: Female reoffending has long been a neglected research interest. Accordingly, risk assessment instruments were developed based on the criminological knowledge of male recidivism. While feminist researchers have repeatedly criticized the failure to incorporate gender-responsive risk (GR) factors, opinions on the gender neutrality of existing instruments remain inconsistent. In order to substitute the existing literature, while extending the scope to mentally disordered offenders, the aim of the given study was the prediction of general recidivism in a sample of 525 female forensic inpatients who had been discharged from forensic psychiatric care in Germany between 2001 and 2018. Primarily, ROC analysis was conducted to assess the predictive accuracy of the LSI-R. Subsequently, separate binary logistic regression analyses were performed to determine the predictive utility of GR factors on recidivism. Lastly, multiple binary logistic regression was used to assess the incremental validity of the GR factors. The results showed that the GR factors (i.e., intimate relationship dysfunction, mental health issues, parental stress, adult physical abuse, and poverty) significantly contributed to the prediction of recidivism, while a mixed personality disorder, a dissocial personality, an unsupportive partner, and poverty added incremental validity to the predictive accuracy of the LSI-R. However, given that the added variables could only improve classification accuracy by 2.2%, the inclusion of gender-specific factors should be cautiously evaluated.

Keywords: female offenders; recidivism; mental illness; risk factors; gender; risk assessment (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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