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Exploring Similarities and Differences of Non-European Migrants among Forensic Patients with Schizophrenia

Author

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  • David A. Huber

    (Department of Forensic Psychiatry, Psychiatric Hospital, University of Zürich, 8006 Zurich, Switzerland
    D.A.H. and S.L. contributed equally to the work presented here and should therefore be regarded as equivalent authors.)

  • Steffen Lau

    (Department of Forensic Psychiatry, Psychiatric Hospital, University of Zürich, 8006 Zurich, Switzerland
    D.A.H. and S.L. contributed equally to the work presented here and should therefore be regarded as equivalent authors.)

  • Martina Sonnweber

    (Department of Forensic Psychiatry, Psychiatric Hospital, University of Zürich, 8006 Zurich, Switzerland)

  • Moritz P. Günther

    (Department of Consultation-Liaison-Psychiatry and Psychosomatic Medicine, University Hospital Zurich, 8091 Zurich, Switzerland)

  • Johannes Kirchebner

    (Department of Forensic Psychiatry, Psychiatric Hospital, University of Zürich, 8006 Zurich, Switzerland)

Abstract

Migrants diagnosed with schizophrenia are overrepresented in forensic-psychiatric clinics. A comprehensive characterization of this offender subgroup remains to be conducted. The present exploratory study aims at closing this research gap. In a sample of 370 inpatients with schizophrenia spectrum disorders who were detained in a Swiss forensic-psychiatric clinic, 653 different variables were analyzed to identify possible differences between native Europeans and non-European migrants. The exploratory data analysis was conducted by means of supervised machine learning. In order to minimize the multiple testing problem, the detected group differences were cross-validated by applying six different machine learning algorithms on the data set. Subsequently, the variables identified as most influential were used for machine learning algorithm building and evaluation. The combination of two childhood-related factors and three therapy-related factors allowed to differentiate native Europeans and non-European migrants with an accuracy of 74.5% and a predictive power of AUC = 0.75 (area under the curve). The AUC could not be enhanced by any of the investigated criminal history factors or psychiatric history factors. Overall, it was found that the migrant subgroup was quite similar to the rest of offender patients with schizophrenia, which may help to reduce the stigmatization of migrants in forensic-psychiatric clinics. Some of the predictor variables identified may serve as starting points for studies aimed at developing crime prevention approaches in the community setting and risk management strategies tailored to subgroups of offenders with schizophrenia.

Suggested Citation

  • David A. Huber & Steffen Lau & Martina Sonnweber & Moritz P. Günther & Johannes Kirchebner, 2020. "Exploring Similarities and Differences of Non-European Migrants among Forensic Patients with Schizophrenia," IJERPH, MDPI, vol. 17(21), pages 1-15, October.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:7922-:d:436376
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    References listed on IDEAS

    as
    1. Milo Bianchi & Paolo Buonanno & Paolo Pinotti, 2012. "Do Immigrants Cause Crime?," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1318-1347, December.
    2. repec:dau:papers:123456789/5382 is not listed on IDEAS
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    4. Brian Bell & Francesco Fasani & Stephen Machin, 2013. "Crime and Immigration: Evidence from Large Immigrant Waves," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1278-1290, October.
    5. Judith W. Spain & Peggy Brewer & Virgil Brewer & S. J. Garner, 2002. "Ethics and Geography –Impact of Geographical Cultural Differences on Students Ethical Decisions," Journal of Business Ethics, Springer, vol. 41(1), pages 187-194, November.
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