Predicting general criminal recidivism in mentally disordered offenders using a random forest approach

BMC Psychiatry

Henning Hachtel¹  Marc Graf¹  Irina Franke¹  Marlon O Pflueger¹ 

[1] Department of Forensic Psychiatry, University Psychiatric Clinics, Wilhelm Klein-Str. 27, Basel, CH-4012, Switzerland

关键词: Prediction;    Risk assessment;    Mentally disordered offenders;    Criminal recidivism;   

Others  :  1164378
DOI  :  10.1186/s12888-015-0447-4

 received in 2014-10-23, accepted in 2015-03-18,  发布年份 2015

【 摘 要 】

Background

Psychiatric expert opinions are supposed to assess the accused individual’s risk of reoffending based on a valid scientific foundation. In contrast to specific recidivism, general recidivism has only been poorly considered in Continental Europe; we therefore aimed to develop a valid instrument for assessing the risk of general criminal recidivism of mentally ill offenders.

Method

Data of 259 mentally ill offenders with a median time at risk of 107 months were analyzed and combined with the individuals’ criminal records. We derived risk factors for general criminal recidivism and classified re-offences by using a random forest approach.

Results

In our sample of mentally ill offenders, 51% were reconvicted. The most important predictive factors for general criminal recidivism were: number of prior convictions, age, type of index offence, diversity of criminal history, and substance abuse. With our statistical approach we were able to correctly identify 58-95% of all reoffenders and 65-97% of all committed offences (AUC = .90).

Conclusions

Our study presents a new statistical approach to forensic-psychiatric risk-assessment, allowing experts to evaluate general risk of reoffending in mentally disordered individuals, with a special focus on high-risk groups. This approach might serve not only for expert opinions in court, but also for risk management strategies and therapeutic interventions.

【 授权许可】

   
2015 Pflueger et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

• [1]Stadtland C, Nedopil N: Psychiatrische Erkrankungen und die Prognose krimineller Rückfälligkeit. Nervenarzt 2005, 76:1402-11.
• [2]Pham TH, Ducro C, Marghem B, Réveillère C: Évaluation du risque de récidive au sein d’une population de délinquants incarcérés ou internés en Belgique francophone. Ann Méd-Psychol Rev Psychiatr 2005, 163:842-5.
• [3]Kröner C, Stadtland C, Eidt M, Nedopil N: The validity of the Violence Risk Appraisal Guide (VRAG) in predicting criminal recidivism. Crim Behav Ment Health 2007, 17:89-100.
• [4]Walter M, Wiesbeck GA, Dittmann V, Graf M: Criminal recidivism in offenders with personality disorders and substance use disorders over 8 years of time at risk. Psychiatry Res 2011, 186:443-5.
• [5]Urbaniok F, Noll T, Grunewald S, Steinbach J, Endrass J: Prediction of violent and sexual offences: a replication study of the VRAG in Switzerland. J Forensic Psychiatry Psychol 2006, 17:23-31.
• [6]Håkansson A, Berglund M: Risk factors for criminal recidivism – a prospective follow-up study in prisoners with substance abuse. BMC Psychiatry 2012, 12:111. BioMed Central Full Text
• [7]Dressing H, Salize HJ: Forensic psychiatric assessment in European Union member states. Acta Psychiatr Scand 2006, 114:282-9.
• [8]Boetticher A, Kröber HL, Müller-Isberner R, Müller-Metz R, Wolf T: Mindestanforderungen für Prognosegutachten. Forens Psychiatr Psychol Kriminol 2007, 1:90-100.
• [9]Quinsey VL, Harris GT, Rice ME, Cornier CA: Violent Offenders: Appraising and Managing Risk. 2nd edition. American Psychological Association, Washington, DC, US; 2006.
• [10]Rossegger A, Gerth J, Seewald K, Urbaniok F, Singh JP, Endrass J: Current obstacles in replicating risk assessment findings: a systematic review of commonly used actuarial instruments. Behav Sci Law 2013, 31:154-64.
• [11]Müller JL, Nedopil N: Forensische Psychiatrie: Klinik. Begutachtung Und Behandlung Zwischen Psychiatrie Und Recht, Georg Thieme Verlag; 2012.
• [12]Hanson KR, Morton-Bourgon KE: The accuracy of recidivism risk assessments for sexual offenders: a meta-analysis of 118 prediction studies. Psychol Assess 2009, 21:1-21.
• [13]Långström N, Grann M: Psychopathy and violent recidivism among young criminal offenders. Acta Psychiatr Scand 2002, 106:86-92.
• [14]Hall DL, Miraglia RP, Lee L-WG, Chard-Wierschem D, Sawyer D: Predictors of general and violent recidivism among SMI prisoners returning to communities in New York State. J Am Acad Psychiatry Law Online 2012, 40:221-31.
• [15]Bonta J, Law M, Hanson K: The prediction of criminal and violent recidivism among mentally disordered offenders: a meta-analysis. Psychol Bull 1998, 123:123-42.
• [16]Lovell D, Gagliardi GJ, Peterson PD: Recidivism and use of services among persons with mental illness after release from prison. Psychiatr Serv 2002, 53:1290-6.
• [17]Dietiker J, Dittmann V, Graf DM: Gutachterliche Risikoeinschätzung bei Sexualstraftätern. Nervenarzt 2007, 78:53-61.
• [18]Breiman L, Friedman J, Stone CJ, Olshen RA: Classification and Regression Trees. Chapman & Hall/CRC press, New York; 1984.
• [19]Breiman L: Random forests. Mach Learn 2001, 45:5-32.
• [20]Ishwaran H, Kogalur UB, Blackstone EH, Lauer MS: Random survival forests. Ann Appl Stat 2008, 2:841-60.
• [21]Genuer R, Poggi J-M, Tuleau-Malot C: Variable selection using random forests. Pattern Recognit Lett 2010, 31:2225-36.
• [22]Strobl C, Boulesteix A-L, Kneib T, Augustin T, Zeileis A: Conditional variable importance for random forests. BMC Bioinformatics 2008, 9:1-11. BioMed Central Full Text
• [23]Gendreau P, Little T, Goggin C: A meta-analysis of the predictors of adult offender recidivism: what works!*. Criminology 1996, 34:575-608.
• [24]Urbaniok F, Endrass J: Prävention Und Opferschutz: Wirksamkeit Und Kosteneffizienz Spezifisch Deliktpräventiver Therapieangebote Zur Verhinderung von Gewalt-Und Sexualstraftaten. 2011.
• [25]Rice ME, Harris GT, Lang C: Validation of and revision to the VRAG and SORAG: The Violence Risk Appraisal Guide—Revised (VRAG-R). Psychol Assess 2013, 25:951.