Crime forecast

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The crime prognosis is a behavioral prediction about whether a person or a certain group of people will violate the criminal law. In many cases, the crime prognosis is prescribed by the legislature (e.g. when ordering custodial measures, Sections 63, 64, 66 StGB ). The court can commission an expert to prepare a criminal prognostic report and use this to make a decision.

Types of forecasts

Within the crime prognosis, a distinction is made between statistical and clinical prognoses. For the statistical (synonymous: actuarial, nomothetic) prognosis, empirical studies on relapse frequencies and predictors of a corresponding group of perpetrators are used. Rules for assessing the risk of relapse are derived from the results of these investigations. Relevant risk characteristics of the present individual case are ascertained through a survey of the personal history ( anamnesis ), a study of files and a personal conversation with the person. Based on the rules derived, the characteristics of a person with regard to these characteristics are condensed into a numerical relapse probability for the individual case.

The clinical (synonymous: ideographic) prognosis relates to the individual case in the risk assessment. For this purpose, an analysis of the person's résumé and family relationships is carried out as well as a psychiatric-psychological diagnosis based on targeted surveys ( exploration ) and test procedures. An explanatory model for the crime is developed from the collected data, which is then checked for future potential for change. The relapse probability is derived from this potential for change. The intuitive method is to be distinguished from the clinical prognosis. This is based on the unsystematic assessment through subjective experiences of the diagnostician. Due to this unsystematic approach, it should not, strictly speaking, be referred to as a separate “method”, but rather represents a malformed clinical method.

Types of forecasting tools

Within the crime prognosis, different generations of prognostic instruments can be distinguished, which are used to assess the likelihood of relapse. The 1st generation (professional judgment) corresponds to the clinical prognostic method and focuses on the development of an individual explanatory model of the fact (clinical principle). The inclusion of statistical forecasting methods is generally rejected. The 2nd generation comprises the statistical forecasting methods. The focus here is on determining the risk of relapse on the basis of empirical and largely unchangeable (static) risk characteristics, as well as the implementation of interventions for those at risk of relapse (risk principle). The 3rd generation (Structured Professional Judgment) derives test questions or tasks ( test items ) from existing theories and uses changeable (dynamic) risk characteristics. In addition to determining the relapse risk of the 2nd generation, interventions can be geared towards the risk characteristics relevant to the person. As a result, the interventions take into account the individual needs of the person (need principle). In addition, elements of the clinical prognostic method can be found: theory-based test items can provide information for an explanatory model of the clinical prognosis and the determination of dynamic risk factors can be very complex and individual. The fourth generation also takes into account the person's response to the intervention (principle of responsiveness). To assess the response to an intervention, treatment motivation, intellectual abilities and, if applicable, relevant gender-specific factors of the person are recorded. The prognosis of the likelihood of relapse can thus be differentiated with regard to the existence of anticipated conditions (e.g. how does the likelihood of relapse change if the person participates or does not participate in a certain intervention).

The ascending numbering of the generations of forecasting instruments does not represent a replacement for the previous generation. Rather, the different generations consider different issues. Depending on the area of ​​application, the different generations fulfill their task of crime prognosis to varying degrees.

Criticism of forecasting tools

Clinical prognostic instruments take into account the individual characteristics of the individual case, which means that their approach is less structured than that of the statistical prognostic instruments. The assessment of the likelihood of relapse is therefore more dependent on the diagnostician and less objective ( objectivity ). In addition, it places high demands on the diagnostician in terms of time and content. The statistical forecasting methods, on the other hand, can be used in a standardized manner due to their predetermined rules and are more objectivity and transparency. The main points of criticism of statistical forecasting instruments are the lack of a theoretical basis and the use of largely unchangeable (static) risk characteristics. Static risk characteristics are only suitable to a limited extent for deriving interventions, as a change in them is unlikely and cannot be measured. Furthermore, an interpretation of the content of the test items is not permitted for individual cases, as their empirical results refer to the average proportions of a group of people. The criticism that can be derived from this is of little or no importance for the individual case.

To illustrate the importance of statistics for individual cases, Gretenkord provides the following example, in which a patient can choose between two doctors:

"Dr. Wolf operated on 60 patients with great success, while 40 died. At Dr. Fuchs did exactly the opposite: 40 successes and 60 patients died. Who would you like to have? ´

[...] I would like Dr. Prefer wolf.

But then the chief doctor continues:

`Interestingly, when you consider the gender of the patients, things are different.

If you only take the male patients, Dr. Fuchs achieved a success rate of 60%, while of the men named by Dr. Wolf were operated on, only 40% survived.´

Then I would say:

'Why don't you let Dr. Fuchs do the operation. '

The chief physician continues:

`Our statistician found out a few other things. For example, in older patients, Dr. Wolf the better successes. And to this day no patient has survived who was told by Dr. Fuchs had an operation on a Thursday; that could have something to do with the fact that he has his bowling evening on Wednesdays. '

Then I would say:

`Professor, could you perhaps give me all the test results and give me some time to think about it? ´"

- Lutz Gretenkord : Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63, page 9

Taking group statistics into account can therefore be a useful decision-making aid for individual cases, despite their disadvantages.

Overall, prognostic instruments are said to have a hit rate that is too low, which can have far-reaching consequences in the field of crime prognostics: For example, people can falsely receive an unfavorable prognosis even though they do not become delinquent ( alpha error ) or wrongly receive a favorable prognosis and then become delinquent ( beta Error ). However, a prognosis is always a decision under risk, not only in the crime prognosis, but also in every other area. In addition, studies show that the accuracy of clinical and statistical prognostic instruments is higher than the probability of chance. In addition, even the smallest improvements in forecasting are of great practical relevance: According to an example by Gretenkord, with 3000 criminal prognostic decisions per year and an improvement in forecast accuracy of 1%, 30 fewer wrong decisions would be made. It should also be taken into account that the crime prognosis is not the only aspect that is used for the decision by the court. So come z. B. also the weighing of legal interests and the proportionality principle are used.

Regardless of the different prognostic methods and schools of psychodiagnostics, the best possible methods available for prognosis should always be used. In order to guarantee this, the latest scientific knowledge must be used. The relapse rates from empirical studies are therefore the best estimates currently available. In relation to the different types of prognosis, the statistical prognosis methods are more accurate than the clinical ones. If the recidivism rate for the present individual case is assessed on the basis of the corresponding group of perpetrators and statistical prognostic instruments and a clinical prognosis is then made based on a scientific procedure, the combination of statistical and clinical prognostic methods can exceed the accuracy of each method separately.

literature

Web links

Individual evidence

  1. ↑ Norbert Nedopil: Prognoses in Forensic Psychiatry - A Handbook for Practice. Pabst, Lengerich 2005, ISBN 978-3-89967-216-9 . Quoted from Lutz Gretenkord: Why forecasting instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.
  2. ↑ a b c d e Lutz Gretenkord: Why forecasting instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.
  3. ↑ a b c d Klaus-Peter Dahle: Criminal (relapse) prognosis. In: Renate Volbert, Max Steller (Hrsg.): Handbuch der Rechtsspsychologie. Hogrefe, Göttingen 2008, ISBN 978-3-8017-1851-0 , pp. 444-452.
  4. ^ A b c Hans Joachim Schneider: Prognostic assessment of the lawbreaker: The foreign research. In: Udo Undeutsch (Ed.): Handbuch der Psychologie. Volume 11, Hogrefe, Göttingen 1967, pp. 397-510. Quoted from Lutz Gretenkord: Why forecasting instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.
  5. ↑ a b c d Klaus-Peter Dahle: Basics of the crime prognosis. 2008, pp. 51-83. [1]  ( Page no longer available , search in web archives )  Info: The link was automatically marked as defective. Please check the link according to the instructions and then remove this notice.@1@ 2Template: Toter Link / www.uni-heidelberg.de  
  6. ^ A b Hans-Georg Mey: Prognostic assessment of the lawbreaker: The German research. In: Udo Undeutsch (Ed.): Handbuch der Psychologie. Volume 11, Hogrefe, Göttingen 1967, pp. 511-564. Quoted from Lutz Gretenkord: Why forecasting instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.
  7. ↑ a b c d e f Lutz Gretenkord: Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63. Deutscher Psychologen Verlag, 2001, ISBN 3-931589-39-0 .
  8. ↑ Donald Arthur Andrews, James Bonta: The Psychology of Criminal Conduct. 4th edition. Anderson, Cincinnati 2006. Quoted from Lutz Gretenkord: Why prognostic instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.
  9. ^ A b Douglas Mossman: Assessing Predictions of Violence: Being Accurate about Accuracy. In: Journal of Consulting and Clinical Psychology. 62, 1994, pp. 783-792. Quoted from Lutz Gretenkord: Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63. Deutscher Psychologen Verlag, 2001, ISBN 3-931589-39-0 .
  10. ↑ Axel Boetticher, Hans-Ludwig Kröber, Rüdiger Müller-Isberner, Klaus M. Bohm, Reinhard Müller-Metz, Thomas Wolf: Minimum requirements for prognostic reports. In: New journal for criminal law. 10, 2006, pp. 537-543. [2]
  11. ↑ James Bonta, Moira Law, Karl Hanson: The Prediction of Criminal and Violent Recidivism among Mentally Disordered Offenders: A Meta-Analysis. In: Psychological Bulletin. 123, No. 2, 1998, pp. 123-142. Quoted from Lutz Gretenkord: Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63. Deutscher Psychologen Verlag, 2001, ISBN 3-931589-39-0 .
  12. ^ William M. Grove, Paul E. Meehl: Comparative Efficiency of Informal (Subjective, Impressionistic) and Formal (Mechanical, Algorithmic) Prediction Procedures: The Clinical Statistical Controversy. In: Psychology, Public Policy, and Law. 2, 1996, pp. 293-323. Quoted from Lutz Gretenkord: Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63. Deutscher Psychologen Verlag, 2001, ISBN 3-931589-39-0 .
  13. ^ R. Karl Hanson, Monique T. Bussière: Predicting Relapse: A Meta-Analysis of Sexual Offender Recidivism. In: Journal of Clinical and Consulting Psychology. 66, 1998, pp. 348-362. Quoted from Lutz Gretenkord: Empirically sound forecasting in the penal system according to § 63 StGB: EFP-63. Deutscher Psychologen Verlag, 2001, ISBN 3-931589-39-0 .
  14. ↑ Klaus-Peter Dahle: Psychological crime prognosis. Towards an integrative methodology for assessing the likelihood of recidivism in prisoners. Centaurus, Pfaffenweiler 2005. Quoted from Lutz Gretenkord: Why forecasting instruments? In: Martin Rettenberger and Fritjof von Franqué: Handbook of criminal prognostic procedures. Hogrefe, 2013, ISBN 978-3-8017-2393-4 , pp. 19-36.