Forensische Psychiatrie zwischen Therapie und Sicherung

Tribolet-Hardy, Fanny de; Habermeyer, Elmar

doi:10.1007/s11757-016-0385-0

Cited by 6 publications

(5 citation statements)

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“…In addition, doubts have been raised about the benefits of prolonged inpatient treatment for patients' rehabilitation [3,7]. Prolonged duration of inpatient treatment has been discussed as an indicator of economic inefficiencyparticularly for forensic inpatient treatment, which constitutes a low-volume high-cost sector [3,[8][9][10][11][12][13][14]. The internationally observed prolongation of forensic hospitalizations in the past years [1,3,7,[15][16][17], as well as the ever-growing demand for forensic services [18][19][20][21], have become a subject of sociopolitical debate with urgent need for more research on avenues to reduce the duration of inpatient treatments in order to reduce exploding costs whenever possible [2,4].…”

Section: Introductionmentioning

confidence: 99%

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach

et al. 2020

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Background: Prolonged forensic psychiatric hospitalizations have raised ethical, economic, and clinical concerns. Due to the confounded nature of factors affecting length of stay of psychiatric offender patients, prior research has called for the application of a new statistical methodology better accommodating this data structure. The present study attempts to investigate factors contributing to long-term hospitalization of schizophrenic offenders referred to a Swiss forensic institution, using machine learning algorithms that are better suited than conventional methods to detect nonlinear dependencies between variables. Methods: In this retrospective file and registry study, multidisciplinary notes of 143 schizophrenic offenders were reviewed using a structured protocol on patients' characteristics, criminal and medical history and course of treatment. Via a forward selection procedure, the most influential factors for length of stay were preselected. Machine learning algorithms then identified the most efficient model for predicting length-of-stay. Results: Two factors have been identified as being particularly influential for a prolonged forensic hospital stay, both of which are related to aspects of the index offense, namely (attempted) homicide and the extent of the victim's injury. The results are discussed in light of previous research on this topic. Conclusions: In this study, length of stay was determined by legal considerations, but not by factors that can be influenced therapeutically. Results emphasize that forensic risk assessments should be based on different evaluation criteria and not merely on legal aspects.

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Section: Introductionmentioning

confidence: 99%

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach

et al. 2020

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“…In addition, doubts have been raised about the benefits of prolonged inpatient treatment for patients' rehabilitation (3,7). Prolonged duration of inpatient treatment has been discussed as an indicator of economic inefficiency -particularly for forensic inpatient treatment, which constitutes a low-volume high-cost sector (3,(8)(9)(10)(11)(12)(13)(14). The internationally observed prolongation of forensic hospitalizations in the past years (1,3,7,(15)(16)(17), as well as the ever-growing demand for forensic services (18)(19)(20)(21), have become a subject of socio-political debate with urgent need for more research on avenues to reduce the duration of inpatient treatments in order to reduce exploding costs whenever possible (2,4).…”

Section: Background and Objectivesmentioning

confidence: 99%

Factors And Predictors Of Length Of Stay In Offenders Diagnosed With Schizophrenia- A Machine-learning-based Approach

Kirchebner

Günther

King

et al. 2020

Preprint

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Background Prolonged forensic psychiatric hospitalizations have raised ethical, economic, and clinical concerns. Due to the confounded nature of factors affecting length of stay of psychiatric offender patients, prior research has called for the application of a new statistical methodology better accommodating this data structure. The present study seeks to examine factors responsible for prolonged detentions of schizophrenic offenders referred to a Swiss forensic hospital using machine learning algorithms more apt to reveal non-linear interdependencies between variables.Methods In this retrospective file and registry study, multidisciplinary notes of 143 schizophrenic delinquents were reviewed by using a structured protocol on patients’ characteristics, criminal and medical history and course of treatment. Via a forward selection procedure, the most influential predictors for length of stay were preselected. Machine learning algorithms identified the most efficient model for predicting length-of-stay.Results/ Conclusions Ten factors prolonging forensic hospitalization were identified: Six were related to aspects of the index offence (index offence, number of crimes, extend of injury to the victim of the offence), two were related to psychopathology at admission or even prior to that (hallucinations in psychiatric history), one alluded to the course of therapy (self-harming during inpatient treatment), and one referred to biographical aspects (poverty during childhood/ adolescence). Results are discussed in light of earlier reports on the subject.

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“…Während suchtkranke Untergebrachte in der Regel maximal 2 Jahre im Maßregelvollzug verbleiben, liegt die mittlere Unterbringungsdauer für psychisch kranke Straftäterinnen und Straftäter bei ca. sechseinhalb Jahren (de Tribolet-Hardy und Habermeyer 2016 ; Dessecker 2008 ). Dementsprechend befinden sich im Maßregelvollzug Untergebrachte oft lange Zeit in ihren Einrichtungen und sind den einhergehenden Einschränkungen über lange Zeiträume ausgesetzt, weswegen (3) ein Einfluss der Unterbringungsdauer auf die Depressivität untersucht wurde.…”

Section: Introductionunclassified

Eine hohe Lebensqualität reduziert depressive Symptome von Maßregelvollzugspatientinnen und -patienten

Bortenschlager

Büsselmann

Wolstein

2022

Forens Psychiatr Psychol Kriminol

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Zusammenfassung Einleitung Die restriktiven Unterbringungsbedingungen im Maßregelvollzug beeinflussen die Lebensqualität und Depressivität der Untergebrachten und damit die psychische Gesundheit und den Behandlungserfolg therapeutischer Maßnahmen. Ziele Ziel der Arbeit ist es, eine Übersicht über die Lebensqualität und die Belastung durch depressive Symptome aus Patientensicht zu erhalten. Es soll analysiert werden, welche Bereiche der Lebensqualität im Zusammenhang mit Depressivität stehen, und ob die Dauer der Maßregel Einfluss auf die Depressivität der Untergebrachten nimmt. Methode Die Lebensqualität wurde mittels einer an die Gegebenheiten des Maßregelvollzugs adaptierten Version des Fragebogens Measuring the Quality of Prison Life (MQPL) erhoben. Depressivität wurde anhand der Allgemeinen Depressionsskala (ADS) erfragt. Insgesamt nahmen N = 73 Personen an der Studie teil. Ergebnisse Die Lebensqualität wurde im Mittel als positiv bewertet. Am höchsten wurde die Beziehung zum therapeutischen Personal eingeschätzt. Es zeigten sich signifikante Unterschiede in der Lebensqualität zwischen depressiv auffälligen und nichtauffälligen Untergebrachten. Die Dauer der Unterbringung war signifikanter Prädiktor für die Depressionswerte suchterkrankter Untergebrachter. Fazit Lebensqualität und Depressivität stehen in signifikant negativem Zusammenhang. Zur Verbesserung der Unterbringungs- und Versorgungsqualität sollte das Klinikpersonal die Lebensqualität der Untergebrachten in den identifizierten Bereichen bestmöglich fördern und besonders zum Aufnahmezeitpunkt sowie bei längeren Behandlungsdauern depressive Symptome identifizieren und behandeln. Hierbei sollte ein Augenmerk auf das Erreichen einer stabilen therapeutischen Allianz gelegt werden.

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Forensische Psychiatrie zwischen Therapie und Sicherung

Cited by 6 publications

References 43 publications

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach

Factors And Predictors Of Length Of Stay In Offenders Diagnosed With Schizophrenia- A Machine-learning-based Approach

Eine hohe Lebensqualität reduziert depressive Symptome von Maßregelvollzugspatientinnen und -patienten

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