Dataset Information

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime.

ABSTRACT:

Background

Children with antisocial behaviour show deficits in the perception of emotional expressions in others that may contribute to the development and persistence of antisocial and aggressive behaviour. Current treatments for antisocial youngsters are limited in effectiveness. It has been argued that more attention should be devoted to interventions that target neuropsychological correlates of antisocial behaviour. This study examined the effect of emotion recognition training on criminal behaviour.

Methods

Emotion recognition and crime levels were studied in 50 juvenile offenders. Whilst all young offenders received their statutory interventions as the study was conducted, a subgroup of twenty-four offenders also took part in a facial affect training aimed at improving emotion recognition. Offenders in the training and control groups were matched for age, SES, IQ and lifetime crime level. All offenders were tested twice for emotion recognition performance, and recent crime data were collected after the testing had been completed.

Results

Before the training there were no differences between the groups in emotion recognition, with both groups displaying poor fear, sadness and anger recognition. After the training fear, sadness and anger recognition improved significantly in juvenile offenders in the training group. Although crime rates dropped in all offenders in the 6 months following emotion testing, only the group of offenders who had received the emotion training showed a significant reduction in the severity of the crimes they committed.

Conclusions

The study indicates that emotion recognition can be relatively easily improved in youths who engage in serious antisocial and criminal behavior. The results suggest that improved emotion recognition has the potential to reduce the severity of reoffending.

SUBMITTER: Hubble K

PROVIDER: S-EPMC4486167 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime.

Hubble Kelly K Bowen Katharine L KL Moore Simon C SC van Goozen Stephanie H M SH

PloS one 20150629 6

<h4>Background</h4>Children with antisocial behaviour show deficits in the perception of emotional expressions in others that may contribute to the development and persistence of antisocial and aggressive behaviour. Current treatments for antisocial youngsters are limited in effectiveness. It has been argued that more attention should be devoted to interventions that target neuropsychological correlates of antisocial behaviour. This study examined the effect of emotion recognition training on cr ...[more]

PMID: 26121148

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Project description:Introduction: Deficits in Emotion Recognition (ER) contribute significantly to poorer functional outcomes in people with schizophrenia. However, rather than reflecting a core symptom of schizophrenia, reduced ER has been suggested to reflect increased mood disorder co-morbidity and confounds of patient status such as medication. We investigated whether ER deficits are replicable in psychometrically defined schizotypy, and whether this putative association is mediated by increased negative affect. Methods: Two hundred and nine participants between the ages of 18 and 69 (66% female) were recruited from online platforms: 80% held an undergraduate qualification or higher, 44% were current students, and 46% were in current employment. Participants were assessed on psychometric schizotypy using the O-LIFE which maps onto the same symptoms structure (positive, negative, and disorganised) as schizophrenia. Negative affect was assessed using the Depression Anxiety and Stress Scale (DASS-21). Emotion Recognition of both positive and negative emotions was assessed using the short version of the Geneva Emotion Recognition Task (GERT-S). Results: Negative schizotypy traits predicted poorer ER accuracy to negative emotions (β = -0.192, p = 0.002) as predicted. Unexpectedly, disorganised schizotypy traits predicted improved performance to negative emotions (β = 0.256, p = 0.007) (primarily disgust). Negative affect was found to be unrelated to ER performance of either valence (both p > 0.591). No measure predicted ER accuracy of positive emotions. Positive schizotypy traits were not found to predict either positive or negative ER accuracy. However, positive schizotypy predicted increased confidence in decisions and disorganised schizotypy predicted reduced confidence in decisions. Discussion: The replication of ER deficits in non-clinical negative schizotypy suggests that the association between negative symptoms and ER deficits in clinical samples may be independent of confounds of patient status (i.e., anti-psychotic medication). The finding that this association was independent of negative affect further suggests ER deficits in patients may also be independent of mood disorder co-morbidity. This association was not demonstrated for the positive symptom dimension of the O-LIFE, which may be due to low levels of this trait in the current sample.

Project description:BackgroundSuffering from schizophrenia spectrum disorder (SSD) has been well-established as a risk factor for offending. However, the majority of patients with an SSD do not show aggressive or criminal behavior. Yet, there is little research on clinical key features distinguishing offender from non-offender patients. Previous results point to poorer impulse control, higher levels of excitement, tension, and hostility, and worse overall cognitive functioning in offender populations. This study aimed to detect the most indicative distinguishing clinical features between forensic and general psychiatric patients with SSD based on the course of illness and the referenced hospitalization in order to facilitate a better understanding of the relationship between violent and non-violent offenses and SSD.MethodsOur study population consisted of forensic psychiatric patients (FPPs) with a diagnosis of F2x (ICD-10) or 295.x (ICD-9) and a control group of general psychiatric patients (GPPs) with the same diagnosis, totaling 740 patients. Patients were evaluated regarding their medical (and, if applicable, criminal) history and the referenced psychiatric hospitalization. Supervised machine learning (ML) was used to exploratively evaluate predictor variables and their interplay and rank them in accordance with their discriminative power.ResultsOut of 194 possible predictor variables, the following 6 turned out to have the highest influence on the model: olanzapine equivalent at discharge from the referenced hospitalization, a history of antipsychotic prescription, a history of antidepressant, benzodiazepine or mood stabilizer prescription, medication compliance, outpatient treatment(s) in the past, and the necessity of compulsory measures. Out of the seven algorithms applied, gradient boosting emerged as the most suitable, with an AUC of 0.86 and a balanced accuracy of 77.5%.DiscussionOur study aimed to identify the most influential illness-related predictors, distinguishing between FPP and GPP with SSD, thus shedding light on key differences between the two groups. To our knowledge, this is the first study to compare a homogenous sample of FPP and GPP with SSD regarding their symptom severity and course of illness using highly sophisticated statistical approaches with the possibility of evaluating the interplay of all factors at play.

Dataset Information

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime.

Background

Methods

Results

Conclusions

Publications

Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime.

Similar Datasets

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