USING THE MMPI-A TO PREDICT RECIDIVISM IN ADJUDICATED MINORS (original) (raw)
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The Prediction of Criminal Recidivism in Juveniles
2004
368 CRIMINAL JUSTICE AND BEHAVIOR 1998, accounted for 18% of all persons arrested in 1998, and are among the fastest growing groups of offenders (FBI, 1998). The per-centage of offenses committed by children and adolescents increased by 24% from 1989 to 1998, ...
Criminal Behaviour and Mental Health, 2010
Background There has been a lot of research on risk factors for recidivism among juvenile offenders, in general, and on individual risk factors, but less focus on subgroups of serious juvenile offenders and prediction of recidivism within these.Objective To find an optimal classification of risk items and to test the predictive value of the resultant factors with respect to severity of recidivism among serious juvenile offenders.Method Seventy static and dynamic risk factors in 1154 juvenile offenders were registered with the Juvenile Forensic Profile. Recidivism data were collected on 728 of these offenders with a time at risk of at least 2 years. After factor analysis, independent sample t-tests were used to indicate differences between recidivists and non-recidivists. Logistic multiple linear regression analyses were used to test the potential predictive value of the factors for violent or serious recidivism.Results A nine-factor solution best accounted for the data. The factors were: antisocial behaviour during treatment, sexual problems, family problems, axis-1 psychopathology, offence characteristics, conscience and empathy, intellectual and social capacities, social network, and substance abuse. Regression analysis showed that the factors antisocial behaviour during treatment, family problems and axis-1 psychopathology were associated with seriousness of recidivism.Conclusions and implications for practice The significance of family problems and antisocial behaviour during treatments suggest that specific attention to these factors may be important in reducing recidivism. The fact that antisocial behaviour during treatment consists mainly of dynamic risk factors is hopeful as these can be influenced by treatment. Consideration of young offenders by subgroup rather than as a homogenous population is likely to yield the best information about risk of serious re-offending and the management of that risk. Copyright © 2010 John Wiley & Sons, Ltd.
The Prediction of Criminal Recidivism in Juveniles: A Meta-Analysis
Criminal Justice and Behavior, 2001
We used meta-analysis to identify variables that are most strongly associated with recidivism rates among juvenile offenders for two outcomes: sexual reoffending and violent reoffending. A total of 9 published studies representing 1,160 participants met inclusion criteria for sexual reoffending among juveniles. Among studies examining violent juvenile reoffending, a total of 4 studies, representing 380 participants, met inclusion criteria. For sexual offense recidivism, predictor variables were grouped into three categories: 1) offense history variables, 2) family/social factors, and 3) intervention variables. Among studies examining violent juvenile offenders, only one used violent reoffending as an outcome variable; the remaining studies focused on any reoffending among violent juvenile offenders. For the "any recidivism" outcome among violent non-sexual offenders, only a single variable could be compared among studies -a composite variable, encompassing various treatment interventions, which was created for this meta-analysis. Effect sizes were calculated for this variable for both sexual and violent juvenile offenders, respectively. For juvenile sexual reoffending, predictors were compared within and across each of the three categories for their impact on reducing recidivism.
Risk Factors for Overall Recidivism and Severity of Recidivism in Serious Juvenile Offenders
International Journal of Offender Therapy and Comparative Criminology, 2011
Unraveling serious juvenile delinquency: risk and needs assessment by classifi cation into subgroups Thesis Erasmus MC, University Medical Center Rotterdam, with references, with summary in Dutch ISBN 978-90-8559-952-4 On the cover: the Dutch windpowered sawmill 'De Herder' (Leiden, 1884). My greatgreat-great-great-grandfather Julianus Mulder owned this mill. The familyname 'Mulder' is the old Dutch word for 'miller' . 'De Herder' was on the cover of the dissertation of my father Martyn Mulder as well. Design by Marcel Klijn. Risk and needs assessment by classifi cation into subgroups Ernstige jeugdcriminaliteit ontrafeld: risk en needs assessment door middel van classifi catie in subgroepen Proefschrift ter verkrijging van de graad van doctor aan de Erasmus Universiteit Rotterdam op gezag van de rector magnifi cus
Recidivism in subgroups of serious juvenile offenders: Different profiles, different risks?
Criminal Behaviour and Mental Health, 2012
Background Research has shown that the treatment of juvenile offenders is most effective when it takes into account the possible risk factors for re-offending. It may be asked whether juvenile offenders can be treated as one homogeneous group, or, if they are divisible into subgroups, whether different risk factors are predictive of recidivism.
Juvenile offenders assessment current opinion 2011 (1)
Evaluation of juveniles is an integral process that includes a broad bio-psychosocial clinical perspective together with the use of auxiliary instruments. The aim of this article is to report relevant issues for this process found in recent publications.
The prediction of criminal recidivism in male juvenile delinquents
Psihologija, 2019
Previous studies have demonstrated a strong association of criminal behavior of juvenile delinquents with delinquents' personality traits and family interactions. However, little is known about the extent to which family interactions and personality traits are associated with criminal recidivism. The present study aimed to examine these relationships, using the Velikih pet plus dva (Big Five Plus Two)-short version (assessing Neuroticism, Extraversion, Openness to experience, Conscientiousness, Aggressiveness, Positive Valence, Negative Valence), The Quality of Family Interaction Scale (Satisfaction with family, Mother and Father Acceptance/Rejection), and official data from criminal records. The study included 61 institutionalized delinquents and 64 non-delinquents, 15 to 18 years of age. Neuroticism, Openness to experience, Conscientiousness, Negative valence, acceptance by father and rejection by mother are statistically significant predictors of criminal recidivism in juvenile delinquents. Delinquents showed higher Neuroticism, lower Conscientiousness and acceptance by mother compared to non-delinquents.
American Journal of Criminal Justice, 1999
One of the most well-known statistical findings in delinquency research is from , who found that just over half (51.9%) of all officially recorded delinquent acts by males in a Philadelphia male birth cohort were the responsibility of only 6% of them. If it is generally true that only 6% are responsible for half the crime, it may be efficient to identify, treat, and prevent their delinquent acts by concentrating juvenile justice resources on a small subset of offenders. The magnitude of the "chronic recidivist" population, as the 6% came to be known, must be gauged, however, relative to the size of the juvenile justice system and its ability to learn about, apprehend, and treat juvenile delinquents. While half of all delinquent acts may be accounted for by 6% of a birth cohort, this represents 18% of all juveniles apprehended. Bringing about desistance in the budding delinquent careers of 18% sounds more difficult than 6%, even though it represents the same number of individuals: 627 boys in the Philadelphia study who were responsible for 5,305 offenses.
Psychiatric evaluation of juvenile delinquents under probation in the context of recidivism
Psychiatry and Clinical Psychopharmacology, 2018
OBJECTIVE: High rates of psychiatric disorders and comorbidities have been reported in the juvenile justice system, and both phenomena are thought to contribute to repetitive offending. Although extensive research on the prevalence of psychiatric disorders in juvenile offenders has been conducted in European countries and the USA, epidemiological research concerning this issue is limited in Turkish population. The aim of the present study is to examine psychiatric diagnoses, comorbidity patterns, psychometric properties, and the factors related to recidivism defined as reconvictions, in juveniles under probation in Turkey. METHODS: We conducted face-to-face interviews with volunteers. This study sample consisted of 55 individuals (Female/Male = 4/51) who were in the Istanbul Anatolian Probation Department. The participants' age ranged from 14 to 18 years (mean age = 17.22 ± 0.62). Diagnoses were established based on the Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime Version. A detailed sociodemographic form, Wechsler Intelligence Scale, Child Depression Inventory, and Beck Anxiety Inventory were used for assessment. The subjects were divided into two groups based on the number of conviction: Group 1 consisted of 65% of the sample (n = 36) with one conviction and Group 2 consisted of 35% of the sample (n = 19) with more than one conviction. We examined the psychometric properties that might predict recidivism through the logistic regression analysis. RESULTS: We ascertained that 67.3% of the juveniles had at least one psychiatric disorder, and 45.5% had two or more comorbid psychiatric disorders. The most common diagnosis was attention deficit hyperactivity disorder (ADHD) (43.6%), and followed by depressive mood disorders (34.5%). Juveniles in Group 2 were less educated, had low levels of verbal, performance and total intelligence quotient (IQ) score, had more numbers of psychiatric diagnoses, particularly depressive mood disorders and history of substance use disorders (p < .05). Having a higher number of psychiatric diagnoses and having comorbidity of both externalizing (i.e. ADHD, conduct disorder) and internalizing disorders (i.e. depressive mood disorders, anxiety disorders) were significantly higher in Group 2 (p < .05). Total duration of education (OR = 0.470, 95% CI = 0.257-0.861, p < .05) and having at least one psychiatric disorder (OR = 10.64, 95% CI = 1.642-68.954, p < .05) were found to predict multiple convictions. CONCLUSION: Juveniles in the justice system are faced with multiple psychiatric disorders, along with social/environmental adversities. There is a need of a holistic approach addressing multiple areas to prevent repetitive offending behaviour. Accordingly, in addition to legal sanctions, evaluation and interventions regarding mental health will contribute to improve for both psychosocial well-being of delinquent juveniles and prevention strategies for recidivism.
International journal of offender therapy and comparative criminology, 2010
The aim of this study was to identify subgroups of serious juvenile offenders on the basis of their risk profiles, using a data-driven approach. The sample consists of 1,147 of the top 5% most serious juvenile offenders in the Netherlands. A part of the sample, 728 juvenile offenders who had been released from the institution for at least 2 years, was included in analyses on recidivism and the prediction of recidivism. Six subgroups of serious juvenile offenders were identified with cluster analysis on the basis of their scores on 70 static and dynamic risk factors: Cluster 1, antisocial identity; Cluster 2, frequent offenders; Cluster 3, flat profile; Cluster 4, sexual problems and weak social identity; Cluster 5, sexual problems; and Cluster 6, problematic family background. Clusters 4 and 5 are the most serious offenders before treatment, committing mainly sex offences. However, they have significantly lower rates of recidivism than the other four groups. For each of the six clusters, a unique set of risk factors was found to predict severity of recidivism. The results suggest that intervention should aim at different risk factors for each subgroup.