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Cadernos de Saúde Pública

versão impressa ISSN 0102-311Xversão On-line ISSN 1678-4464

Cad. Saúde Pública vol.31 no.12 Rio de Janeiro dez. 2015 


Factors associated with recidivism among adolescents girls in conflict with the law in an institution in Brasília, Federal District, Brazil

Fatores associados à reincidência entre adolescentes femininas em conflito com a lei de uma instituição de Brasília, Distrito Federal, Brasil

Factores asociados a la reincidencia entre adolescentes mujeres en conflicto con la ley de una institución de Brasília, Distrito Federal, Brasil

Andrea Donatti Gallassi1 

Samantha Lima dos Santos1 

Vagner dos Santos1 

Eduardo Yoshio Nakano2 

Benedikt Fischer3  4 

Ana Lúcia Galinkin5 

Gabriela Arantes Wagner6 

1 Faculdade de Ceilândia, Universidade de Brasília, Brasília, Brasil.

2Instituto de Ciências Exatas, Universidade de Brasília, Brasília, Brasil.

3Centre for Addiction and Mental Health, Toronto, Canada.

4University of Toronto, Toronto, Canada.

5Instituto de Psicologia, Universidade de Brasília, Brasília, Brasil.

6Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brasil.


Recidivism is a challenge for the Brazilian socio-educational system because it is associated with personal, social and environmental factors, especially among juvenile offenders. This study examined key characteristics and potential association with recidivism in 391 female adolescent offenders from a correctional institution in Brasília, Federal District, Brazil, between 2004 and 2011. Cross-sectional data on socio-demographics, drug use and offense characteristics from institutional information were examined. Associate factors with recidivism were examined using negative binomial regression analyses. 32.5% of offenders were recidivists at present admission and the mean frequency of recidivism among recidivists was 2.16. About half (53.6%) of the sample reported drug use. After the adjustment, recidivism was positively associated with: age; offender’s drug use; residence status; offense type; and no family drug use. Factors associated with juvenile offenders’ recidivism confirm findings from elsewhere, and should inform targeted interventions in Brazil.

Key words: Recurrence; Adolescent; Drug Users


A reincidência constitui um desafio para o sistema socioeducativo brasileiro por estar associada a fatores pessoais, sociais e ambientais, especialmente entre adolescentes em conflito com a lei. Este estudo verificou as principais características associadas à reincidência em uma amostra de 391 mulheres adolescentes em conflito com a lei em uma unidade de internação de Brasília, Distrito Federal, Brasil, entre 2004-2011. Dados transversais sociodemográficos acerca do uso de drogas e sobre as características do ato infracional foram analisados. Fatores associados à reincidência foram analisados por regressão binomial negativa. Trinta e dois vírgula cinco por cento das adolescentes pesquisadas eram reincidentes e a frequência média de reincidências foi de 2,16. Cinquenta e três vírgula seis por cento da amostra relataram uso de drogas. Após ajuste, reincidir foi positivamente associado à idade, uso de drogas, residência, tipo de ato infracional e não uso de drogas pela família. Nossos achados corroboram com outros contextos mundiais, demonstrando a necessidade de orientação nas intervenções adotadas pelo sistema socioeducativo brasileiro.

Palavras-Chave: Recidiva; Adolescente; Usuários de Drogas


La reincidencia es un reto para el sistema socio-educativo brasileño. Este estudio examinó características claves y su posible asociación con la reincidencia de 391 adolescentes mujeres infractoras en una institución correccional en Brasília, Distrito Federal, Brasil, entre 2004 a 2011. Se examinaron datos transversales socio-demográficos, uso de drogas y las características del delito cometido a partir de la información institucional. Los factores asociados con la reincidencia se obtuvieron por análisis de regresión negativa-binomial. 32,5% de las internas eran reincidentes y la frecuencia media de reincidencia entre las reincidentes era de 2,16. Un 53,6% de la muestra informó consumo de drogas. Después del ajuste, la reincidencia se asoció positivamente con: edad; uso de drogas de la delincuente; estatus de residencia; tipo de delito; el no uso de drogas por parte de la familia. Los factores asociados con la reincidencia de las delincuentes confirman hallazgos de otros estudios, y deberían informar intervenciones específicas sobre esta población en Brasil.

Palabras-clave: Recurrencia; Adolescente; Usuários de Drogas


In many countries, the number of correctional inmates has been rising in recent decades. Additionally, correctional institutions need improvements in the health care offered to its incarcerated population 1. Particular attention is given to young offenders or inmates, given that they constitute a key risk population susceptible to a complex array of external factors and circumstances in their behavior 2. Individuals who make up this population are at an early stage in their lives and so future offenses and their negative consequences for individual and society form a principal concern for interventions 3. In many industrialized countries, young offenders represent up to 20% of the recorded offender or correctional inmate population. In Brazil, the number of young offenders has increased from 10,446 in 2006 to 20,532 in 2012, only 5% of whom were female 4,5; reported information on recidivism varies between 43,3%4 and 54% 5.

Among young offender following residential treatment, different studies have documented recidivism rates of between 40% and 85% 6. Available data suggests that the odds of recidivism are generally higher for male than female juvenile offenders 3,7. A fairly large body of research has focused on identifying potential factors associated with recidivism among male young offenders8,9,10. Consequently, there has been a lack of attention to female offenders 11,12,13, especially in Brazil, including information about recidivism by gender.

Factors associated with recidivism among young offenders are commonly differentiated into “static” factors (those that are historic and cannot be changed, such as age at first offense and prior offenses), and “dynamic” factors (those that can potentially be changed, such as the youth’s friends or school performance, criminal attitudes and denial of responsibility) 14,15. Factors for which at least some supportive evidence for an association with recidivism include: socio-demographic and offense history 7,16; family history and situational variables (unfavorable social context of life, such as lack of access to housing, education and health with desirable quality) 14,16,17; clinical or behavioral problems 8,19,20; and educational factors 8,21. A large proportion of young offenders placed in correctional facilities are diagnosed with a mental health disorder, and most reported that they were under the influence of alcohol or drugs when they committed the delinquent act that led to their current detainment 10,22,23. In addition, it has been emphasized that the characteristics and recidivism of female young offender populations have been understudied, yet require distinct attention 11.

This study examined characteristics of a sample of adolescent female offenders admitted to a correctional facility ( Unidade de Internação do Plano Piloto – UI) between 2004 and 2011 in Brasília, Federal District, Brazil, and examined (a) factors potentially associated with recidivism in the sample, and (b) factors potentially associated with the frequency of recidivism in the sub-sample of offenders who had reported any recidivism.


This is a study based on secondary data obtained from self-reported information at the time of admission from a sample of 391 female adolescent offenders admitted to a UI in Brasília from 2004 to 2011, with an age range of 12-18 years. Following deletion of cases with missing variable values, an overall analysis sample of n = 284 remained. The dependent variable was the frequency of recidivism, which has computed among those reporting previous offenses. People for whom the current correctional admission is the first occurrence were given a recidivism number of zero.

The following independent variables were also analyzed: age in years (≤ 15; 16; 17; 18); type of offense for which current correctional admission occurred (robbery/attempted robbery; theft; drug dealing/possession; attempt against life; threat and extortion; bodily injury/fight/contempt; other); current drug use (yes; no); family drug use (yes; no); attending school (yes; no); residential status (parents/other relatives; on her own).

A descriptive analysis was conducted of the socio-demographic characteristics and recidivism. For the categorical variables, data are presented as proportions and for continuous variables; means and their standard errors were calculated. Factors associated with the number of recidivism were analyzed using simple and multiple negative binomial regressions with log link and reported in mean-ratio (MR). Factors associated with frequency of recidivism were computed with the sub-sample (n = 127) of offenders who had reported “any recidivism” (number of recidivism > 0) using the same approach. In both analyses, the potential associations of factors with recidivism were analyzed individually and all variables considered in the univariate model were included in the multivariate model. All tests were performed assuming a 5% significance level. All statistical analyses were performed using the Generalized Linear Models 24 module of Statistical Package for Social Sciences, version 15 (SPSS Inc., Chicago, USA). This research study was approved by the Ethics Research Committee, Faculty of Health, University of Brasília, approval file #649.523.


Table 1 gives the descriptive characteristics of the sample. Specifically, about four in ten participants of the sample were 15 years or younger. Most common offenses for current admission were robbery/attempted robbery. A higher proportion of the sample reported current drug use, did not report any family drug use, were not attending school at the time of detention, and lived with their parents or other relatives at point of admission. Information on recidivism is described next: 44.7% of offenders in the sample were recidivists at present admissions; 25% had 2 or more previous offenses; the mean frequency of recidivism among the entire sample was 1.05 (range: 0-8; SD = 1.61), and among recidivists 2.34 (range: 1-8; SD = 1.67).

Table 1 Select socio-demographic, drug use and offense characteristics of female adolescent offenders (n = 284). Brasília, Federal District, Brazil, 2004-2011. 

Characteristic Frequency (n = 284) %
Age (years)
≤ 15 99 39.4
16 80 28.2
17 96 33.8
18 9 3.2
Type of offence
Robbery/Attempted robbery 116 40.8
Theft 20 7.0
Drug dealing/Possession 74 26.1
Attempt against life 28 9.9
Threat and extortion 14 4.9
Bodily injury/Fight/Contempt 12 4.2
Other 20 7.0
Offender drug use
No 134 47.2
Yes 150 52.8
Family drug use
No 215 75.7
Yes 69 24.3
Attending school at thje time of detention
No 185 65.1
Yes 99 34.9
Residence status
Parents/Other relatives 198 30.3
On her own 86 69.7

The potential associations of recidivism and the variables of study are shown inTable 2. In the simple negative binomial regression analysis, the association of each variable (separately) with recidivism was considered (crude analysis). The frequency of recidivism in 16 year old young offenders increased 56,6% when compared to girls aged 15 years or younger (MR = 1.566; p-value = 0.046) and, regarding 17 and 18 year old young offenders, the frequency of recidivism increased 117.5% and 192.2%, respectively. The recidivism for theft offense was more than 2 times the recidivism of robbery/attempted robbery offenses (MR = 2.32; p-value = 0.005) and the bodily injury/fight/contempt offenses also showed higher recidivism (MR = 2.381; p-value = 0.05). However, there were no significance differences between robbery/attempted robbery with drug dealing/possession, attempt against life and threat and extortion offenses (p-value > 0.05). Young offenders who were attending school at the time of detention presented 39.1% less recidivism (MR = 0.609, p-value = 0.007). Although offender drug use showed a positive association with recidivism (MR = 2.741; p-value < 0.001), no associations were found with family drug use in crude analysis (p-value > 0.05). Recidivism was more frequent in young offenders who live on their own (MR = 1.696; p-value = 0.002).

Table 2 Results of the simple (univariate) and multiple negative binomial regression analysis of potential associations of age, type of offense, school attendance, offender drug use, family drug use and residence status with recidivism in the sample of female adolescent offenders (n = 284). Brasília, Federal District, Brazil, 2004-2011. 

Crude Adjusted
β ± SE MR (95%CI) p-value β ± SE MR (95%CI) p-value
Age (years) 0.001 0.000
≤ 15 0.000 1.000 0.000 1.000
16 0.449 ± 0.225 1.566 (1.008-2.434) 0.046 0.702 ± 0.255 2.018 (1.224-3.327) 0.006
17 0.777 ± 0.209 2.175 (1.445-3.275) 0.000 0.824 ± 0.233 2.279 (1.444-3.597) 0.000
18 1.072 ± 0.442 2.922 (1.228-6.953) 0.015 2.108 ± 0.514 8.228 (3.006-2.252) 0.000
Type of offense 0.006 0.001
Robbery/Attempted robbery 0.000 1.000 0.000 1.000
Theft 0.842 ± 0.309 2.320 (1.266-4.251) 0.005 1.257 ± 0.341 3.516 (1.800-6.868) 0.000
Drug dealing/Possession 0.213 ± 0.215 1.238 (0.813-1.884) 0.320 0.106 ± 0.231 1.112 (0.707-1.749) 0.645
Attempt against life -0.242 ± 0.332 0.785 (0.409-1.506) 0.466 -0.342 ± 0.351 0.710 (0.357-1.412) 0.329
Threat and extortion -0.041 ± 0.426 0.959 (0.416-2.211) 0.922 0.104 ± 0.463 1.110 (0.448-2.750) 0.821
Bodily injury/Fight/Contempt 0.759 ± 0.387 2.137 (1.000-4.566) 0.050 1.085 ± 0,414 2.960 (1.316-6.659) 0.009
Other 0.868 ± 0.308 2.381 (1.266-4.251) 0.005 0.641 ± 0.345 1.898 (0.966-3.732) 0.063
Attending school at the time of detention 0.007 0.316
No 0.000 1.000 0.000 1.000
Yes -0.496 ± 0.184 0.609 (0.425-0.73) 0.007 -0.203 ± 0.202 0.816 (0.549-1.214) 0.316
Offender drug use 0.000 0.000
No 0.000 1.000 0.000 1.000
Yes 1.008 ± 0.180 2.741 (1.927-3.899) 0.000 0.995 ± 0.201 2.704 (1.822-4.014) 0.000
Family drug use 0.491 0.026
No 0.000 1.000 0.000 1.000
Yes -0.136 ± 0.197 0.873 (0.593-1.285) 0.491 -0.505 ± 0.227 0.603 (0.387-0.941) 0.026
Residence status 0.002 0.045
Parents/Other relatives 0.000 1.000 0.000 1.000
On her own 0.529 ± 0.186 1.696 (1.205-2.388) 0.002 0.390 ± 0.194 1.477 (1.009-2.162) 0.045

95%CI: 95% confidence interval; MR: mean ratio.

β ± SE: beta coefficients and standard error estimated by simple (crude) and multiple (adjusted) negative binomial regression. In each variable, the category with MR = 1 is the reference category. Pearson chi-squared goodness of fit test: χ2 = 270.929; df = 270; p-value = 0.423.

In adjusted analysis performed using multiple negative binomial regression, all variables essentially showed the same results, with two exceptions. Attending school at the time of detection was no longer significant (p-value > 0.05) and the family drug use became significant (p-value = 0.026).

Results of the potential associations with frequency of recidivism among the sub-sample of recidivists are displayed in Table 3. In the univariate model, residence status was the only variable positively associated with recidivism; after adjustments, no associations were found.

Table 3 Results of the simple (univariate) and multiple negative binomial regression analysis of potential associations of age, type of offense, school attendance, offender drug use, family drug use and residence status with frequency of recidivism in a sub-sample of female adolescent offenders recidivists (n = 127). Brasília, Federal District, Brazil, 2004-2011. 

Crude Adjusted
β ± SE MR (95%CI) p-value β ± SE MR (95%CI) p-value
Age (years) 0.455 0.190
< 15 0.000 1.000 0.000 1.000
16 0.111 ± 0.335 1.117 (0.579-2.155) 0.741 0.580 ± 0.388 1.786 (0.836-3.817) 0.134
17 0.436 ± 0.307 1.547 (0.848-2.822) 0.155 0.741 ± 0.347 2.098 (1.063-4.138) 0.033
18 0.055 ± 0.546 1.057 (0.652-1.738) 0.919 0.808 ± 0.649 2.244 (0.629-8.009) 0.213
Type of offense 0.245 0.191
Robbery/Attempted robbery 0.000 1.000 0.000 1.000
Theft 0.391 ± 0.394 1.479 (0.683-3.203) 0.321 0.757 ± 0.441 2.132 (0.898-5.063) 0.086
Drug dealing/Possession -0.014 ± 0.310 0.986 (0.537-1.809) 0.964 -0.033 ± 0.327 0.968 (0.510-1.838) 0.921
Attempt against life -0.600 ± 0.526 0.549 (0.196-1.538) 0.254 -0.615 ± 0.534 0.541 (0.190-1.540) 0.249
Threat and extortion 0.035 ± 0.640 1.035 (0.296-3.626) 0.957 0.123 ± 0.672 1.131 (0.303-4.224) 0.854
Bodily injury/Fight/Contempt 0.546 ± 0.507 1.725 (0.639-4.657) 0.282 0.752 ± 0.536 2.122 (0.742-6.069) 0.161
Other 0.787 ± 0.411 2.196 (0.981-4.915) 0.056 0.744 ± 0.448 2.103 (0.874-5.060) 0.097
Attending school in the moment of detention 0.193 0.604
No 0.000 1.000 0.000 1.000
Yes -0.352 ± 0.271 0.703 (0.414-1.196) 0.193 -0.151 ± 0.292 0.860 (0.485-1.522) 0.604
Offender drug use 0.303 0.649
No 0.000 1.000 0.000 1.000
Yes 0.279 ± 0.271 1.322 (0.777-2.247) 0.303 0.143 ± 0.314 1.154 (0.624-2.133) 0.649
Family drug use 0.822 0.798
No 0.000 1.000 0.000 1.000
Yes 0.064 ± 0.284 1.066 (0.611-1.862) 0.822 -0.082 ± 0.320 0.921(0.492-1.724) 0.798
Residence status 0.036 0.085
Parents/Other relatives 0.000 1.000 0.000 1.000
On her own 0.506 ± 0.241 1.658 (1.034-2.359) 0.036 0.454 ± 0.264 1.575 (0.939-2.641) 0.085

95%CI: 95% confidence interval; MR: mean ratio.

β ± SE: beta coefficients and standard error estimated by simple (crude) and multiple (adjusted) negative binomial regression. In each variable, the category with MR = 1 is the reference category. Pearson chi-squared goodness of fit test: χ2 = 87.411; df = 113; p-value = 0.965.


Our study described select offender characteristics, and explored potential factors associated with recidivism in a sample of adolescent female offenders from a correctional institution in Brasília. Much of the scientific attention regarding correctional populations – including young offenders – has focused on male offenders, who are the predominant group in correctional facilities and more often recidivists 25,26. Consequently, there has been a lack of attention on female offenders, as recognized elsewhere 11,12,13. These studies have argued that life challenges or factors influencing deviance are experienced differently between genders, including mental health or substance use problems; victimization or violence; educational and/or financial disadvantages.

Similar to other studies on recidivism in young offenders, our analysis found age to be a primary determinant for recidivism in our study population 10,25,27,28. Concretely, the major proportions of recidivism observed occurred among girls aged between 16 and 18 years 29. Especially in this overall young offender population, the influence – and positive correlation – of age with recidivism may be quite simple, as increased age provides additional opportunity for offending; this however does not necessarily suggest or constitute any implications for “criminal careers” within such a short and early lifespan as indicated for adult offender populations 30. On this basis, this age group should receive highest rehabilitation and secondary prevention, because they are more vulnerable to recidivism given that one of the strongest predictors of adult crime is a crime history from earlier in life 29,31.

However, there is a discrepancy among dynamic and static factors associated with young offenders. Other static factors, such as type of offense, increase their relevance as the adolescents get older 14,29, or may be the main predictor of recidivism in some cases6. In the total sample of the present study, the type of offense showed negative association with recidivism among the young offenders involved in other offenses when compared to robbery. This is important information for the development of rehabilitation and/or secondary prevention programs for these adolescents; specifically those held for robbery offenses need to be monitored more closely 14,29.

As has been indicated elsewhere, drug use is a consistent risk factor for violent behavior and recidivism 32. This indicates also that, as age increases, adolescents have more alcohol- and drug-related problems, which may be an opportunity effect, since those who have been alive longer have simply had more time to engage in these problem behaviors 15,24. We found a substantive prevalence of drug use among adolescent offenders in the present sample; however our data did not allow us to explore the type of drug relation to offenses. Additionally, our results indicate that girls from non-drug user families were more likely to recidivate, a link that is not corroborated by previously published research. Although there is considerable support for the association between parenting profiles and adolescent problem behaviors, these data cannot be unambiguously interpreted. The interactions between parenting style and problem behaviors may be bi-directional, or even include – mediating – external factors 33.

Our findings indicate that living with parents or relatives can be relevant factor in predicting recidivism for those who were recidivist already or not, and in this instance constitutes a protective factor for recidivism, as other studies have suggested 8,10,34. It may be that parental restraints or role modeling, or overall dynamics of higher psycho-social stability experienced by living with family at this stage of adolescent life may protect from continued delinquent behavior resulting in repeated correctional admission 26. In this context, it has been proposed that a multi-system approach might be desirable or effective towards reducing further recidivism in the target population of adolescent offenders 35,36, for example in the form of community-based supervision and substance abuse treatment, and with family involvement, both during and after the time spent in the correctional system.

Finally, the absence of any significant variable for “frequency of recidivism” among recidivists may be due to the sample’s short age-span covered or the relatively crude nature of the data that simply may not allow for the detection of any clear single-variable influences (or they may simply not exist).

Some limitations of our study need to be acknowledged. Firstly, our data are cross-sectional, drawn as an opportunistic sample from an adolescent female offender population in a single correctional facility; therefore results are not generalizable. Our analyses rely on secondary data generated by self-report, and not drawing on standardized question items and/or a validated protocol, which significantly increases the possibility of bias (e.g., due to possible social desirability effects in responses) and reduces the potential of comparisons with other studies. Even though drug dealing and possession are distinct type of offense, we combined in the same variable because the frequency of possession only had appeared in a few cases (4).

In conclusion, in this sample we found that most female offenders were aged ≥ 15 years old, and admitted to adolescent corrections for robbery/attempted robbery and drug dealing/possession. Over half the sample reported current drug use and about half were recidivist offenders. Recidivism was positively associated with age, offender’s drug use, residence status, offense type and no family drug use, and negatively associated with attendance at school. Among the sub-sample of recidivists, there was an association with residence status. Finally, the results indicate several factors associated with recidivism among a sample of adolescent female offenders in Brazil that largely confirm findings from other countries.


The authors acknowledge support from the Center of Drugs and Associated Vulnerabilities, Faculty of Ceilândia, University of Brasilia, and the National Drug Policy Secretariat, Ministry of Justice, Brazil. B. Fischer acknowledges funding from the LACREG program, Association of Universities and Colleges of Canada (AUCC), and funding from a CIHR/PHAC Applied Public Health Chair which supported the present work.


1. Watson R, Stimpson A Hostick T. Prison health care: a review of the literature. Int J Nurs Stud 2004; 41:119-28. [ Links ]

2. Fazel S, Baillargeon J. The health of prisoners. Lancet 2011; 377:956-5. [ Links ]

3. Moffitt TE, Caspi A, Harrington H, Milne BJ. Males on the life-course-persistent and adolescence-limited antisocial pathways: follow-up at age 26 years. Dev Psychopathol 2002; 14:179-207. [ Links ]

4. Secretaria de Direitos Humanos, Presidência da República. Levantamento nacional do atendimento socioeducativo ao adolescente em conflito com a lei – 2012. Brasília: Secretaria de Direitos Humanos, Presidência da República; 2012. [ Links ]

5. Conselho Nacional de Justiça. Panorama nacional de execução de medidas socioeducativas – 2012. Brasília: Conselho Nacional de Justiça; 2012. [ Links ]

6. Calley NG. Juvenile offender recidivism: an examination of risk factors. J Child Sex Abuse 2012; 21:257-72. [ Links ]

7. Ang RP, Huan VS. Predictors of recidivism for adolescent offenders in a Singapore sample. Crim Justice Behav 2008; 35:895-905. [ Links ]

8. Cottle CC, Lee RJ, Heilbrun K. The prediction of criminal recidivism in juveniles: a meta-analysis. Crim Justice Behav 2001; 28:367-94. [ Links ]

9. Loeber R, Farrington DP. Young children who commit crime: epidemiology, developmental origins, risk factors, early interventions, and policy implications. Dev Psychopathol 2000; 12:737-62. [ Links ]

10. McCoy LA, Miller HA. Comparing gender across risk and recidivism in nonviolent offenders. Women Crim Justice 2013; 23:143-62. [ Links ]

11. Roobins RN, Bryan A. Relationships between future orientation, impulsive sensation seeking, and risk behavior among adjudicated adolescents. J Adolesc Res 2004; 19:428-45. [ Links ]

12. Belknap J, Holsinger K. The gendered nature of risk factors for delinquency. Fem Criminol 2006; 1: 48-71. [ Links ]

13. Minor KI, Wells JB, Angel E. Recidivism among juvenile offenders following release from residential placements: multivariate predictors and gender differences. J Offender Rehabil 2008; 46:171-88. [ Links ]

14. Myner J, Santman J, Cappelletty GG, Perlmutterm BF. Variables related to recidivism among juvenile offenders. Int J Offender Ther Comp Criminol 1998; 42:65-80. [ Links ]

15. van der Put CE, Dekovic M, Stams GJJM, Van der Laan PH, Hoeve M, van Amelsfort L. Changes in risk factors during adolescence: implications for risk assessment. Crim Justice Behav 2011; 38: 248-62. [ Links ]

16. Katsiyannis A, Zhang D, Barrett DE, Flaska T. Background and psychosocial variables associated with recidivism among adolescent males: a 3-year investigation. J Emot Behav Disord 2004; 12:23-9. [ Links ]

17. Andrews DA, Bonta J. The psychology of criminal conduct. New Providence: Lexis Nexis/Anderson Publishing; 2010. [ Links ]

18. Benda BB, Tollett CL. A study of recidivism of serious and persistent offenders among adolescents. J Crim Justice 2012; 27:111-26. [ Links ]

19. Chang JJ, Chen JJ, Brownson RC. The role of repeat victimization in adolescent delinquent behaviors and recidivism. J Adolesc Health 2003; 32:272-80. [ Links ]

20. Mulder E, Brand E, Bullens R, van Marle H. Risk factors for overall recidivism and severity of recidivism in serious juvenile offenders. Int J Offender Ther Comp Criminol 2011; 55:118-35. [ Links ]

21. Nagin DS, Land KC. Age, criminal careers, and population heterogeneity: specification and estimation of a nonparametric, mixed poisson model. Criminology 1993; 31:327-62. [ Links ]

22. Becker SP, Kerig PK, Lim JY, Ezechukwu RN. Predictors of recidivism among delinquent youth: interrelations among ethnicity, gender, age, mental health problems, and posttraumatic stress. J Child Adolesc Trauma 2012; 5:145-60. [ Links ]

23. Fazel S, Doll H, Långström N. Mental disorders among adolescents in juvenile detention and correctional facilities: a systematic review and metaregression analysis of 25 surveys. J Am Acad Child Adolesc Psychiatry 2008; 47:1010-9. [ Links ]

24. Field A. Advanced techniques for the beginner: exploring data. Discovering statistics using SPSS for windows. London: Sage Publications; 2000. [ Links ]

25. Chu CM, Daffern M, Thomas S, Lim JY. Violence risk and gang affiliation in youth offenders: a recidivism study. Psychology, Crime & Law 2012; 18:299-315. [ Links ]

26. Wilson JJ, Rojas N, Haapanen R, Duxbury E, Steiner H. Substance abuse and criminal recidivism: a prospective study of adolescents. Child Psychiatry Hum Dev 2001; 31:297-312. [ Links ]

27. Cauffman E. Understanding the female offender. Future of Children 2008; 18:119-42. [ Links ]

28. Horta RL, Horta BL, Pinheiro RT, Krindges M. Violent behavior in adolescents and parent-child cohabitation. Rev Saúde Pública 2010; 44:979-85. [ Links ]

29. Vries AM, Liem M. Recidivism of juvenile homicide offenders. Behav Sci Law 2011; 29:483-98. [ Links ]

30. Ogden T, Halliday-Boykins CA. Multisystemic treatment of antisocial adolescents in Norway: replication of clinical outcomes outside of the US. Child Adolesc Ment Health 2004; 9:77-83. [ Links ]

31. Henggeler SW, Cunningham PB, Schoenwald SK, Borduin CM, Rowland MD. Multisystemic therapy for antisocial behavior in children and adolescents. New York: Guilford Press; 2009. [ Links ]

32. Borum R, Verhaagen DA. Assessing and managing violence risk in juveniles. New York: Guilford Press; 2006. [ Links ]

33. Katsiyannis A, Archwamety T. Factors related to recidivism among delinquent youths in a state correctional facility. J Child Fam Stud 1997; 6:43-55. [ Links ]

34. Huh D, Tristan J, Wade E, Stice E. Does problem behavior elicit poor parenting? A prospective study of adolescent girls. J Adolesc Res 2006; 21:185-204. [ Links ]

35. Ho KM, Litton E, Geelhoed E, Gope M, Burrell M, Coribel J, et al. Effect of an injury awareness education program on risk-taking behaviors and injuries in juvenile justice offenders: a retrospective cohort study. PLoS One 2012; 7:e31776. [ Links ]

36. Rettinger LJ, Andrews DA. General risk and need, gender specificity, and the recidivism of female offenders. Crim Justice Behav 2010; 37:29-46. [ Links ]

Received: November 17, 2014; Revised: May 13, 2015; Accepted: June 08, 2015

Correspondence A. D. Gallassi. Faculdade de Ceilândia, Universidade de Brasília. Centro Metropolitano 1, Conjunto A, Ceilândia Sul, Brasília, DF 72220-900, Brasil.


A. D. Gallassi participated on the data collection, study design, drafted the article and revised it critically for important intellectual content and final approval of the version to be published. S. L. Santos and A. L. Galinkin contributed on the data collection and final approval of the version to be published. V. Santos, B. Fischer and G. A. Wagner participated on the study design, drafted the article and revised it critically for important intellectual content and final approval of the version to be published. E. Y. Nakano contributed on the statistical analyses and final approval of the version to be published.

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