These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The research project has tested a possible explanation for the Great American Crime Decline of the 1990s and especially 2000s: the increasing rates at which psychotropic drugs are prescribed, especially to children and adolescents. Psychotropic drugs are often prescribed to youth for mental health conditions that involve disruptive and impulsive behaviors and learning difficulties. The effects of these drugs are thus expected to lead to the decrease in the juveniles' involvement in delinquency and violence. The effects of two legislative changes are hypothesized to have contributed to the increased prescribing of psychotropic drugs to children growing up in families in poverty: 1) changes in eligibility for Supplemental Security Income (SSI) that made it possible for poor children to qualify for additional financial assistance due to mental health conditions (1990 and 1996), and 2) changes in school accountability rules following the passage of No Child Left Behind Act (2002) that put pressure on schools in some low-income areas to qualify academically challenged students as having ADHD or other learning disabilities. The objectives of the project are: 1) to assemble a data set, using state-level data from various publicly available sources, containing information about trends in juvenile delinquency and violence, trends in psychotropic drug prescribing to children and adolescents, and various control variables associated with these two sets of trends; 2) to test the proposed hypotheses about the effect of increasing psychotropic medication prescribing to children and adolescents on juvenile delinquency and violence, using the assembled data set; and 3) to disseminate the scientific knowledge gained through this study among criminal justice researchers, psychiatric and public health scientists, as well as among a wider audience of practitioners and the general public. This collection includes one SPSS file (Dataset_NIJ_GRANT_2014-R2-CX-0003_DV-IV_3-29-17.sav; n=1,275, 113 variables) and one Word syntax file (doc36775-0001_syntax.docx).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. To assess "double transition" (the transition from confinement to community in addition to the transition from adolescence to adulthood), the study used nationally representative data from the National Longitudinal Study of Adolescent Health (Add Health) to compare psychosocial maturity for three groups: approximately 162 adolescents placed in correctional confinement, 398 young adults who reported an arrest before age 18 but no juvenile correctional confinement, and 11,614 youths who reported no arrests before age 18. Three dimensions of psychosocial maturity (responsibility, temperance, and perspective) were assessed at Waves 1 (baseline) and Wave 3 (post-confinement) in models assessing the effects of confinement on the attainment (or non-attainment) of markers of successful transition to adulthood at Wave 4. Results were contextualized with data from the Survey of Youth in Residential Facilities and discussed with respect to the role of confinement in interrupting the development of psychosocial maturity in the transition to adulthood and for young adult attainment more generally. There are no data files available with this study. Only syntax files used by the researchers are provided.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study examined etiological pathways to teen dating violence (TDV) in a sample of adolescents who had been followed since infancy and were at high-risk due to parental alcohol problems. Adolescents (M=17.68 years of age) who had been participating, along with their parents, in a longitudinal study of the effects of parental alcohol problems on child development completed an additional wave of survey data in 11-12th grades. Families (N=227) were initially recruited from county birth records when the child was 12 months of age and had been previously assessed at 12-, 18-, 24-, 36-months, kindergarten, 4th, 6th, and 8th grades. For the current wave of data collection, adolescent participants (n=185) used computer-assisted interviewing to complete questionnaires assessing their individual characteristics, family and peer relationships, substance use, dating behaviors and involvement in TDV as a victim or perpetrator.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study identified risk and protective factors for dating violence (DV) among young adults (ages 18-22) with a history of maltreatment and placement in foster care, and who had enrolled in Fostering Healthy Futures (FHF) during 2002-2009. FHF is a Colorado-based positive youth program for maltreated youth. This study focused on factors that ameliorated the effects of risk to reduce DV perpetration and victimization in young adulthood. The participants were interviewed at three different points during the FHF time frame. That data provided a basis for determining risk and mediating factors which in turn were compared to the current study's DV outcomes. The risk and protective factors included: Mental health Substance abuse Social support Gender Stereotypes Attitudes about Teen DV Communication Skills Perpetration and victimization outcomes were then examined in relation to the risk and protective factors. The collection includes 1 SPSS file: NIJ-2013-VA-CX-0002---2nd-revision---5-17-18.sav (215 cases / 2023 variables).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The Safe Start Promising Approaches for Children Exposed to Violence Initiative funded 10 sites to implement and evaluate programs to improve outcomes for children exposed to violence. RAND conducted the national evaluation of these programs, in collaboration with the sites and a national evaluation team, to focus on child-level outcomes. The dataset includes data gathered at the individual family-level at baseline, 6-, 12-months. All families were engaged in experimental or quasi-experimental studies comparing the Safe Start intervention to enhanced services-as-usual, alternative services, a wait-list control group, or a comparable comparison group of families that did not receive Safe Start services. Data sources for the outcome evaluation were primary caregiver interviews, child interviews (for ages 8 and over), and family/child-level service utilization data provided by the Safe Start program staff.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study was designed to begin to build a knowledge base to address the challenges of crossover youth in Maryland - those involved at some point in their lives in the dependency and delinquency systems. Employing a mix of qualitative and quantitative methods, the research focused on the five most populous jurisdictions in the state, Baltimore City, and Anne Arundel, Montgomery, Prince George's, and Baltimore Counties. This collection includes 4 SPSS data files: CINA BCity_Archive_final_Corrected-ICPSR.sav (n=400; 64 variables) CY Stakeholder Survey_Archive_final_Corrected_Update2016-ICPSR.sav (n=164; 302 variables) Delinquency_Risk_Archive_final_Corrected_Update2016-ICPSR.sav (n=1,127; 62 variables) Needs_Archive_final-ICPSR.sav (n=700; 67 variables) Data from interviews with 26 officials in state and local agencies to collect information on policies and practices affecting crossover youth in Maryland are not available as part of this collection.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.Prior to 1996, surveys pertaining to youth gangs in the United States were conducted infrequently, and methodology and samples had been inconsistent. No single source of data pertaining to the nature, size, and scope of youth gangs existed. From 1996 through 2012, the National Youth Gang Survey (NYGS) collected data annually from a large, representative sample of local law enforcement agencies to track the span and seriousness of gang activity nationwide. The NYGS collected data from a sample of the universe of law enforcement agencies in the United States from which data can be extrapolated to determine the scope of youth gangs nationally.This collection includes one SPSS data file "1996-2001_cleaned_for_NACJD.sav" with 330 variables and 3,018 cases.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The National Youth Gang Survey (NYGS) 2002-2012 is a continuation of data collected annually from a representative sample of all law enforcement agencies in the United States that began in 1996. In 2002, the NYGS resampled law enforcement agencies based on updated data from the United States Census Bureau and the Federal Bureau of Investigation (FBI), and the NYGS continued to collect law enforcement data through 2012. This longitudinal study allows for examination of the trends in scope and magnitude of youth gangs nationally by measuring the presence, characteristics, and behaviors of local gangs in jurisdictions throughout the United States. This collection includes 1 SPSS data file with 2,388 cases and 606 variables.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This is a quasi-experimental, observational study using administrative data to assess whether time in juvenile placement was associated with the acquisition of social-emotional skills and subsequent felony recidivism. Concurrent with a change in juvenile sentencing policy in Washington State a comprehensive risk and needs assessment tool (R-PACT) was piloted to investigate the impact that therapeutically oriented incarceration had on youth. This tool was made up of 12 domains of risk and needs, including a section on dynamic factors related to therapeutic skills. Youth were admitted into the study in two cohorts, a main study cohort and a replication study cohort.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study examined the validity, reliability, equity and cost of nine juvenile justice risk assessment instruments. It was designed to provide a comprehensive examination of how several risk assessments perform in practice. This study posed the following questions: Is each risk assessment instrument sufficiently reliable (i.e., inter-rater reliability) to ensure that decisions regarding level of risk and identified service needs are consistent across the organization? What specific risk assessment items are associated with less reliability? What items are rated reliably by staff? Is each risk assessment instrument valid? Specifically, what degree of discrimination is attained between assigned risk levels? Could the instrument be improved by adding or deleting specific factors and/or altering cut-off scores? Is each risk assessment instrument valid for population subgroups: White/Caucasian, Black/African American, Hispanic/Latino, females, probationers, and youth in aftercare status? Could equity be improved by adding or deleting specific factors or altering cut-off scores? What costs are associated with each risk assessment instrument? The study collection includes 31 SPSS data files all_jais_combined.sav (n=1,141; 6 variables) ar_fire_final_file_ojjdp-ICPSR.sav (n=119; 205 variables) AR_yls_irr_FINAL-ICPSR.sav (n=155; 136 variables) azaoc_FINALFILE-ICPSR.sav (n=7,589; 438 variables) AZAOC_irr_FINAL-ICPSR.sav (n=458; 101 variables) AZDJC_FINAL_FILE-ICPSR.sav (n=1,265; 1,290 variables) AZDJC_irr_FINAL-ICPSR.sav (n=55; 120 variables) COMMITMENT_FINAL_SAMPLE2-ICPSR.sav (n=11,154; 719 variables) FinalDJJReleasesWithRecid_BothYears2-ICPSR.sav (n=90,818; 31 variables) FIRE_NE_COMM_FINAL_FILE_OJJDP-ICPSR.sav (n=597; 174 variables) fire_ne_probation_final-ICPSR.sav (n=1,077; 237 variables) FL_irr_FINAL-ICPSR.sav (n=519; 140 variables) GA_irr_FINAL-ICPSR.sav (n=509; 263 variables) gafire_boyscommunityALL_FINAL-ICPSR.sav (n=5,009; 781 variables) gafire_communityALLforretrofit2-ICPSR.sav (n=6,943; 666 variables) gafire_finalsampforanalysis_all-ICPSR.sav (n=7,412; 642 variables) gafire_finalsampforanalysis_girls-ICPSR.sav (n=2,005; 768 variables) jais_boys_wk_1-ICPSR.sav (n=1,989; 484 variables) jais_girls_wk_1-ICPSR.sav (n=745; 484 variables) NE_irr_FINAL-ICPSR.sav (n=727; 160 variables) OR_irr_FINAL-ICPSR.sav (n=477; 112 variables) ORE_FIRE_final-ICPSR.sav (n=12,370; 340 variables) PROBATION_FINAL_BOYS_ALL-ICPSR.sav (n=20,621; 837 variables) PROBATION_FINAL_GIRLS_ALL-ICPSR.sav (n=6,748; 849 variables) va_boyssample-ICPSR.sav (n=1,106; 1,273 variables) va_final_sample_fullscreen-ICPSR.sav (n=1,439; 1,237 variables) va_girlssample-ICPSR.sav (n=333; 1,256 variables) VA_irr_expert_FINAL-ICPSR.sav (n=10; 308 variables) VA_irr_worker_FINAL-ICPSR.sav (n=685; 308 variables) vafinalsample-ICPSR.sav (n=1,919; 1,200 variables) workersurveyfinal-ICPSR.sav (n=400; 69 variables)