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Julian Ford; Robert L. Trestman; Fred Osher; Jack E. Scott; Henry J. Steadman; Pamela Clark Robbins
Mental Health Screens for Corrections
US Dept of Justice
National Institute of Justice
This paper reports on the findings and implications of two research projects that developed and validated mental health screening instruments that corrections staff can use during intake. The researchers created short questionnaires that have accurately identified inmates who required mental health interventions. One mental health screening instrument, the Brief Jail Mental Health Screen (BJMHS), was proven effective for men and is being adapted for women. The other screening instrument, the Correctional Mental Health Screen (CMHS), has versions that are effective for identifying mental disorders for both men and women. The CMHS for women and the CMHS for men were developed by first presenting to study participants a 25-minute composite of all the questions (n=53) from 4 separate existing screening instruments. Study participants were 2,196 adults detained in 5 Connecticut jails. Approximately 20 percent of the participants were randomly selected to come back 1-5 days later for a lengthier clinical assessment. Statistical analysis was performed separately by gender in order to determine the questions with the most statistical sensitivity, specificity, and predictive power in measuring nine clusters of mental health disorders. These included current depressive disorders, current anxiety disorders, antisocial personality disorder, and posttraumatic stress disorder. Further statistical analysis reduced the instruments to 38 items for women and 40 items for men. The final analysis reduced the instruments to 8 items for women and 12 items for men, each of which take 3-5 minutes to administer. These final versions were validated on an additional group of 206 participants. The BJMHS was directly derived from the Referral Decision Scale (RDS), which was designed to detect signs and symptoms of severe impairment stemming from serious mental health disorders. The number of RDS items was reduced from the original 14 to 8 items by eliminating those items that had questionable validity. 20 notes and appended instruments
Mary T. Phillips
Bail, Detention, & Nonfelony Case Outcomes
New York City Criminal Justice Agency, Inc
This report presents highlights from an ongoing New York City, Criminal Justice Agency (CJA) study examining relationships among the amount of bail, the duration of detention, and case outcomes with a focus on non-felony cases. Results support the hypothesis that pretrial detention has an adverse effect on case outcomes, especially the likelihood of conviction. However, detention was not the predominant factor in predicting conviction, and it was only a very small factor in predicting incarceration and sentence length. Offense type, charge severity class, the defendant’s criminal history, borough of prosecution, and other factors together accounted for a much larger proportion of the variation in outcomes than did detention. The findings suggest a causal loop: case-related factors affect outcome, judges adjust bail setting in response to those same and other factors, and the resulting detention has an additional small effect on the outcomes, particularly likelihood of conviction. Research literature has long reported a connection between pretrial detention and the severity of case outcomes. However, the nature of the relationship is hard to determine. This study examined the effects of pretrial detention on case outcomes in New York City. The outcomes included in the analysis were likelihood of conviction, likelihood of incarceration, and sentence length. The dataset used for this study included all arrests in New York City from October 2003 through January 2004. The analyses were restricted to docketed cases with a non-felony top charge entering criminal court (lower court) arraignment. The use of non-felony cases sets this study apart from previous studies. Figures
Michael W. Finigan; Shannon M. Carey; Anton Cox
Impact of a Mature Drug Court Over 10 Years of Operation: Recidivism and Costs (Executive Summary)
US Dept of Justice
National Institute of Justice
This study examined the impact and costs of a primarily pre-plea drug court on the total population of drug court-eligible offenders over a 10-year period in Portland, OR. Results included reduced recidivism for drug court participants up to 14 years after drug court entry compared to eligible offenders that did not participate. Drug court judges that worked longer with the drug court had better participant outcomes. Judges that rotated through the drug court twice had better participant outcomes the second time than the first. Compared to traditional criminal justice system processing, treatment and other investment costs averaged $1,392 lower per drug court participant. Reduced recidivism and other long-term program outcomes resulted in public savings of $6,744 on average ($12,218 if victimization costs are included), or an estimated $79 million over 10 years. The analysis of the data focused on the overall impact of the drug court on the target population over time, variations over time on that impact, and external and internal conditions that influenced these outcomes. A cost analysis was conducted to assess the overall investment of taxpayer money in the court compared to its benefits. This study covers the period from program start in 1991 through 2001. The entire population of offenders, identified as eligible for drug court by the Multnomah County District Attorney’s Office from 1991 to 2001, was identified and tracked through a variety of administrative data systems. Approximately 11,000 cases were identified; 6,500 participated in the Drug Court program during that period and 4,600 had their case processed outside the drug court model. Data on outcomes were gathered on each offender, with a particular emphasis on criminal recidivism. The outcome data were drawn in late 2005 and early 2006, allowing a minimum of 5 years of followup on all cohorts and more than 10 years on many cohorts. Data on costs were calculated in terms of investment costs, outcome costs, and total costs per participant.