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Crime, Violence, and Managing Client and Public Safety

Crime, Violence, and Managing Client and Public Safety. Michael L. Dennis, Ph.D., Chestnut Health Systems, Bloomington, IL

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Crime, Violence, and Managing Client and Public Safety

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  1. Crime, Violence, and Managing Client and Public Safety Michael L. Dennis, Ph.D., Chestnut Health Systems, Bloomington, IL Presentation at “NEW DIRECTIONS TO HEALTHIER COMMUNITIES & METH SUMMIT”, September 28-30, 2005, Savannah Marriott Riverfront, Savannah, GA. Sponsored by the Georgia Council on Substance Abuse and the Georgia Department of Juvenile Justice, Office of Behavioral Health Services. The content of this presentations are based on treatment & research funded by the Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA) under contract 270-2003-00006 using data provided by the CYT and AMT grantees: (TI11320, TI11324, TI11317, TI11321, TI11323, TI11874, TI11424, TI11894, TI11871, TI11433, TI11423, TI11432, TI11422, TI11892, TI11888). The meta analysis of juvenile offender intervention data was adapted from an earlier presentation by Mark Lipsey with his permission. The opinions are those of the author and do not reflect official positions of the consortium or government. Available on line at www.chestnut.org/LI/Posters or by contacting Joan Unsicker at 720 West Chestnut, Bloomington, IL 61701, phone: (309) 827-6026, fax: (309) 829-4661, e-Mail: junsicker@Chestnut.Org

  2. Goals of this Presentation • To summarize the need for measuring substance use, crime and violence and its correlates • To examine the utility of the GAIN’s Substance Problem for assessing the risk of relapse and recidivism • To summarize the results of meta analyses of effective programs for juvenile offenders by Lipsey and colleagues

  3. Adolescent Present with a Broad Range of Past Year Illegal Activity and Violence 100 95 93 93 86 85 90 82 81 81 80 78 74 80 71 69 68 65 70 60 50 40 30 20 10 0 OP/IOP (n=560) LTR (n=390) STR (n=594) Any illegal activity Property crimes Interpersonal crimes Drug related crimes Acts of physical violence Source: Adolescent Treatment Model (ATM) data

  4. Substance Abuse Treatment (particularly residential) Reduces Illegal Activity 60 STR\t,s,ts LTR\t,ts 50 OP\s 40 Intake 3 6 9 12 Months from Intake \a Source: Adolescent Treatment Model (ATM) data; Levels of care coded as Long Term Residential (LTR, n=390), Short Term Residential (STR, n=594), Outpatient/Intensive and Outpatient (OP/IOP, n=560);. T scores are normalized on the ATM outpatient intake mean and standard deviation. Significance (p<.05) marked as \t for time effect, \s for site effect, and \ts for time x site effect.

  5. Background • Substance use and crime are inter-related. • Self-report methodis valid and useful for predicting treatment placement, relapse and recidivism. • Typically, substance use measures have been used to predict placement and relapse, while criminological measures have been used to predict recidivism. • This is one of the first adolescent studies to look at the ability of substance use and criminological measures combined to predict placement, relapse, and recidivism in the same population or study.

  6. 2 1 b 4 d a 6 5 3 8 7 9 c 10 Location of CYT/ATM Treatment Sites • Adolescent Treatment • Model (ATM) Sites: • Chestnut Health Systems, Bloomington, IL • Dynamite Youth, New York, NY • Four Corners Regional Adolescent Center/ University of Oklahoma Shiprock, NM • Friends Institute/Epoch Counseling, Catonsville, MD • Mountain Manor, Baltimore, MD • Public Health Institute/Thunder Road, Oakland, CA • Rand Corp./Phoenix Academy/Group Homes, Santa Monica, CA • University. of Arizona/IMPACT, Phoenix, AZ • University of Arizona/La Cañada/7-Challenges/Drug Court, Tucson, Az • University of Miami/MDFT/The Village, Miami, FL • Cannabis Youth Treatment (CYT) Sites: • Chestnut Health Systems, Madison County, IL • Children’s Hospital of Phil., Philadelphia, PA • Operation PAR, St. Petersburg, FL • Univ. of Conn. Health Center, Farmington, CT Sponsored by: Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services

  7. Evaluation • Target Population: Adolescents entering substance abuse treatment. • Inclusion Criteria: 12 to 22 year old adolescents who present for substance abuse treatment and received at least 2 outpatient sessions or 1 week of residential treatment. • Data Sources: Self-report measures of diagnosis and outcome collected with the Global Appraisal of Individual Needs (GAIN). • Participants: 2007 adolescents recruited from 14 sites around the U.S. and interviewed at 3, 6, 9 and 12 months later (98% completed 1 plus interview; 92% completed 12 month interview).

  8. Intensity of Juvenile Justice System Involvement Row % Low Hi Severity 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Detention 14+ days (n=433) Probation/parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  9. Intensity by Level of Care Row % Total Step Down OP Outpatient/IOP Long Term Residential Short Term Residential 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  10. Demographic Characteristics Row % Source: CYT & ATM Data

  11. Females and Caucasians more likely in lower intensity Minorities More Likely to be in higher intensity Demographics by Intensity Col % 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Female Caucasian African Hispanic Native Other American American Detention 14+ days (n=433) Probation/parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  12. High Severity More likely to be 15-17 years olds and from Single Parent Families Youngest least likely to be in the system Demographics by Intensity (continued) Col % Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  13. Substance Use Characteristics Row % Source: CYT & ATM Data

  14. Current Intensity Inversely related to Substance Use Severity Past Involvement a Mix of Severity Substance Use Disorder Diagnosis by Intensity Col % Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data; a\ Self report for past year

  15. External Diagnoses by Intensity Col % Multiple Co-Occurring Disorders are Common in all levels of JJ involvement Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  16. Curvilinear Relationship between Intensity and Internal Distress Internal Diagnoses/Problems by Intensity Col % Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data \b n=1838 because some sites did not ask trauma questions

  17. Most Internal Distress is Multi-morbid with External (and Substance Use) Disorders Pattern of Co-occurring Disorders by Intensity Col % Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  18. Legal Characteristics Row % Source: CYT & ATM Data

  19. Often Both Perpetrator and Victim     Any High levels of     Any crime High Crime/     Homeless or     High Health Victimization Victimization Violence Runaway Problems Crime/Other Problems by Intensity Col % Focus of JJ Detention Stress Can lead to higher rates of health problems Also higher incidents of Running away 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Detention 14+ days (n=433) Probation/ Parole and urine monitoring 14+ days (n=472) Other detention, parole, or probation (n=374) Other current arrest or JJ status (n=303) Past arrest or JJ status (n=170) Past year illegal activity (n=298) Source: CYT & ATM Data

  20. Substance Problem Scale (SPS) The SPS (alpha=.88) is a count of 16 past year symptoms based on • three common screening questions (S9c-e), • two questions related to substance “induced” psychological or health disorders (S9f-g), • lay versions of the DSM-IV/ICD-9 criteria for substance abuse (S9h-m), • Lay versions of the DSM-IV/ICD-9 criteria for substance dependence (S9n-u). The latter also forms the Substance Dependence Subscale (SDS; alpha=.82). The SPS symptom count severity is triaged as Low (0 past year symptoms), Moderate (1 to 9 symptoms) or High (10 to 16 symptoms) severity.

  21. Crime and Violence Scale (CVS) • The CVS (alpha=.90) is a count of 29 past year symptoms from two subscales: • The General Conflict Tactic Subscale (GCTS; alpha = .88) - based on the National Family Violence Survey and work by Murray Strauss. • The General Crime Subscale (GCS; alpha = .86) - based on the National Household Survey on Drug Abuse lay terms for the Uniform Crime Report categories. • CVS symptom count severity is triaged as: • Low (0 to 2 past year symptoms), • Moderate (3 to 6 symptoms), or • High (7 to 29 symptoms) severity.

  22. Moderate to high severity substance use and crime/ violence problems are common Distribution of SPS by CVS Risk Groups 40% Percent of Total (n=2007) 20% Crime and Violence Scale Substance Problem Scale 0% High High Mod. Mod. Low Low Source: CYT & ATM Data

  23. Validation of the SPS and CVS subgroups • Endorsement of each items and subscales increased with the shift from low to moderate to high. • For the Substance Problem Scale (SPS) severity subgroups: • Shifting from low to moderate was associated with sharp increases in the screener questions (c-e), continued use in spite of getting into fights or legal problems (m), and time spent on getting/using/recovering from substance use (s). • Shifting from moderate to high was associated with more of the above and greater increases in the substance dependence and substance induced disorder symptoms. • For Crime/Violence Scale (CVS) severity subgroups: • Shifting from low to moderate was associated with increased oral violence, property crime, and drug related crime. • Shifting from moderate to high was associated with even more of these things, as well as more physical violence and interpersonal (aka violent) crimes. • Next we looked at their predictive validity separately and together

  24. Substance Problem Severity predicted residential placement Probability of Being Placed in Residential Treatment at Intake 100% Crime/ Violence did not predict residential placement 80% Probability of Residential Placement 60% 40% 20% Crime and Violence Scale Substance Problem Scale 0% High High Mod. Mod. Low Low Source: CYT & ATM Data

  25. Substance Problem Severity predicted Relapse However knowing both was the best predictor Probability of Using at Month 12 100% (Intake) Crime/ Violence did not predict relapse 80% Probability of Using at Month 12 60% 40% 20% Crime and Violence Scale Substance Problem Scale 0% High High Mod. Mod. Low Low Source: CYT & ATM Data

  26. Includes days of aggression towards others and victimization by others Recall that the effects of treatment are mediated by the extent to which they lead to actual changes in the recovery environment or peer group Includes substance use, fighting, and illegal activity by peers Subsequent Violence, Victimization, and Illegal Activity (by self and others) is one of the Major Environmental Predictors of Relapse Baseline Family .32 .77 .18 Conflict Recovery Environment -.54 -.13 Risk .17 .58 .74 Family .22 .32 -.09 Substance- Cohesion Substance .43 Related Use .32 Problems .82 .19 .11 .19 Social -.08 .22 Social Support Baseline Baseline Risk Model Fit CFI=.97 to .99 RMSEA=.04 to .06 .21 Baseline Source: Godley et al (2005)

  27. Crime/ Violence predicted recidivism Substance Problem Severity predicted recidivism Knowing both was the best predictor Crime/Violence and Substance Problems Interact to Predict Recidivism 12 month recidivism 100% 80% 60% 40% 20% Crime and Violence Scale Substance Problem Scale 0% High High Mod. Mod. Low Low Source: CYT & ATM Data

  28. 100% 80% Crime/ Violence predicted violent recidivism 60% 40% 20% 0% Knowing both was the best predictor Crime/Violence and Substance Problems Interact to Predict Violent Crime or Arrest 12 month recidivism To violent crime or arrest Crime and Violence Scale Substance Problem Scale High High Mod. Mod. (Intake) Substance Problem Severity did not predict violent recidivism Low Low Source: CYT & ATM Data

  29. Discussion of SPS and CVS • The GAIN’s SPS and CVS scales appears to be face valid, internally consistent and to have good construct validity. • While placement in residential treatment focuses on substance use severity, CVS helps to predict relapse. This suggests the need to consider crime and violence more closely in placement decisions. • Conversely, SPS helps to predict recidivism. This suggests the potential benefits of screening for substance use problems in juvenile justice settings. • The next step is to combine these variables with other factors in a multivariate model. • We also need to replicate these findings, preferably with a sample not presenting for treatment and with urine and record checks.

  30. The Effectiveness of Programs for Juvenile Offenders N of Offender Sample Studies Preadjudication (prevention) 178 Probation 216 Institutionalized 90 Aftercare 25 Total 509 Source: Adapted from Lipsey, 1997, 2005

  31. Most Programs are actually a mix of components Average of 5.6 components distinguishable in program descriptions from research reports Intensive supervision Prison visit Restitution Community service Wilderness/Boot camp Tutoring Individual counseling Group counseling Family counseling Parent counseling Recreation/sports Interpersonal skills Anger management Mentoring Cognitive behavioral Behavior modification Employment training Vocational counseling Life skills Provider training Casework Drug/alcohol therapy Multimodal/individual Mediation Source: Adapted from Lipsey, 1997, 2005

  32. Most programs have small effectsbut those effects are not negligible • The median effect size (.09) represents a reduction of the recidivism rate from .50 to .46 • Above that median, most of the programs reduce recidivism by 10% or more • One-fourth of the studies show recidivism reductions of 30% or more, that is, a recidivism rate of .35 or less for the treatment group compared to .50 for the control group • The “nothing works” claim that rehabilitative programs for juvenile offenders are ineffective is false Source: Adapted from Lipsey, 1997, 2005

  33. Major Predictors of Bigger Effects • Chose a strong intervention protocol based on prior evidence • Used quality assurance to ensure protocol adherence and project implementation • Used proactive case supervision of individual • Used triage to focus on the highest severity subgroup

  34. Impact of the numbers of Favorable features on Recidivism (509 JJ studies) Usual Practice has little or no effect Source: Adapted from Lipsey, 1997, 2005

  35. Some Programs Have Negative or No Effects on recidivism • “Scared Straight” and similar shock incarceration program • Boot camps mixed – had bad to no effect • Routine practice – had no or little (d=.07 or 6% reduction in recidivism) • Similar effects for minority and white (not enough data to comment on males vs. females) • The common belief that treating anti-social juveniles in groups would lead to more “iatrogenic” effects appears to be false on average (i.e., relapse, violence, recidivism for groups is no worse then individual or family therapy) Source: Adapted from Lipsey, 1997, 2005

  36. Program types with average or better effects on recidivism AVERAGE OR BETTERBETTER/BEST Preadjudication Drug/alcohol therapy Interpersonal skills training Parent training Employment/job training Tutoring Group counseling Probation Drug/alcohol therapy Cognitive-behavioral therapy Family counseling Interpersonal skills training Mentoring Parent training Tutoring Institutionalized Family counseling Behavior management Cognitive-behavioral therapy Group counseling Employment/job training Individual counseling Interpersonal skills training Source: Adapted from Lipsey, 1997, 2005

  37. Cognitive Behavioral Therapy (CBT) Interventions that Typically do Better than Practice in Reducing Recidivism (29% vs 40%) • Aggression Replacement Training • Reasoning & Rehabilitation • Moral Reconation Therapy • Thinking for a Change • Interpersonal Social Problem Solving • Multisystemic Therapy • Functional Family Therapy • Multidimensional Family Therapy • Adolescent Community Reinforcement Approach • MET/CBT combinations and Other manualized CBT NOTE: Generally little or no differences in mean effect size between these brand names Source: Adapted from Lipsey et al 2001, Waldron et al, 2001, Dennis et al, 2004

  38. Implementation is Essential (Reduction in Recidivism from .50 Control Group Rate) The best is to have a strong program implemented well The effect of a well implemented weak program is as big as a strong program implemented poorly Thus one should optimally pick the strongest intervention that one can implement well Source: Adapted from Lipsey, 1997, 2005

  39. Conclusions • Research shows that intervention programs can be very effective for reducing the recidivism of juvenile offenders, even in routine practice • Program selection and strong implementation are critical; otherwise effects quickly slide to zero (or worse) • What evidence we have about the effects of programs in routine practice indicates that most are not very effective– there is plenty of room for improvement

  40. Next Steps • Currently working on evaluating RWJF reclaiming futures diversion projects, CSAT young offender re-entry projects, drug court projects and several individual juvenile justice projects • Doing more work on predicting risk of recidivism and how they related to substance use disorders, co-morbidity, and environmental factors

  41. Resources and References • Copy of these slides and handouts • http://www.chestnut.org/LI/Posters/ • References cited Dennis, M. L., Godley, S. H., Diamond, G., Tims, F. M., Babor, T., Donaldson, J., Liddle, H., Titus, J. C., Kaminer, Y., Webb, C., Hamilton, N., & Funk, R. (2004). The Cannabis Youth Treatment (CYT) Study: Main Findings from Two Randomized Trials. Journal of Substance Abuse Treatment, 27, 197-213. Dennis, M. L., Titus, J. C., White, M., Unsicker, J., & Hodgkins, D. (2003). Global Appraisal of Individual Needs (GAIN) Administration guide for the GAIN and related measures. (Version 5 ed.). Bloomington, IL Chestnut Health Systems. Retrieve from http//www.chestnut.org/li/gain Dennis, M.L., & White, M.K. (2003). The effectiveness of adolescent substance abuse treatment: a brief summary of studies through 2001, (prepared for Drug Strategies adolescent treatment handbook). Bloomington, IL: Chestnut Health Systems. [On line] Available at http://www.drugstrategies.org Dennis, M. L. and White, M. K. (2004). Predicting residential placement, relapse, and recidivism among adolescents with the GAIN. Poster presentation for SAMHSA's Center for Substance Abuse Treatment (CSAT) Adolescent Treatment Grantee Meeting; Feb 24; Baltimore, MD. 2004 Feb. Godley, M. D., Kahn, J. H., Dennis, M. L., Godley, S. H., & Funk, R. R. (2005). The stability and impact of environmental factors on substance use and problems after adolescent outpatient treatment. Psychology of Addictive Behaviors. Lipsey, M. W. (1997). What can you build with thousands of bricks? Musings on the cumulation of knowledge in program evaluation. New Directions for Evaluation, 76, 7-24. Lipsey, M.W. (2005). What Works with Juvenile Offenders: Translating Research into Practice. Adolescent Treatment Issues Conference, February 28, Tampa, FL Lipsey, M.W., Chapman, G.L., & Landenberger, N.A. (2001).  Cognitive-Behavioral Programs for Offenders.  The ANNALS of the American Academy of Political and Social Science, 578(1), 144-157 Waldron, H. B., Slesnick, N., Brody, J. L., Turner, C. W., & Peterson, T. R. (2001). Treatment outcomes for adolescent substance abuse at four- and seven-month assessments. Journal of Consulting and Clinical Psychology, 69(5), 802-812. White, M. K., Funk, R., White, W., & Dennis, M. (2003). Predicting violent behavior in adolescent cannabis users The GAIN-CVI. Offender Substance Abuse Report, 3(5), 67-69.

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