1. MAYSIs Across the Nation: What do 70,000 Delinquents Tell Us About Youths’ Mental Health Symptoms? Gina Vincent, Ph.D., Thomas Grisso, Ph.D., Anna Terry, B.A., & Steve Banks, Ph.D. University of Massachusetts Medical School Supported by William T. Grant Foundation Law and Psychiatry Program

2. Prevalence of MH Disorder in JJ (Teplin, 2002; Wasserman, 2002) Based on current studies conducted at a few JJ facilities, it seems 65% of JJ adolescents meet DSM criteria for at least one disorder (vs. 20% in general population) Rates of disorders vary by Gender (higher for girls) Race (highest for Whites and lowest for Blacks)

3. History of the MAYSI Project Identified the need, developed the prototype Field testing, norms, initial validation Preparation for release Released to JJ agencies, developed technical support office, National Youth Screening Assistance Project Developed national norms and MAYSIWARE Evaluation of impact of MH screening on MH services in JJ programs Technical Assistance for MacArthur Foundation’s “Models for Change” Initiative 1994 1996 1998 2000-8 2002-5 2003-5 2006-8

4. Used Statewide in Probation, Detention or Corrections In 38 States AK AL AR AZ CA CO CT DC DE FL GA HI IA ID IL IN KS KY LA MA MD ME MI MN MO MS MT NC ND NE NH NJ NM NV NY OH OK OR PA RI SC SD TN TX UT VA VT WA WI WV WY

5. Purpose/Research Questions Develop national norms for the MAYSI-2 Are there differences between gender, age, and racial groups in the reporting of psychological disturbance (as measured by the Massachusetts Youth Screening Instrument-2; MAYSI-2) among youth in the Juvenile Justice (JJ) System? Are these differences consistent (reliable, generalizable) across JJ systems nationwide?

6. MAYSI-2 Use & Norm Study Donors = Statewide MAYSI-2 User = Norm study donor

7. Method We gathered archival MAYSI-2 records and demographic information from 283 JJ facilities located in 19 states Started With 155,835 youths Removed cases that were: 1) duplicates, 2) outside of the age range, or 3) from any community or treatment facility

8. Final Sample (N = 70,423)

9. Gender: Boys - 78% Girls - 22% Age (years):12-14 - 29%15-17 - 71% Ethnicity/Race: Black- 33% Hispanic - 24% White - 39% Asian – 1% AK Native/Amer Indian - >1% Legal Status:Pre-adj - 77%Post-adj - 23% Time of MAYSI-2 Administration (hrs after intake): First few hours - 56% =/> 48 hrs - 12% Within 24 hrs - 32%

10. MAYSI-2 Data  Gathered Item Responses and Scale Scores ALCOHOL / DRUG USE 8 items ANGRY-IRRITABLE 9 items DEPRESSED-ANXIOUS 9 items SOMATIC COMPLAINTS 6 items SUICIDE IDEATION 5 items THOUGHT DISTURBANCE (boys) 5 items TRAUMATIC EXPERIENCES 5 items Caution Cutoffs: Most generalizable. Based on “clinically significant” scores from corresponding MACI and YSR scales of youth in the general population. Warning Cutoffs: Least generalizable. Compares juveniles to other juvenile offenders to identify the top 10% of the distribution of Massachusetts scores.

11. Research Question Are the national norms for each scale comparable to the original Massachusetts norms?

12. Massachusetts vs National Sample % Above Caution Cut-Off

14. Massachusetts vs National Sample % above Warning Cut-Off

16. Findings Massachusetts > National % youth above cutoffs % youth above cutoffs Alcohol/Drug Scale Angry/Irritable Scale Officially, decreased warning cutoff on Alc/Drug Scale from 7 to 6

17. What Methods of Analysis Could Be Used to Answer The Following Questions? What are the differences between gender, age, and race groups in the reporting of clinically significant levels of symptoms? Where differences exist, were these differences consistent (homogenous) across all sites and across all possible interactions?

18. Meta-analytic Procedures  Unit of Analysis – Site (JJ Facility)  Separate Analyses for Each MAYSI-2 Clinical Scale - TRAUMATIC EXPERIENCES not included  Examined Odds of Scoring > Caution Cut-offs  Past research was done to determine clinically significant levels of disturbance.  Variables for Testing Interactions/Controls  Gender  Age Group (12-14, 15-17)  Race (White, Black, Hispanic)  Legal Status (pre vs. post-adjudication)  Time of MAYSI-2 Administration

19. Meta-analytic Procedures (cont.) Cochran-Mantel-Haenszel (CMH) Calculated Odds Ratios ORs weighted for reliability General Linear Modeling Produce Avg OR across all sites for each effect (Gender, etc) I 2 - Test Homogeneity of ORs If No Explain w/interactions? If Yes Consistent Effect

20. Overall Gender Differences (Main Effects) % Above “Clinical” Cut Off

22. Are Gender Differences Consistent Across Sites & Demographics? Mostly – girls at most all sites, on average, are more likely than boys to report clinically significant levels of symptoms on most MAYSI-2 scales Large Effects: Suicide Ideation OR = 2.4 Medium Effects: Angry-Irritable OR = 1.8 Depressed-Anxious OR = 1.95 – 2.14 Somatic Complaints OR = 1.8

23. When do Gender Differences Vary Across Youths? Alcohol-Drug Scale – gender interacts w/age consistently across sites 12-14 year olds – girls > boys (OR=1.6) 15-17 year olds – no gender difference

24. Overall Age Differences (Main Effects) % Above “Clinical” Cut-Off

26. Are Age Differences Consistent Across Sites & Demographics Mostly – at most all sites, there were no differences or only small differences between younger and older youths in reporting clinically significant levels of symptoms on most MAYSI-2 scales. Small Effects Angry-IrritableOR = 1.3 Thought Disturbance OR = 1.2 Younger youths > older youths

27. When Do Age Differences Vary Across Youths? Alcohol-Drug Scale Older youths > Younger youths OR = 1.7 No appreciable age differences among girls No appreciable differences among youths in custody post-adjudication

28. Overall Race Differences (Main Effects) % Above “Clinical” Cut-Off

34. Are Racial Differences Consistent Across Sites & Demographics? No. Whites, on average, were more likely to report clinically significant levels of symptoms than Blacks or Hispanics, but Results generally were not consistent across sites, and The Meta-analysis was unable to determine the source of the variability in most cases

35. When Do Racial Differences Vary Across Youths? Alcohol Drug Scale Whites > Blacks OR = 2.3 Large ES Hispanics > Blacks OR = 1.7 Medium ES Variability in the magnitude of the odds ratios between Whites & Blacks: Age (larger for older youths) Gate (larger for pre-adjudicated youths) State

36. Site-Level Variables (% of cases) Site-Level Variables (% of cases) Gate: Probation - 36%Pretrial Detention - 42% Corrections (post-adjudicated) - 22% Density: Urban - 78%Rural - 22% Region: West - 17% Midwest - 44% South - 17%Northeast - 22% Test Administration Staff: Non-professional - 70%Professional - 30% Setting:Individual - 87%Group - 13% Method:Voice CD - 28%Self-administer - 64% Staff Administer - 8%

37. Differences by Gate % Above “Clinical” Cut-Off

38. Differences by Region % Above “Clinical” Cut-Off

40. Advantages to the Meta-analytic Approach for Norming Tests Provides the strength and consistency of “prevalence rate” differences across settings and youth characteristics (gender, race, etc.) Provides confidence in the generalizability of these findings across the population of interest

41. Conclusions 1.% of youths scoring above cut-off not substantially different between Massachusetts and National norms 2.Girls in JJ much more likely than boys to report clinically significant symptoms – generalizes across JJ sites

42. Conclusions 3. Wide variability in racial differences: White youths most likely to report problem levels of alcohol or drug use, but the disparity varies across the US White youths, on average, are consistently more likely than black youths to report suicide ideation

43. Future Applications Translating the results to improve juvenile justice programs’ understanding of mental health needs of girls and ethnic minority youths Published a revision of MAYSI-2 manual for mental health screening in juvenile justice Studying whether race differences are “true” differences or measurement bias… Study in progress: Item Response Theory and Psychological Disturbance in Young Offenders (NIMH) (PI: Gina Vincent)