Advances in Adolescent Substance Abuse Treatment and Research Michael Dennis, Ph.D. Chestnut Health Systems, Bloomington, IL Presentation for the Adolescent Treatment Initiative, Concord, NH, April 20, Sponsored by New Futures. 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 and several individual grants. The opinions are those of the author and do not reflect official positions of the consortium or government. Available on line at or by contacting Joan Unsicker at 720 West Chestnut, Bloomington, IL 61701, phone: (309) , fax: (309) ,

Examine the prevalence, course, and consequences of adolescent substance use and co-occurring disorders Examine the rates of use, substance use disorders (SUD) and unmet treatment needs in the US and NH Summarize major trends in the adolescent treatment system Review the current knowledge base on treatment effectiveness Examine the results of recent major studies Examine how characteristics vary by intensity of juvenile justice system involvement Goals of this Presentation

Relationship between Past Month Substance Use and Age Source: Dennis (2002) and 1998 NHSDA

Age of First Use Predicts Dependence an Average of 22 years Later Source: Dennis, Babor, Roebuck & Donaldson (2002) and 1998 NHSDA

Source: OAS (2004). Results from the 2003 National Survey on Drug Use and Health: National Findings. Rockville, MD: SAMHSA. The Growing Incidence of Adolescent Marijuana Use: Adult Initiation Relatively Stable Adolescent Initiation Rising

Importance of Perceived Risk Source: Office of Applied Studies. (2000) NHSDA Marijuana Use Risk & Availability

Actual Marijuana Risk From 1980 to 1997 the potency of marijuana in federal drug seizures increased three fold. The combination of alcohol and marijuana has become very common and appears to be synergistic and leads to much higher rates of problems than would be expected from either alone. Combined marijuana and alcohol users are 4 to 47 times more likely than non-users to have a wide range of dependence, behavioral, school, health and legal problems. Marijuana and alcohol are the leading substances mentioned in arrests, emergency room admissions, autopsies, and treatment admissions.

Source: Dennis and McGeary (1999) and 1997 NHSDA Substance Use in the Community

Consequences of Substance Use Source: Dennis, Godley and Titus (1999) and 1997 NHSDA

Source: D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA Adolescents with Past Year Alcohol or Other Drug (AOD) Abuse or Dependence National=8.92% NH=12.21%

Adolescents Needing But Not Receiving Treatment for Alcohol Use Source: D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA National=5.55% NH=8.24%

Source: D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA Adolescents Needing But Not Receiving Treatment for Illicit Drug Use National=5.14% NH=6.99%

Rates of Use in NH by Age Age Age Age 26+ Any Alcohol Use Binge Alcohol Use Any Past Month Illicit Drug Use Any Past Month Marijuana Use Any Past Month Illicit Beside Marijuana Source: D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA.

Rates of SUD and Unmet Tx Need in NH by Age Source: D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA Age Age 26+ Age Abuse or Dependence Unmet Treatment Need Drug Alcohol Either

Adolescent Treatment Admissions have increased by 50% over the past decade Source: Office of Applied Studies Treatment Episode Data Set (TEDS) 50% higher than in 1992

Change in Primary Substance Source: OAS 2004, Treatment Episode Data Set (TEDS) Rockville, MD: SAMHSA % increase in marijuana -50% decrease in alcohol +375% increase in stimulants -21% decrease in cocaine +144% increase in opiates

Change in Referral Sources Source: OAS 2004, Treatment Episode Data Set (TEDS) Rockville, MD: SAMHSA JJ referrals have doubled and are driving growth

Primary Substance by Referral Source Source: OAS 2004, Treatment Episode Data Set (TEDS) Rockville, MD: SAMHSA More recent marijuana referrals driven more by JJ

Level of Care at Admission Intensive Outpatient 11% Detox. or Hospital 5% Short-Term Residential 6% Long-Term Residential 9% Outpatient 68% Source: Dennis, Dawud-Noursi, Muck & McDermeit, 2002 and 1998 Treatment Episode Data Set (TEDS) Most Adolescents are treated in Outpatient Settings

Severity Varies by Level of Care 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Weekly use at intake DependenceFirst used under age 15 Prior Treatment Outpatient (n=24704) Intensive Outpatient (n=4024) Detoxification or Hospital (n=2062) Short Term Residential (n=2046) Long Term Residential (n=3124) Source: Dennis, Dawud-Noursi, Muck & McDermeit, 2002 and 1998 Treatment Episode Data Set (TEDS) Severity goes up with level of care STR clients get there younger and sooner * Weekly use is the Norm * 1 in 5 report with no past month use

Key Problems in the System Less than 1/10th of adolescents with substance dependence problems receive treatment Less than 50% stay 6 weeks Less than 75% stay the 3 months recommended by NIDA Under 25% in Residential Treatment successfully step down to outpatient care Little is known about the rate of initiation after detention The size of the NH system is actually coming out of a 7 year decline in admissions Source: Dennis, Dawud-Noursi, Muck, & McDermeit (Ives), 2002; Godley et al., 2002; Hser et al., 2001; OAS, 2000

NH is also a Heterogeneous Mix of Urban, Small Urban & Rural Systems 1,235,786 people in 9,345 square miles (137.8 people per square mile or ppsm) Ranges from 18.8 ppsm in Coos County to ppsm in Hillsborough County Approximately 9% age , 4% age 18-20, 71% age 21+ Source: U.S. Census 2000 <-US avg. 79.6

Pre-2002 Knowledge Base from 36 Studies 9 large multi-site longitudinal studies (ATM, DARP, TOPS, SROS, TCA, NTIES, DATOS-A, DOMS), including 1 large multi-site experiment (Cannabis Youth Treatment - CYT) 24 behavioral treatment studies (12-step, behavioral, family, other outpatient, inpatient, therapeutic communities, engagement, aftercare), including CYT and 1 pharmacology- behavioral (CBT) trial 8 pharmacology treatment studies (bupropion, disulfiram, fluoxetine, lithium, pemoline, sertaline) and 1 pharmacology- behavioral (CBT) trial Source: Bukstein & Kithas, 2002; Dennis & White (2003), & Lewinsohn et al. 1993; PNLDP, 2003

Key Lessons from Early Literature Assessment needs to be very concrete Multiple co-occurring problems are the norm in clinical samples of SUD adolescents (60-80% external disorders, 25-60% mood disorders, 16-45% anxiety disorders, 70-90% 3 or more diagnoses) Adolescents are involved in multiple systems competing to control their behavior (e.g, family, peers, school, work, criminal justice, and controlled environments) Relapse is common in the first 3-12 months Recovery often takes multiple attempts and episodes of care that may take years Improvements generally come during active treatment and are sustained for 12 or more months Family therapies are associated with less initial change but more change post active treatment and less relapse

Interventions associated with reduced substance use and problems: 1 experimental and 3 non-experimental studies of 12-step treatment (e.g., CD, Hazelden) 7 experimental studies of behavior therapies (e.g., ACRA, AGT, BTOS, CBT, MET, RP) 8 experimental studies of family therapy (CFT, FDE, FFT, FSN, FST, MDFT, MST, PBFT, TIPS) 6 longitudinal studies of existing outpatient 6 longitudinal studies of existing short term residential/inpatient 7 longitudinal studies of therapeutic communities (TC) and other forms of long term residential treatment (LTR) Another 3 experimental studies have shown that engagement and retention are associated with several interventions (case management, stepping down residential to OP, assertive aftercare)

Lessons from 9 Pharmacology Studies No controlled trials of medication for treating withdrawal, substitution therapy, blocking therapy, aversive therapy or management of cravings – Though NIDA’s Clinical Trials Network (CTN) and Australian researchers are currently studying the effects of Buprenorphine/Naloxone Most studies of other disorders exclude adolescents with substance use disorders Small (n of 8-25), short-term (4-12 weeks) studies suggest medication can be used to effectively treat several co- occurring problems: – Fluoxetine (Prozac®) & Sertaline (Zoloft®) helped reduce depressive symptoms – Lithium carbonate (Eskalith®) reduced bipolar symptoms and positive urine rates – Pemoline (Cylert®) and Bupropion (Wellbutrin®) reduced symptoms of ADHD

Effectiveness was also associated with therapies that technologically were: manual-guided had developmentally appropriate materials involved more quality assurance and clinical supervision achieved therapeutic alliance and early positive outcomes successfully engaged adolescents in aftercare, support groups, positive peer reference groups, more supportive recovery environments

Lessons about what did NOT work Interventions associated with No or Minimal Change: Passive referrals Educational units alone Probation services as usual Early unstandardized outpatient services as usual Interventions associated with Deterioration: treatment of adolescents in badly managed groups or “groups including one or more highly deviant individuals” (but NOT! all groups or any CD) treatment of adolescents in adult units and/or with adult models/materials (particularly outpatient)

Key Points that Have Been Contentious As other therapies have improved, there is no longer the clear advantage of family therapy found in early literature reviews While there have been concerns about the potential iatrogenic effects of group therapy, the rates do not appear to be appreciably different from individual or family therapy if it is done well (important since group tx typically costs less) Effectiveness was not consistently associated with the amount of therapy over a short period of time (6-12 weeks) but was related to longer term continuing care Over time, adolescents regularly cycle between use, treatment, incarceration and recovery Treatment primarily impacts the short term movement from use to non use in the community The long term effectiveness of therapy was dependent on changes in the long term recovery environment and social risk

Limitations of the Early Literature Small sample sizes (most under 50) High rates (30-50%) of refusals by eligible people Unstandardized measures, no measures of abuse or dependence, no measures of co-morbidity, crime or violence (just arrest) Unstandardized and minimally-supervised therapies (making replication very difficult) Minimal information on services received High rates (20-50%) of treatment dropout High rates of attrition from follow-up (25-54%) leading to potentially large (unknown) bias

Studies are Improving! New studies are likely to have higher rates of participation (70-90%), treatment completion (70-85%), and successful follow-up (85-95%) They are more likely to involve standardized assessments, manual-guided therapy, and better quality assurance/clinical supervision They have experimental design, multiple time points of assessment and follow-up lasting 1 or more years They include economic analysis of their costs, cost- effectiveness and benefit cost They have agreed to pool their data to facilitate further comparisons and secondary analysis

Studies by Date of First Publication From 1998 to 2002 the number of adolescent treatment studies doubled and has doubled again in the past 2 years – with twice this many published in the past 2 years and over 100 adolescent treatment studies currently in the field Source: Dennis &, White (2003) at

Studies with Publications Currently Coming Out NIDA’s Drug Abuse Treatment Outcome Study of Adolescents (DATOS-A) Drug Abuse Treatment Outcome Study (DOMS) CSAT’s Cannabis Youth Treatment (CYT) experiments NIAAA/CSAT’s 14 individual research grants CSAT’s 10 Adolescent Treatment Models (ATM) CSAT’s Persistent Effects of Treatment Study (PETS-A) CSAT’s 12 Strengthening Communities for Youth (SCY) RWJF’s 10 Reclaiming Futures (RF) diversion projects CSAT’s 12+ Targeted Capacity Expansion TCE/HIV NIDA’s 12 individual research grants CSAT’s 17 Adolescent Residential Treatment (ART) NIDA’s Criminal Justice Drug Abuse Treatment Study (CJ-DATS) CSAT’s 36 Effective Adolescent Treatment (EAT) NIAAA/CSAT’s study of diffusion of innovation Full ( ) or Partial ( ) use of the Global Appraisal of Individual Needs (GAIN)

Source: NIAAA/NIDA Other Grantees CSAT Cannabis Youth Treatment (CYT) Adolescent Treatment Model (ATM) Strengthening Communities for Youth (SCY) Adolescent Residential Treatment (ART) Effective Adolescent Treatment (EAT) Targeted Capacity Expansion (TCE) grants Other Collaborators RWJF Reclaiming Futures Program Other RWJF Grantees Other Grants/Contracts Co-occurring Disorder Studies Young Offender Re-Entry Program (YORP) Adolescent Treatment Program GAIN Clinical Collaborators State, County, or Agency-wide systems (also negotiating with 12 states/counties)

Since 1997, the data has been pooled to create one of the largest benchmark data sets in the field 17,464 32,054 57, ,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 Cumulative GAIN Interviews (observations) Prior to FY2003 FY2004FY2005 FY2006 Largest Combined Adolescent Data Set ~ Half of all Adolescent Treatment Data One of the Largest Data Sets in the Field with 1+ year follow-up (2 nd only to ASI) 74,670..and we are still growing

Normal Adolescent Development Biological changes in the body, brain, and hormonal systems that continue into mid-to-late 20s. Shift from concrete to abstract thinking. Improvements in the ability to link causes and consequences (particularly strings of events over time). Separation from a family-based identity and the development of peer- and individual-based identities. Increased focus on how one is perceived by peers. Increasing rates of sensation seeking/trying new things. Development of impulse control and coping skills. Concerns about avoiding emotional or physical violence.

Key Adaptation for Adolescents Examples need to be altered to relevant substances, situations, and triggers Consequences have to be altered to things of concern to adolescents Most adolescents do not recognize their substance use as a problem and are being mandated to treatment All materials need to be converted from abstract to concrete concepts Co-morbid problems (mental, trauma, legal) are the norm and often predate substance use Treatment has to take into account the multiple systems (family, school, welfare, criminal justice) Less control of life and recovery environment Less aftercare and social support Complicated staffing needs

Length of Stay Varies by Level of Care Source: Adolescent Treatment Model (ATM) Data

Adolescents often go through multiple levels of care Source: Adolescent Treatment Model (ATM) Data Length of Stay Across Episodes of care is about 50% longer

Program Evaluation Data Level of CareClinicsAdolescents1+ FU* Outpatient/ Intensive Outpatient (OP/IOP) % Long Term Residential (LTR)**439098% Short Term Residential (STR)** % Total % * Completed follow-up calculated as 1+ interviews over those due-done, with site varying between 2-4 planned follow-up interviews. Of those due and alive, 89% completed with 2+ follow-ups, 88% completed 3+ and 78% completed 4. ** Both LTR and STR include programs using CD and therapeutic community models

Years of Use Source: Adolescent Treatment Model (ATM) data

Patterns of Weekly (13+/90) Use Source: Adolescent Treatment Model (ATM) data OP/IOP (n=560)LTR (n=390)STR (n=594) Weekly use of anythingWeekly Marijuana Use Weekly Alcohol UseWeekly Crack/Cocaine Use Weekly Heroin/Opioid Use Weekly Other Drug Use Days in Controlled Environment

Substance Use Severity Source: Adolescent Treatment Model (ATM) data

Change in Substance Frequency Index by Level of Care\a \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.

Change in Substance Problem Index by Level of Care\a \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.

Percent in Recovery (no past month use or problems while living in the community) \a Source: Adolescent Treatment Model (ATM) data; Levels of cares 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.

Multiple Co-occurring Problems Were the Norm and Increased with Level of Care Source: CSAT’s Cannabis Youth Treatment (CYT) and Adolescent Treatment Model (ATM), Conduct Disorder ADHDMajor Depressive Disorder Generalized Anxiety Disorder Traumatic Stress Disorder Any Co- Occurring Disorder OutpatientLong Term ResidentialShort Term Residential

Change in Emotional Problem Index by Level of Care\a \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.

Pattern of SA Outcomes is Related to the Pattern of Psychiatric Multi-morbidity Source: Shane et al 2003, PETSA data Months Post Intake (Residential only) Number of Past Month Substance Problems 2+ Co-occurring 1 Co-occurring No Co-occurring Multi-morbid Adolescents start the highest, change the most, and relapse the most

High Rates of Victimization are the Norm Source: Adolescent Treatment Model (ATM) data

Victimization Is Related to Severity Source: Titus, Dennis, et al., Substance Frequency Index (SFI6P; f=.13) Substance Problem Index (SPI16; f=.21) General Mental Distress Index (GMDI; f=.32) Traumatic Stress Index (TSI; f=.25) General Conflict Tactic Index (GCTI; f=.20) Effect Size (f) High (n=102) Moderate (31) Low (n=80) Use goes up with Moderate Victim. Pathology goes up with High Victim.

Victimization Also Interacts with Level of Care to Predict SA Outcomes Source: Funk, et al., Intake6 MonthsIntake6 Months Marijuana Use (Days of 90) OP -AcuteOP - Low/Cl.Resid-AcuteResid - Low/Cl. Outpatient Residential Traumatized groups have higher severity Acute trauma group does not respond to OP Both groups respond to residential treatment

Broad Range of Past Year Illegal Activity Source: Adolescent Treatment Model (ATM) data OP/IOP (n=560)LTR (n=390)STR (n=594) Any illegal activityProperty crimesInterpersonal crimes Drug related crimesActs of physical violence

Change in Illegal Activity Index by Level of Care\a \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.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Low (n=150)Moderate (n=158)High (n=216) No crime Incarcerated Substance Use only Non-violent crime Violent crime X2(8)=18.36, p<.05 GAIN’s Crime and Violence Scale at Intake can predict 30 Months Recidivism Odds of committing violent crime 4.5 times higher Source: White et al (2003), PETSA

Crime/Violence and Substance Problems Interact to Predict Recidivism Low Mod. High Low Mod. High 0% 20% 40% 60% 80% 100% Substance Problem Scale (Abuse/Dependence symptoms) Crime and Violence Scale Source: Dennis et al 2004 Probability of 12 month recidivism The probability of committing another crime goes up with the CVS score The probability of committing another crime goes up with the SPS score Knowing both is the best predictor

Findings from the Assertive Continuing Care (ACC) Experiment 183 adolescents admitted to residential substance abuse treatment Treated for days inpatient, then discharged to outpatient treatment Random assignment to usual continuing care (UCC) or “assertive continuing care” (ACC) Source: Godley et al 2002

Assertive Continuing Care (ACC) Enhancements Continue to participate in UCC Home Visits Sessions for adolescent, parents, and together Sessions based on ACRA manual (Godley, Meyers et al., 2001) Case Management based on ACC manual (Godley et al, 2001) to assist with other issues (e.g., job finding, medication evaluation)

Assertive Continuing Care (ACC) Hypotheses Assertive Continuin g Care General Continuin g Care Adherence Relative to UCC, ACC will increase General Continuing Care Adherence (GCCA) Early Abstinence GCCA (whether due to UCC or ACC) will be associated with higher rates of early abstinence Sustained Abstinence Early abstinence will be associated with higher rates of long term abstinence.

Usual Continuing Care (UCC): Expectation vs. Performance Source: Godley et al % 10% 20% 30%40%50%60%70%80%90%100% 0% 10% 20% 30%40%50%60%70%80%90%100% Expected WeeklyTx Weekly 12 step meetings Regular urine tests Contact w/probation/school Follow up on referrals Relapse prevention Communication skills training Problem solving component Meet with parents 1-2x month Weekly telephone contact Referrals to other services Discuss probation/school compliance Adherence: Meets 7/12 criteria UCC

ACC Improved Adherence Source: Godley et al 2002, forthcoming 0% 10% 20% 30% 40%50%60%70%80% WeeklyTx Weekly 12 step meetings Regular urine tests Contact w/probation/school Follow up on referrals* ACC * p<.05 90% 100% Relapse prevention* Communication skills training* Problem solving component* Meet with parents 1-2x month* Weekly telephone contact* Referrals to other services* Discuss probation/school compliance* Adherence: Meets 7/12 criteria* UCC

GCCA Improved Early (0-3 mon.) Abstinence Source: Godley et al 2002, forthcoming 24% 36% 38% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any AOD (OR=2.16*)Alcohol (OR=1.94*) Marijuana (OR=1.98*) Low (0-6/12) GCCA 43% 55% High (7-12/12) GCCA * p<.05

Early (0-3 mon.) Abstinence Improved Sustained (4-9 mon.) Abstinence Source: Godley et al 2002, forthcoming 19% 22% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any AOD (OR=11.16*)Alcohol (OR=5.47*) Marijuana (OR=11.15*) Early(0-3 mon.) Relapse 69% 59% 73% Early (0-3 mon.) Abstainer * p<.05

Next Steps for ACC Preliminary findings and manual published, main findings under review Currently in use in eight clinical sites ACC 2 experiment is currently testing – the ACC intervention model in a multi-site trial – whether or not participants get contingency management (CM) alone or with ACC – CM is targeted at reducing use and increasing prosocial activities

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

Intensity by Level of Care 0%10%20%30%40%50%60%70%80%90%100% Short Term Residential Long Term Residential Outpatient/IOP Step Down OP Total 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

Intensity by Demographics 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Female Caucasian African American Hispanic Native American Other Females and Caucasians more likely in lower intensity Minorities More Likely to be in higher intensity

Intensity by Demographics (continued) 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Age Years Age Years Age 18+ Years Single Parent High Severity More likely to be years olds and from Single Parent Families Low Intensity More Likely to be Still Committing Crime

Intensity by Substance Use Disorder Diagnosis 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any Substance DisorderDependence Abuse Current Intensity Inversely related to Substance Use Severity Past Involvement a Mix of Severity

Intensity by External Diagnoses 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any External Conduct DisorderADHD

Intensity by Internal Diagnoses/Problems 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any Internal Major Depression Suicide Ideation Generalized Anxiety Trauma Related Curvilinear Relationship between Intensity and Internal Distress

Intensity by Pattern of Co-occurring Disorders 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% None Internal Only External Only Both Most Internal Distress is Multi-morbid with External (and Substance Use) Disorders

Intensity by Other Common Problems 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 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Any Victimization High levels of Victimization Any Crime High Crime/ Violence Homeless or Runaway High Health Problems Focus of JJ Detention

Concluding Comments We are entering a renaissance of new knowledge in this area, but are only reaching 1 of 10 in need Several interventions work, but 2/3 of the adolescents are still having problems 12 months later We need to move beyond focusing on minor variations in therapy (behavioral brand names) and acute episodes of care to focus on continuing care and a recovery management paradigm It is very difficult to predict exactly who will relapse so it is essential to conduct aftercare monitoring with all adolescents Juvenile justice referrals are a central factor in recent growth of the adolescent treatment system and the intensity of JJ involvement is correlated with clinical severity

Resources Copy of these slides and handouts – Assessment Instruments – CSAT TIP 3 at – NIAAA Assessment Handbook, – GAIN Coordinating Center Adolescent Treatment Manuals – CSAT CYT, ATM, ACC and other manuals at or – SAMHSA at or NCADI at Adolescent Treatment Programs and Studies – List of programs by state and summary of pre-2002 studies at – Cannabis Youth Treatment (CYT) : – Persistent Effects of Treatment Study of Adolescents (PETSA): (then select PETS from program resources) – Adolescent Program Support Site (APSS): Society for Adolescent Substance Abuse Treatment Effectiveness (SASATE) – Website at with bibliography – Darren Fulmore to be added to list server – Next conference is March 21-23, 2005, See website or Darren for information about meeting

References Babor, T. F., Webb, C. P. M., Burleson, J. A., & Kaminer, Y. (2002). Subtypes for classifying adolescents with marijuana use disorders Construct validity and clinical implications. Addiction, 97(Suppl. 1), S58-S69. Buchan, B. J., Dennis, M. L., Tims, F. M., & Diamond, G. S. (2002). Cannabis use Consistency and validity of self report, on- site urine testing, and laboratory testing. Addiction, 97(Suppl. 1), S98-S108. Bukstein, O.G., & Kithas, J. (2002) Pharmacologic treatment of substance abuse disorders. In Rosenberg, D., Davanzo, P., Gershon, S. (Eds.), Pharmacotherapy for Child and Adolescent Psychiatric Disorders, Second Edition, Revised and Expanded. NY, NY: Marcel Dekker, Inc. Dennis, M.L., (2002). Treatment Research on Adolescents Drug and Alcohol Abuse: Despite Progress, Many Challenges Remain. Connections, May, 1-2,7, and Data from the OAS 1999 National Household Survey on Drug Abuse Dennis, M.L. (2004). Traumatic victimization among adolescents in substance abuse treatment: Time to stop ignoring the elephant in our counseling rooms. Counselor, April, Dennis, M.L., & Adams, L. (2001). Bloomington Junior High School (BJHS) 2000 Youth Survey: Main Findings. Bloomington, IL: Chestnut Health Systems Dennis, M. L., Babor, T., Roebuck, M. C., & Donaldson, J. (2002). Changing the focus The case for recognizing and treating marijuana use disorders. Addiction, 97 (Suppl. 1), S4-S15. Dennis, M.L., Dawud-Noursi, S., Muck, R., & McDermeit, M. (2003). The need for developing and evaluating adolescent treatment models. In S.J. Stevens & A.R. Morral (Eds.), Adolescent substance abuse treatment in the United States: Exemplary Models from a National Evaluation Study (pp. 3-34). Binghamton, NY: Haworth Press and 1998 NHSDA. 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, Dennis, M. L., Godley, S. and Titus, J. (1999). Co-occurring psychiatric problems among adolescents: Variations by treatment, level of care and gender. TIE Communiqué (pp. 5-8 and 16). Rockville, MD: Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment. Dennis, M. L., Perl, H. I., Huebner, R. B., & McLellan, A. T. (2000). Twenty-five strategies for improving the design, implementation and analysis of health services research related to alcohol and other drug abuse treatment. Addiction, 95, S281- S308. Dennis, M. L. and McGeary, K. A. (1999). Adolescent alcohol and marijuana treatment: Kids need it now. TIE Communiqué (pp ). Rockville, MD: Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment.

References - continued Dennis, M. L., Titus, J. C., Diamond, G., Donaldson, J., Godley, S. H., Tims, F., Webb, C., Kaminer, Y., Babor, T., Roebeck, M. C., Godley, M. D., Hamilton, N., Liddle, H., Scott, C., & CYT Steering Committee. (2002). The Cannabis Youth Treatment (CYT) experiment Rationale, study design, and analysis plans. Addiction, 97, 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// 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 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 Feb. Diamond, G., Leckrone, J., & Dennis, M. L. (In press). The Cannabis Youth Treatment study Clinical and empirical developments. In R. Roffman, & R. Stephens, (Eds.) Cannabis dependence Its nature, consequences, and treatment. Cambridge, UK Cambridge University Press. Diamond, G., Panichelli-Mindel, S. M., Shera, D., Dennis, M. L., Tims, F., & Ungemack, J. (in press). Psychiatric syndromes in adolescents seeking outpatient treatment for marijuana with abuse and dependency in outpatient treatment. Journal of Child and Adolescent Substance Abuse. French, M.T., Roebuck, M.C., Dennis, M.L., Diamond, G., Godley, S.H., Tims, F., Webb, C., & Herrell, J.M. (2002). The economic cost of outpatient marijuana treatment for adolescents: Findings from a multisite experiment. Addiction, 97, S84-S97. French, M. T., Roebuck, M. C., Dennis, M. L., Diamond, G., Godley, S. H., Liddle, H. A., and Tims, F. M. (2003). Outpatient marijuana treatment for adolescents Economic evaluation of a multisite field experiment. Evaluation Review,27(4) Funk, R. R., McDermeit, M., Godley, S. H., & Adams, L. (2003). Maltreatment issues by level of adolescent substance abuse treatment The extent of the problem at intake and relationship to early outcomes. Journal of Child Maltreatment, 8, Godley, S. H., Dennis, M. L., Godley, M. D., & Funk, R. R. (2004). Thirty-month relapse trajectory cluster groups among adolescents discharged from outpatient treatment. Addiction, 99 (s2), , Godley, M. D., Godley, S. H., Dennis, M. L., Funk, R., & Passetti, L. (2002). Preliminary outcomes from the assertive continuing care experiment for adolescents discharged from residential treatment. Journal of Substance Abuse Treatment, 23, Godley, S. H., Jones, N., Funk, R., Ives, M., and Passetti, L. L. (2004). Comparing Outcomes of Best-Practice and Research- Based Outpatient Treatment Protocols for Adolescents. Journal of Psychoactive Drugs, 36, 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.

References - continued Hser, Y., Grella, C. E., Hubbard, R. L., Hsieh, S. C., Fletcher, B. W., Brown, B. S., & Anglin, M. D. (2001). An evaluation of drug treatments for adolescents in four U.S. cities. Archives of General Psychiatry, 58, Lewinsohn, P.M., Hops, H., Roberts, R.E., Seeley, J.R., Andrews, J.A. (1993). Adolescent psychopathology, I: prevalence and incidence of depression and other DSM-III-R disorders in high school students. J Abn Psychol, 102, National Academy of Sciences (1994). Reducing risks for mental disorders: Frontiers for preventive intervention research. Washington, DC: National Academy Press. Office of Applied Studies. (2000). National Household Survey on Drug Abuse: Main Findings Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved, from Office of Applied Studies (OAS) (1999). Treatment Episode Data Set (TEDS) : National admissions to substance abuse treatment services. Rockville, MD: Author. [Available online at.] Office of Applied Studies (OAS) (2000). Treatment Episode Data Set (TEDS) : National admissions to substance abuse treatment services. Rockville, MD: Author. [Available on line at.] Office of Applied Studies. (2000). National Household Survey on Drug Abuse: Main Findings Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved, from Office of Applied Studies Treatment Episode Data Set (TEDS) retrived from Physician Leadership on National Drug Policy (PNLDP, 2002) Adolescent Substance Abuse: A Public Health Priority. Providence, RI: Brown University. Retrieved from Shane, P., Jasiukaitis, P., & Green, R. S. (2003). Treatment outcomes among adolescents with substance abuse problems: The relationship between comorbidities and post-treatment substance involvement. Evaluation and Program Planning, 26, Tims, F. M., Dennis, M. L., Hamilton, N., Buchan, B. J., Diamond, G. S., Funk, R., & Brantley, L. B. (2002). Characteristics and problems of 600 adolescent cannabis abusers in outpatient treatment. Addiction, 97, Titus, J. C., Dennis, M. L., White, W. L., Scott, C. K., & Funk, R. R. (2003). Gender differences in victimization severity and outcomes among adolescents treated for substance abuse. Journal of Child Maltreatment, 8, 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), White, M. K., White, W. L., & Dennis, M. L. (2004). Emerging models of effective adolescent substance abuse treatment. Counselor, 5(2), D. Wright (2004). State Estimates of Substance Use from the 2002 National Survey on Drug Use and Health. Rockville, MD: OAS, SAMHSA.