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State of the Art of Treating Adolescent Substance Use Disorders: Course, Treatment System, and Evidence Based Practices Michael Dennis, Ph.D. Chestnut.

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Presentation on theme: "State of the Art of Treating Adolescent Substance Use Disorders: Course, Treatment System, and Evidence Based Practices Michael Dennis, Ph.D. Chestnut."— Presentation transcript:

1 State of the Art of Treating Adolescent Substance Use Disorders: Course, Treatment System, and Evidence Based Practices Michael Dennis, Ph.D. Chestnut Health Systems, Bloomington, IL Presentation at “2005 State Adolescent Coordinators (SAC) Grantee Orientation Meeting”, November 28-30, 2005, Baltimore, MD. 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 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 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 2 1.Epidemiological Course : Examining the prevalence, course, and consequences of adolescent substance use and co-occurring disorders and the unmet need for treatment 2.The Treatment System: Summarizing major trends in the adolescent treatment system and the variability by state 3.Evidence Based Practice: Highlighting what it takes to move the field towards evidenced based practice related to assessment, treatment, program evaluation and planning 4.Treatment Effectiveness: Findings from four recent treatment outcome studies. Four Parts of this Presentation

3 3 Part 1 Epidemiological Course: Examining the prevalence, course, and consequences of adolescent substance use and co-occurring disorders and the unmet need for treatment

4 4 Severity of Past Year Substance Use/Disorders (2002 U.S. Household Population age 12+= 235,143,246) Dependence 5% Abuse 4% Regular AOD Use 8% Any Infrequent Drug Use 4% Light Alcohol Use Only 47% No Alcohol or Drug Use 32% Source: 2002 NSDUH

5 5 Problems Vary by Age Source: 2002 NSDUH and Dennis et al forthcoming 0 10 20 30 40 50 60 70 80 90 100 12-1314-1516-1718-2021-2930-3435-4950-64 65+ No Alcohol or Drug Use Light Alcohol Use Only Any Infrequent Drug Use Regular AOD Use Abuse Dependence NSDUH Age Groups Severity Category Adolescent Onset Remission Increasing rate of non- users

6 6 Higher Severity is Associated with Higher Annual Cost to Society Per Person Source: 2002 NSDUH $0 $231 $725 $406 $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 No Alcohol or Drug Use Light Alcohol Use Only Any Infrequent Drug Use Regular AOD Use Abuse Dependence Median (50 th percentile) $948 $1,613 $1,078 $1,309 $1,528 $3,058 Mean (95% CI) This includes people who are in recovery, elderly, or do not use because of health problems Higher Costs

7 7 Age of First Use Predicts Dependence an Average of 22 years Later Source: Dennis, Babor, Roebuck & Donaldson (2002) and 1998 NHSDA 39 45 63 71 37 34 51 62 30 23 41 48 0 10 20 30 40 50 60 70 80 90 100 Tobacco, OR=1.3*, Pop.=151,442,082 Alcohol, OR=1.9*, Pop.=176,188,916 Marijuana, OR=1.5*, Pop.=71,704,012 Other, OR=1.5*, Pop.=38,997,916 % with 1+ Past Year Symptoms Under Age 15 Aged 15-17 Aged 18 or older Tobacco: Pop.=151,442,082 OR=1.49* Alcohol: Pop.=176,188,916 OR=2.74* * p<.05 Marijuana: Pop.=71,704,012 OR=2.45* Other Drugs: Pop.=38,997,916 OR=2.65*

8 8 Substance Use Careers Last for Decades Cumulative Survival Years from first use to 1+ years abstinence 302520151050 1.0.9.8.7.6.5.4.3.2.1 0.0 Median of 27 years from first use to 1+ years abstinence Source: Dennis et al., 2005

9 9 Substance Use Careers are Longer the Younger the Age of First Use Cumulative Survival Years from first use to 1+ years abstinence under 15* 21+ 15-20* Age of 1 st Use Groups * p<.05 (different from 21+) 302520151050 1.0.9.8.7.6.5.4.3.2.1 0.0 Source: Dennis et al., 2005

10 10 Substance Use Careers are Shorter the Sooner People Get to Treatment Cumulative Survival 20+ 0-9* 10-19* Year to 1 st Tx Groups 302520151050 1.0.9.8.7.6.5.4.3.2.1 0.0 * p<.05 (different from 20+) Source: Dennis et al., 2005 Years from first use to 1+ years abstinence

11 11 Treatment Careers Last for Years Cumulative Survival Years from first Tx to 1+ years abstinence 2520151050 1.0.9.8.7.6.5.4.3.2.1 0.0 Median of 3 to 4 episodes of treatment over 9 years Source: Dennis et al., 2005

12 12 Source: OAS (2004). Results from the 2003 National Survey on Drug Use and Health: National Findings. Rockville, MD: SAMHSA. http://oas.samhsa.gov/nhsda/2k3nsduh/2k3ResultsW.pdf The Growing Incidence of Adolescent Marijuana Use: 1965-2002 Adult Initiation Relatively Stable Adolescent Initiation Rising

13 13 Importance of Perceived Risk Source: Office of Applied Studies. (2000). 1998 NHSDA Marijuana Use Risk & Availability

14 14 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.

15 15 Source: Dennis and McGeary (1999) and 1997 NHSDA Substance Use in the Community

16 16 Consequences of Substance Use Source: Dennis, Godley and Titus (1999) and 1997 NHSDA

17 17 Need for Treatment (% of 24,753,586 Adolescents in the U.S. Household Population) Source: NSDUH and TEDS (see state level estimates in appendix) 8.9% 0.7% 0.6% 5.7% 8.1% 11.5% 10.7% 14.9% 17.8% 0%5%10%15%20%25% Tobacco Alcohol Alcohol Binge Any Drug Use Marijuana Use Any Non-Marijuana Drug Use Past Year AOD Dependence or Abuse Any Treatment (From NHSDA) Public Treatment (From TEDS)  --------Past Month Use------  Less than 1 in 10 getting treatment 88% of adolescents are treated in the public system

18 18 Adolescent AOD Dependence/Abuse Prevalence 6.0 to 8.4% 8.5 to 9.0% 9.1 to 9.9% 10.0 to 14.6% U.S.Avg.=8.9% SAC Grantee Source: Wright, D., & Sathe, N. (2005). State Estimates of Substance Use from the 2002–2003 National Surveys on Drug Use and Health (DHHS Publication No. SMA 05-3989, NSDUH Series H-26). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies (retrieved from http://oas.samhsa.gov/2k3State/2k3SAE.pdf ) and Kilpatrick et al, 2000. Up 27% from 7% in 1995

19 19 Unmet Treatment Need Adolescent (% of AOD Dependence/Abuse without any private/public treatment) Prevalence 82.4 to 90.1% 90.2 to 92.3% 92.4 to 94.2% 94.3 to 98.0% U.S.Avg.=92.2% SAC Grantee Source: Wright, D., & Sathe, N. (2005). State Estimates of Substance Use from the 2002–2003 National Surveys on Drug Use and Health (DHHS Publication No. SMA 05-3989, NSDUH Series H-26). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies (retrieved from http://oas.samhsa.gov/2k3State/2k3SAE.pdf ) 9 in 10 Untreated

20 20 Summary Points on Epidemiological Course Consequences go up as severity increases from use to multiple substance use, abuse, and dependence. Substance use disorders typically on-set during adolescence and last for decades. The earlier the age of onset, the longer the course of substance use The earlier treatment is received, the shorter the course of substance use Marijuana has become the leading substance problem Less than 1 in 10 adolescents with substance abuse or dependence problems receive treatment Over 88% are treated in the public system

21 21 Part 2 The Treatment System: Summarizing major trends in the adolescent treatment system and the variability by state

22 22 Adolescent Treatment Admissions have increased by 61% over the past decade Source: Office of Applied Studies 1992- 2002 Treatment Episode Data Set (TEDS) http://www.samhsa.gov/oas/dasis.htm 61% increase from 95,271 in 1993 to 153,251 in 2003

23 23 Change in Public Sector Admissions (%=(2003-1993)/1993) Change Not available -96 to -7% -8 to +33% +34 to +116% +117 to +337% U.S.Avg.=+61% SAC Grantee Source: Wright, D., & Sathe, N. (2005). State Estimates of Substance Use from the 2002–2003 National Surveys on Drug Use and Health (DHHS Publication No. SMA 05-3989, NSDUH Series H-26). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies (retrieved from http://oas.samhsa.gov/2k3State/2k3SAE.pdf ) Both Cause & Consequence

24 24 Change in Focal Substances* Source: Treatment Episode Data Set (TEDS) 1993-2003. Marijuana and Alcohol Most Common Methamphetamines & Opiates Rare but Growing Fast Most other drugs admissions grew slower than expected 61% growth 253% 310% 46% 138% -66% 36% -56% 44% 19% 111% 0 25,000 50,000 75,000 100,000 125,000 150,000 Alcohol Marijuana/Hash Cocaine/Crack Heroin/Opiates Hallucinogens Methamphetamines Other Amphetamines Stimulants Inhalants Other\e -200% -100% 0% 100% 200% 300% 400% 1993 2003 Change *TEDS Primary, Secondary or Tertiary problem

25 25 0% 20% 40% 60% 80% 100% Alcohol Marijuana/ Hash Cocaine/ Crack Heroin/Opiates Hallucinogens Meth- amphetamines Other Amphetamines Stimulants Inhalants Other\e 0% 20% 40% 60% 80% 100% Prevalence of Focal Problems Vary by State Source: Treatment Episode Data Set (TEDS) 1993-2003. Methamphetamine, Heroin/Opiate, and Cocaine problems common in about 25% of states – but under 10% in most states Methamphetamine 20% or higher in AZ, CA,ID,MN,NV,WA Cocaine 20% or higher in DE & TX Opiates 20% or higher in MA & NM Other Amphetamines 20% or higher in OR

26 26 Change in Referral Sources Source: Treatment Episode Data Set (TEDS) 1993-2003. JJ referrals have doubled, are 53% of 2003 admissions and driving growth 61% growth Other sources of Referral have grown, but less than expected

27 27 Change in Level of Care Source: Treatment Episode Data Set (TEDS) 1993-2003. 61% growth 19% 30% 66% 56% 208% 0 25,000 50,000 75,000 100,000 125,000 150,000 OutpatientIntensive Outpatient DetoxShort-term Residential Long-term Residential -200% -100% 0% 100% 200% 300% 400% 1993 2003 Change 82% of Adolescents are treated in Outpatient Settings IOP has had the fastest growth Residential has grown, but slower than expected

28 28 Severity Goes up with Level of Care Source: Treatment Episode Data Set (TEDS) 1993-2003. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Weekly use at intake First used under age 15 Dependence Prior Treatment Case Mix Index (Avg) OutpatientIntensive OutpatientDetoxification Long-term ResidentialShort-term Residential STR: Higher on Dependence Baseline Severity Goes up with Level of Care Detox: Higher on Use Detox: Higher on Use, but lower on prior tx

29 29 Other Characteristics 70% 58% 19% 17% 6% 83% 63% 57% 16% 22% 2% 1% 0%10%20%30%40%50%60%70%80%90% Male Caucasian African American Hispanic Other 15 to 17 years old 9 to 11 yrs education Student Employed Psychological Problems Pregnant at Admission Homeless/Runaway Source: Treatment Episode Data Set (TEDS) 1993-2003. These numbers are artificially low because of how they are measured System dominated by male, white, 15 to 17 year olds

30 30 Most Lack of Standardized Assessment for… Substance use disorders (e.g., abuse, dependence, withdrawal), readiness for change, relapse potential and recovery environment Common mental health disorders (e.g., conduct, attention deficit-hyperactivity, depression, anxiety, trauma, self-mutilation and suicidality) Crime and violence (e.g., inter-personal violence, drug related crime, property crime, violent crime) HIV risk behaviors (needle use, sexual risk, victimization) Child maltreatment (physical, sexual, emotional)

31 31 Median Length of Stay is only 50 days Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf. 0306090 Outpatient (37,048 discharges) IOP (10,292 discharges) Detox (3,185 discharges) STR (5,152 discharges) LTR (5,476 discharges) Total (61,153 discharges) Level of Care Median Length of Stay 50 days 49 days 46 days 59 days 21 days 3 days Less than 25% stay the 90 days or longer time recommended by NIDA Researchers

32 32 53% Have Unfavorable Discharges Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf. Despite being widely recommended, only 10% step down after intensive treatment

33 33 Summary of Problems in the Treatment System The public systems is changing size, referral source, and focus – often in different directions by state Major problems are not reliably assessed (if at all) Less than 50% stay 50 days (~7 weeks) Less the 25% stay the 3 months recommended by NIDA researchers Less than half have positive discharges After intensive treatment, less than 10% step down to outpatient care While JJ involvement is common, little is known about the rate of initiation after detention

34 34 Part 3 Evidence Based Practice: Highlighting what it takes to move the field towards evidenced based practice related to assessment, treatment, program evaluation and planning

35 35 The field is increasingly facing demands from payers, policymakers, and the public at large for “evidence-based practices (EBP)” which can reliably produce practical and cost-effective interventions, therapies and medications that will – reduce risks for initiating drug use among those not yet using, – reduce substance use and its negative consequences among those who are abusing or dependent, and – reduce the likelihood of relapse for those who are recovering NIDA Blue Ribbon Panel on Health Services Research (see www.nida.nih.gov )www.nida.nih.gov Context

36 36 Accumulating evidence indicates that most of the theories and approaches that are used within the community of practitioners are unsupported by empirical evidence of effects Various lists of 70 or so “proven” empirically supported therapies (ESTs) have proven to be relatively infeasible because they have rarely been compared with each other and generally have not been tested with the clinically diverse samples found in community based settings Need for a new method of integrating scientific evidence and the realities of practice is called for. Source: Beutler, 2000 General Behavioral Health Practice

37 37 People with multiple substance use and multiple co- occurring problems are the norm of severity in practice, but are often excluded from research Individualization of treatment content/duration is the norm in practice, but research based protocols typically involves fixed components/length that are not as appropriate for heterogeneous problems No treatment is not considered a ethical or significant option, practitioner’s are more interested in identifying which of several treatments to use for a given type of patient – but few such studies have been done When research practices have been identified, they are often not adopted because practitioner’s often lack the appropriate materials, training and resources to know when or how to implement them Problems and Barriers in SA Tx

38 38 Randomized Clinical Trials (RCT) are to Evidence Based Practice (EBP) like Self-reports are to Diagnosis They are only as good as the questions asked (and then only if done in a reliable/valid way) They are an efficient and logical place to start But they can be limited or biased and need to be combined with other information Just because the person does not know something (or the RCT has not be done), does not mean it is not so Synthesizing them with other information usually makes them better

39 39 So what does it mean to move the field towards Evidence Based Practice (EBP)? Introducing reliable and valid assessment that can be used – At the individual level to immediately guide clinical judgments about diagnosis/severity, placement, treatment planning, and the response to treatment – At the program level to drive program evaluation, needs assessment, and long term program planning Introducing explicit intervention protocols that are – Targeted at specific problems/subgroups and outcomes – Having explicit quality assurance procedures to cause adherence at the individual level and implementation at the program level Having the ability to evaluate performance and outcomes – For the same program over time, – Relative to other interventions

40 40 Reoccurring Themes in the Examples… Severity and specificity of problem subgroup Manualized and replicable assessment and treatment protocols Relative strength of intervention for a specific problem Adherence and implementation of intervention Evaluation of outcomes targeted by the intervention (a.k.a., logic modeling)

41 41 The Current Renaissance of Adolescent Treatment Research Feature1930-19971997-2005 Tx Studies*16Over 200 Random/Quasi944 Tx Manuals*030+ QA/AdherenceRareCommon Std Assessment*RareCommon Participation RatesUnder 50%Over 80% Follow-up Rates40-50%85-95% MethodsDescriptive/SimpleMore Advanced EconomicSome CostCost, CEA, BCA * Published and publicly available

42 42 Adolescent Treatment Research Currently Being Published 1994-2000 NIDA’s Drug Abuse Treatment Outcome Study of Adol. (DATOS-A) 1995-1997 Drug Abuse Treatment Outcome Study (DOMS) 1997-2000 CSAT’s Cannabis Youth Treatment (CYT) experiments 1998-2003 NIAAA/CSAT’s 15 individual research grants 1998-2003 CSAT’s 10 Adolescent Treatment Models (ATM) 2000-2003 CSAT’s Persistent Effects of Treatment Study (PETS-A) 2002-2007 CSAT’s 12 Strengthening Communities for Youth (SCY) 2002-2007 RWJF’s 10 Reclaiming Futures (RF) diversion projects 2002-2007 CSAT’s 12+ Targeted Capacity Expansion TCE/HIV 2003-2009 NIDA’s 14 individual research grants and CTN studies 2003-2006 CSAT’s 17 Adolescent Residential Treatment (ART) 2003-2008 NIDA’s Criminal Justice Drug Abuse Treatment Study (CJ-DATS) 2003-2007 CSAT’s 38 Effective Adolescent Treatment (EAT) 2004-2007 NIAAA/CSAT’s study of diffusion of innovation 2004-2009 CSAT 22 Young Offender Re-entry Programs (YORP) 2005-2008 CSAT 20 Juvenile Drug Court (JDC) 2005-2008 CSAT 16 State Adolescent Coordinator (SAC) grants Full ( ) or Partial ( ) use of the Global Appraisal of Individual Needs (GAIN)

43 43 Number of GAIN Sites Adolescent and Adult Treatment Program GAIN Clinical Collaborators 30 to 60 10 to 29 2 to 9 1 One or more state or county wide systems uses the GAIN One or more state or county wide systems considering using the GAIN 07/05

44 44 Progressive Assessment Approach GAIN Short Screener (2 pages, 5 min) for use in a general population or as fast/simple measure severity – of substance use disorders is needed. Screening for Targeted Referral – Assessment of who needs crisis or brief intervention (e.g., by SAP, doctor) vs. more detailed assessment and specialized treatment/referral – Decision rules about where to send may be more complex (e.g., substance abuse, mental health, both) Comprehensive Biopsychosocial – Used to identify common problems and how they are interrelated – Requires more skill in administration and even more in interpretation Specialized Assessment – The bio-psycho-social may identify areas where additional assessment by a specialist (e.g., psychiatrist, school counselor) may be needed to rule out a diagnosis or develop a treatment plan or individual education plan Program Level Assessment – For program management, evaluation, and planning

45 45 Common Hierarchical Structure of the GAIN’s Psychopathology Scales Substance Issues Index (SII) Substance Abuse Scale (SAS) Substance Dependence Scale (SDS) Substance Problem Scale (SPS) Somatic Symptom Index (SSI) Depression Symptom Scale (DSS) Homicidal/Suicidal Thought Index (HSTI) Anxiety/Fear Symptom Scale (AFSS) Traumatic Distress Scale (TDS) Internal Mental Distress Scale (IMDS) Inattentiveness Disorder Scale (IDS) Hyperactivity-Impulsivity Scale (HIS) Conduct Disorder Scale (CDS) Behavior Complexity Scale (BCS) General Conflict Tactic Scale (GCTS) Property Crime Scale (PCS) Interpersonal Crime Scale (ICS) Drug Crime Scale (DCS) Crime/Violence Scale (CVS) General Individual Severity Scale (GISS) Confirmatory factor analysis demonstrates that this is reliable overall and stable across adults and adolescents, outpatient & residential (confirmatory fit index =.97; Root Mean Square Error=.04)

46 46 GAIN Short Screen (GAIN-SS) Administration Time: 4-5 minute Training Requirements: Minimal Mode: Self or staff administered Purpose: Designed for use in general populations or where there is less control to identify who has a disorder warranting further assessment or behavioral intervention, measuring change in the same, and comparing programs Scales: The total scale (20-symptoms) and its 4 subscales (5- symptoms each) for internal disorders (somatic, depression, suicide, anxiety, trauma, behavioral disorders (ADHD, CD), substance use disorders (abuse, dependence), and crime/violence (interpersonal violence, property crime, drug related crime) can be used to generate symptom counts for the past month to measure change, past year to identify current disorders and lifetime to serve as covariates/validity checks. Reports: There are currently no reports.

47 47 GAIN Short Screen (GAIN-SS) Total Disorder Screener (TDScr) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 01234567891011121314151617181920 Prevalence (% 1+ disorder) Sensitivity (% w disorder above) Specificity (% w/o disorder below) (n=6194 adolescents) Low Mod. High 99% prevalence, 91% sensitivity, & 89% specificity at 3 or more symptoms Using a higher cut point increases prevalence and specificity, but decreases sensitivity Total score has alpha of.85 and is correlated.94 with full GAIN version Source: Dennis et al 2005 GSS manual

48 48 GSS Performance by Subscale and Disorders Prevalence Sensitivity Specificity Screener/Disorder 1+ 3+ 1+ 3+ 1+ 3+ Internal Disorder Screener (0-5) Any Internal Disorder 81% 99% 94% 55% 71% 99% Major Depression 56% 87% 98% 72% 54% 94% Generalized Anxiety 32% 56% 100% 83% 44% 83% SuicideIdeation 24% 43% 100% 84% 41% 79% Mod/High Traumatic Stress 60% 82% 94% 60% 55% 90% External Disorder Screener (0-5) Any External Disorder 88% 97% 98% 67% 75% 96% AD, HD or Both 65% 82% 99% 78% 51% 85% Conduct Disorder 78% 91% 98% 70% 62% 90% Substance Use Disorder Screener (0-5) Any Substance Disorder 96% 100% 96% 68% 73% 100% Dependence 65% 87% 100% 91% 30% 82% Abuse 30% 13% 89% 25% 14% 28% Crime Violence Screener (0-5) Any Crime/Violence 88% 99% 94% 49% 76% 99% High Physical Conflict 31% 46% 100% 70% 38% 77% Mod/High General Crime 85% 100% 94% 51% 71% 100% Total Disorder Screener (0-5) Any Disorder 97% 99% 91% 47% 89% Any Internal Disorder 58% 63% 100% 98% 8% 28% Any External Disorder 68% 75% 100% 99% 10% 37% Any Substance Disorder 89% 92% 99% 92% 20% 51% Any Crime/Violence 68% 73% 100% 96% 10% 32% Low (0), Moderate (1-2), and High (3+) cut points can be used to identify the need for specific types of interventions Moderate can be targeted where resources allow or where a more assertive approach is desired Mod/Hi can be used to evaluate program delivery/referral

49 49 GAIN Quick (GAIN-Q) Administration Time: 20-30 minute Training Requirements: ½ day Mode: Generally Staff Administered on Computer (can be done on paper or self administered) Purpose: Designed for use in targeted populations to support brief intervention or referral for further assessment or behavioral intervention Scales: The GQ has total scale (99-symptoms) and 15 subscales (including more detailed versions of the GSS scales and subscales plus scales for service utilization, sources of psychosocial stress, and health problems). All scales focus on the past year only and it is primarily used to support motivational interviewing or for a one time assessment (though there is a shorter follow-up version). Reports: Summary narrative report and a graphic individual profile to support clinical decision making.

50 50 The GAIN-Quick can Predict Level of Care Source: Titus et al, 2003; ATM data -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 Depression Symptom Index Suicide Risk Index Anxiety Symptom Index Internal Behavior Index Attention-Hyperactivity Disorder Index Conduct Disorder- Aggression Index General Crime Index External Behavior Index Substance Use and Abuse Substance Dependence Index Substance Problem Index TC (n=288)STR (n=604)OP/IOP (n=513) Good reliability (alpha over.9 on main scales,.7 on subscales) and correlated.9 or higher with full GAIN scale Z score from mean

51 51 GAIN Initial (GAIN-I) Administration Time: 90 (core) to 120 (full) minute Training Requirements: 3 days + review/feedback on 2 to 6 tapes (or direct observations) over 1 to 2 months; formal certification program for administration and trainers Mode: Generally Staff Administered on Computer (can be done on paper or self administered) Purpose: Designed to provide a standardized biopsychosocial for people presenting to a substance abuse treatment using DSM-IV for diagnosis, ASAM for placement, and needing to meet common (CARF, JCAHO, insurance, CDS/TEDS, Medicaid, CSAT, NIDA) requirements for assessment, diagnosis, placement, treatment planning, accreditation, performance/outcome monitoring, economic analysis, program planning and to support referral/communications with other systems Scales: The GI has 9 sections (access to care, substance use, physical health, risk and protective behaviors, mental health, recovery environment, legal, vocational, and staff ratings) that include 103 long (alpha over.9) and short (alpha over.7) scales, summative indices, and over 2000 created variables to support clinical decision making and evaluation. It is also modularized to support customization

52 52 GAIN-I’s Main Reports GAIN Referral and Recommendation Summary (GRRS): A text-based narrative in MS Word designed to be edited and shared with specialists, clinical staff from other agencies, insurers and lay people. Individual Clinical Profile (ICP): A more detailed report in MS Access designed to help triage problems and help the clinician go back to the GAIN for more details if necessary (generally not edited or shared). Personal Feedback Reports (PFR): A text based summary to support the motivational interviewing or MET based on the GAIN-I (or GAIN-Q). Validity Reports: A list of potential problems and areas for clarification and. Other: Custom reports to word, excel or transferring data from/to other data systems.

53 53 Other Measures Collateral versions of all three measures Follow-up versions of all three measures Spanish Translation of all three measures Native American Module CSAT, State, Organization, Program, and Project Specific (aka CORE) versions Ability to customize by site within prescribed parameters Over 4 dozen scientist using the data to develop additional clinical guidance on diagnosis, placement, treatment planning, treatment effectiveness and economic analysis More information is available at www.chestnut.org/li/gainwww.chestnut.org/li/gain

54 54 CSAT Adolescent Treatment Cooperative Data Set Recruitment: 1998-2004 Sample: The 2004 CSAT adolescent treatment data set included data on 5,468 adolescents from 67 local evaluations (and is growing exponentially in people, sites, and number of follow-ups) Levels of Care: Adolescent EI, OP, IOP, STR, LTR, CC Instrument:Global Appraisal of Individual Needs (GAIN) Follow-up:Over 85% follow-up 3, 6, & 9 months post discharge Funding: CSAT contract 270-2003-00006 and multiple individual grants

55 55 Demographic Characteristics 74% 6% 1% 17% 45% 15% 16% 17% 76% 7% 0% 10%20%30%40%50%60%70%80%90%100% Male Am. Native Asian African Am. White Hispanic Mixed/Other Under 14 15-17 18 to 25 Source: CSAT AT Common GAIN Data set 300 or more adolescents in each subgroup

56 56 Other Characteristics 50% 39% 34% 86% 45% 0%10%20%30%40%50%60%70%80%90%100% Single Parent Homeless or Runaway Employed In School Recently in a Controlled Environment 75% Juvenile Justice Involvement Source: CSAT AT Common GAIN Data set

57 57 Weekly/Daily Substance Use Pattern 65% 20% 52% 5% 3% 8% 30% 0%10%20%30%40%50%60%70%80%90%100% Any AOD Use Alcohol Marijuana Cocaine/Crack Heroin/Opioids Other Drugs 14 or more days in Controlled Environment In our data and in TEDS, 1 in 5 did not use in the month before intake – hence the use of 90 day window and measures of pre-CE use Source: CSAT AT Common GAIN Data set

58 58 Severity of Substance Use Disorders 88% 86% 65% 58% 43% 34% 12% 11% 0% 10%20%30%40%50%60%70%80%90%100% Self reported abuse/ dependence First use under 15 Weekly or more AOD use Past Year Dependence Prior Substance Abuse Tx Past week withdrawal Past week severe withdrawal First use under 10 Source: CSAT AT Common GAIN Data set

59 59 Mixed Problem Recognition 35% 81% 92% 99% 0%10%20%30%40%50%60%70%80%90%100% Acknowledges AOD problem Believes treatment needed Self reports 1+ abuse/dependence Problem criteria Gives one or more reasons to quit Source: CSAT AT Common GAIN Data set

60 60 High Risk Recovery Environments 29% 52% 61% 17% 67% 79% 0%10%20%30%40%50%60%70%80%90%100% Regular alcohol use In home among work/ school peers among social peers Regular drug use In home among work/ school peers among social peers Source: CSAT AT Common GAIN Data set

61 61 High Rates of Other Psychiatric Problems 49% 38% 21% 28% 32% 28% 67% 59% 48% 0%10%20%30%40%50%60%70%80%90%100% Any Internal Disorder Depressive Disorder Anxiety Disorder Trauma Related Disorder Any Self Mutilation Any homicidal/ suicidal thoughts Any External Disorder Conduct Disorder Attention Deficit- Hyperactivity Disorder (ADHD) With External Disorders more prominent in Adolescents Source: CSAT AT Common GAIN Data set

62 62 Psychiatric Problems Increase with Level of Care Source: CSAT’s Cannabis Youth Treatment (CYT) and Adolescent Treatment Model (ATM) 44 21 25 21 70 47 43 78 80 65 88 56 36 35 68 44 52 0 20 40 60 80 100 Conduct Disorder ADHDMajor Depressive Disorder Generalized Anxiety Disorder Traumatic Stress Disorder Any Co- Occurring Disorder OutpatientLong Term-ResidentialShort-Term Residential Like Dependence, “Short Term” actually the most severe on psychiatric disorders

63 63 High rate of crime and violence Source: CSAT AT Common GAIN Data set 86% 72% 58% 57% 51% 0%10%20%30%40%50%60%70%80%90%100% Any violence or illegal activity Physical Violence Property Crimes Drug Related Crime Interpersonal/violent Crimes Past Year

64 64 Intensity of Juvenile Justice System Involvement Source: CSAT 2004 AT Common GAIN Data set (n= 5,468 adolescents from 67 local evaluations) 17% In detention/jail 14+ days 25% On probation or parole 14+ days w/ 1+ drug screens 17% Other probation/parole/detention 16% Other JJ status 8% Past arrest/ JJ status 17% Past year illegal activity/SA use Highest severity for Long Term Residential (followed by STR, IOP, OP)

65 65 High Rates of HIV/STI risk behaviors 81% 57% 16% 61% 51% 35% 29% 23% 4% 0%10%20%30%40%50%60%70%80%90%100% Sexual Activity Victimization Needle Use Sexual Activity Sex Under AOD Influence Multiple Sex Partners Unprotected Sex Victimization Needle Use Lifetime Past 90 Days Source: CSAT AT Common GAIN Data set

66 66 Multiple Problems* are the Norm Source: CSAT AT Common GAIN Data set None One Two Three Four Five to Twelve 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Most acknowledge 1+ problems Few present with just one problem (the focus of traditional research) In fact, over half present acknowledging 5+ major problems * (Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity)

67 67 No. of Problems* by Severity of Victimization Source: CSAT AT Common GAIN Data set (odds for High over odds for Low) * (Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Low (31%)Moderate (17%)High (51%) Five or More Four Three Two One None Those with high lifetime levels of victimization have 117 times higher odds of having 5+ major problems* GAIN General Victimization Scale Score (Row %)

68 68 Other Assessment and Treatment Resources Assessment Instruments – GAIN Coordinating Center at www.chestnut.org/li/gainwww.chestnut.org/li/gain – CSAT TIP 3 at http://www.athealth.com/practitioner/ceduc/health_tip31k.html http://www.athealth.com/practitioner/ceduc/health_tip31k.html – NIAAA Assessment Handbook at http://www.niaaa.nih.gov/publications/instable.htm http://www.niaaa.nih.gov/publications/instable.htm Treatment Programs – CSAT CYT, ATM, ACC and other treatment manuals at www.chestnut.org/li/apss/csat/protocols and on CDs provided www.chestnut.org/li/apss/csat/protocols – SAMHSA Knowledge Application Program (KAP) at http://kap.samhsa.gov/products/manuals http://kap.samhsa.gov/products/manuals – NCADI at www.health.orgwww.health.org – National Registry of Effective Prevention Programs Substance Abuse and Mental Health Services Administration (SAMHSA), Department of Health and Human Services : http://www.modelprograms.samhsa.gov http://www.modelprograms.samhsa.gov

69 69 Other Resources (continued) Implementing Evidenced based practice – Central East ATTC Evidence Based Practice Resource Page http://www.ceattc.org/nidacsat_bpr.asp?id=LGBT http://www.ceattc.org/nidacsat_bpr.asp?id=LGBT – Northwest Frontier ATTC Best Practices in Addiction Treatment: A Workshop Facilitator's Guide http://www.nattc.org/resPubs/bpat/index.html http://www.nattc.org/resPubs/bpat/index.html – Turning Knowledge into Practice: A Manual for Behavioral Health Administrators and Practitioners About Understanding and Implementing Evidence-Based Practices http://www.tacinc.org/index/viewPage.cfm?pageId=114 http://www.tacinc.org/index/viewPage.cfm?pageId=114 – Evidence-Based Practices: An Implementation Guide for Community- Based Substance Abuse Treatment Agencies http://www.uiowa.edu/~iowapic/files/EBP%20Guide%20- %20Revised%205-03.pdf http://www.uiowa.edu/~iowapic/files/EBP%20Guide%20- %20Revised%205-03.pdf – National Center for Mental Health and Juvenile Justice Evidence Based Practice resource list at http://www.ncmhjj.com/EBP/default.asphttp://www.ncmhjj.com/EBP/default.asp Society for Adolescent Substance Abuse Treatment Effectiveness (SASATE) www.chestnut.org/li/apss/sasatewww.chestnut.org/li/apss/sasate 2006 Joint Meeting on Adolescent Substance Abuse Treatment Effectiveness http://www.mayatech.com/cti/jmate/http://www.mayatech.com/cti/jmate/ – next meeting March 27-29, 2006, Baltimore, MD

70 70 What are the pitfalls of EBP? EBP generally causes some staff turnover EBP often shines a light on staff or work place problems that would otherwise be ignored EBP often impact a wide range of existing procedures and policies – requiring modification and provoking resistance EBP (and most organizational changes) will fail without good senior staff leadership EBP typically require going for more funds from grant or other funders On-going needs assessment will create demand for more change and more EBP

71 71 Summary of Evidenced Based Practice Section Achieving reliable outcomes requires reliable measurement, protocol delivery and on-going performance monitoring. The GAIN is one measure that is being widely used by CSAT grantees and others trying to address gaps in current knowledge and move the field towards evidenced based practice. Standardized and more specific assessment helps to draw out treatment planning implications of readiness for change, recovery environment, relapse potential, psychopathology, crime/violence, and HIV risks. Adolescents entering more intensive levels of care typically have higher severity. Multiple problems and child maltreatment are the norm and are closely related to each other. There is a growing number of standardized assessment tools, treatment protocols and other resources available to support evidenced based practices

72 72 Part 4 Treatment Effectiveness: Findings from four recent treatment outcome studies

73 CYT Cannabis Youth Treatment Randomized Field Trial Sponsored by: Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services Coordinating Center: Chestnut Health Systems, Bloomington, IL, and Chicago, IL University of Miami, Miami, FL University of Conn. Health Center, Farmington, CT Sites: Univ. of Conn. Health Center, Farmington, CT Operation PAR, St. Petersburg, FL Chestnut Health Systems, Madison County, IL Children’s Hosp. of Philadelphia, Phil.,PA

74 74 Context Circa 1997 Cannabis had become more potent, was associated with a wide of problems (particularly when combined with alcohol), and had become the leading substances mentioned in arrests, emergency room admissions, autopsies, and treatment admissions (doubling in in 5 years) Over 80% of adolescents with Cannabis problems were being seen in outpatient setting The median length of stay was 6 weeks, with only 25% making it 3 months There were no published manuals targeting adolescent marijuana users in outpatient treatment The purpose of CYT was to manualize five promising protocols, field test their relative effectiveness, cost, and benefit-cost and provide them to the field Source: Dennis et al, 2002

75 75 Randomly Assigns to: MET/CBT5 Motivational Enhancement Therapy/ Cognitive Behavioral Therapy (5 weeks) MET/CBT12 Motivational Enhancement Therapy/ Cognitive Behavioral Therapy (12 weeks) FSN Family Support Network Plus MET/CBT12 (12 weeks) Trial 2Trial 1 Incremental ArmAlternative Arm Two Effectiveness Experiments ACRA Adolescent Community Reinforcement Approach(12 weeks) MDFT Multidimensional Family Therapy Randomly Assigns to: MET/CBT5 Motivational Enhancement Therapy/ Cognitive Behavioral Therapy (5 weeks) (12 weeks) Source: Dennis et al, 2002

76 76 Contrast of the Treatment Structures Individual Adolescent Sessions CBT Group Sessions Individual Parent Sessions Family Sessions/Home Visits Parent Education Sessions Total Formal Sessions Type of Service MET/ CBT5 MET/ CBT12 FSNACRAMDFT 2 3 5 2 10 12 2 10 4 6 22 10 2 2 14 6 3 6 15 Case management/ Other Contacts As needed Total Expected Contacts51222+14+15+ Total Expected Hours51222+14+15+ Total Expected Weeks6-712-13 Source: Diamond et al, 2002

77 77 Actual Treatment Received by Condition Source: Dennis et al, 2004 MET/CBT12 adds 7 more sessions of group FSN adds multi family group, family home visits and more case management ACRA and MDFT both rely on individual, family and case management instead of group With ACRA using more individual therapy And MDFT using more family therapy

78 78 $1,559 $1,413 $1,984 $3,322 $1,197 $1,126 $- $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 MET/CBT5 (6.8 weeks) MET/CBT12 (13.4 weeks) FSN (14.2 weeks w/family) MET/CBT5 (6.5 weeks) ACRA (12.8 weeks) MDFT(13.2 weeks w/family) $1,776 $3,495 NTIES Est (6.7 weeks) NTIES Est.(13.1 weeks) Average Cost Per Client-Episode of Care |--------------------------------------------Economic Cost-------------------------------------------|-------- Director Estimate-----| Average Episode Cost ($US) of Treatment Source: French et al., 2002 Less than average for 6 weeks Less than average for 12 weeks Integrating family therapy was less expensive than adding it

79 79 Implementation of Evaluation Over 85% of eligible families agreed to participate Quarterly follow-up of 94 to 98% of the adolescents from 3- to 12-months (88% all five interviews) Collateral interviews were obtained at intake, 3- and 6- months on over 92-100% of the adolescents interviewed Urine test data were obtained at intake, 3, 6, 30 and 42 months 90-100% of the adolescents who were not incarcerated or interviewed by phone (85% or more of all adolescents). Long term follow-up completed on 90% at 30-months Self reported marijuana use largely in agreement with urine test at 30 months (13.8% false negative, kappa=.63) Good reliability (alphas over.85 on main scales) and correlations with collateral reports (r=.4 to.7) Source: Dennis et al, 2002, 2004

80 80 Adolescent Cannabis Users in CYT were as or More Severe Than Those in TEDS* Source: Tims et al, 2002

81 81 Demographic Characteristics Source: Tims et al, 2002

82 82 Institutional Involvement 25% 87% 47% 62% 0% 20% 40% 60% 80% 100% In schoolEmployedCurrent JJ Involvement Coming from Controlled Environment Source: Tims et al, 2002

83 83 Patterns of Substance Use 9% 17% 71% 73% 0% 20% 40% 60% 80% 100% Weekly Tobacco Use Weekly Cannabis Use Weekly Alcohol Use Significant Time in Controlled Environment Source: Tims et al, 2002

84 84 Multiple Problems were the NORM Self-Reported in Past Year Source: Dennis et al, 2004

85 85 Substance Use Severity was Related to Other Problems * p<.05 Source: Tims et al 2002 71% 57% 25% 42% 30% 37% 22% 5% 13% 22% 0% 20% 40% 60% 80% 100% Health Problem Distress* Acute Mental Distress* Acute Traumatic Distress* Attention Deficit Hyperactivity Disorder* Conduct Disorder* Past Year Dependence (n=278)Other (n=322)

86 86 CYT Increased Days Abstinent and Percent in Recovery* Source: Dennis et al., 2004 0 10 20 30 40 50 60 70 80 90 Intake36912 Days Abstinent Per Quarter 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% % in Recovery at the End of the Quarter Days Abstinent Percent in Recovery *no use, abuse or dependence problems in the past month while in living in the community

87 87 Similarity of Clinical Outcomes by Conditions Source: Dennis et al., 2004 200 220 240 260 280 300 Total days abstinent. over 12 months 0% 10% 20% 30% 40% 50% Percent in Recovery. at Month 12 Total Days Abstinent* 269256260251265257 Percent in Recovery** 0.280.170.220.230.340.19 MET/ CBT5 (n=102) MET/ CBT12 FSN (n=102) MET/ CBT5 (n=99) ACRA (n=100) MDFT (n=99) Trial 1 Trial 2 * n.s.d., effect size f=0.06 ** n.s.d., effect size f=0.12 * n.s.d., effect size f=0.06 ** n.s.d., effect size f=0.16 Not significantly different by condition. But better than the average for OP in ATM (200 days of abstinence)

88 88 Moderate to large differences in Cost-Effectiveness by Condition Source: Dennis et al., 2004 $0 $4 $8 $12 $16 $20 Cost per day of abstinence over 12 months $0 $4,000 $8,000 $12,000 $16,000 $20,000 Cost per person in recovery at month 12 CPDA* $4.91 $6.15 $15.13 $9.00 $6.62 $10.38 CPPR** $3,958 $7,377 $15,116 $6,611 $4,460 $11,775 MET/ CBT5 MET/ CBT12 FSN MET/ CBT5 ACRA MDFT * p<.05 effect size f=0.48 ** p<.05, effect size f=0.72 Trial 1 Trial 2 * p<.05 effect size f=0.22 ** p<.05, effect size f=0.78 MET/CBT5 and 12 did better than FSN ACRA did better than MET/CBT5, and both did better than MDFT

89 89 Cost Per Person in Recovery at 12 and 30 Months After Intake by CYT Condition Source: Dennis et al., 2003; forthcoming $0 $5,000 $10,000 $15,000 $20,000 $25,000 $30,000 CPPR at 30 months** $6,437 $10,405 $24,725 $27,109 $8,257 $14,222 CPPR at 12 months* $3,958 $7,377 $15,116 $6,611 $4,460 $11,775 MET/ CBT5MET/ CBT12FSNMMET/ CBT5ACRAMDFT Trial 1 (n=299)Trial 2 (n=297) Cost Per Person in Recovery (CPPR) * P<.0001, Cohen’s f= 1.42 and 1.77 at 12 months ** P<.0001, Cohen’s f= 0.76 and 0.94 at 30 months Stability of MET/CBT-5 findings mixed at 30 months MET/CBT-5, -12 and ACRA more cost effective at 12 months Integrated family therapy (MDFT) was more cost effective than adding it on top of treatment (FSN) at 30 months ACRA Effect Largely Sustained

90 90 Change in Quarterly Costs to Society (12 months minus Intake) Source: Dennis et al., 2004 $(25,000) $(20,000) $(15,000) $(10,000) $(5,000) $- $5,000 $10,000 $15,000 $20,000 $25,000 $30,000 MET/ CBT5 MET/ CBT12 FSNMET/ CBT5 ACRAMDFTAverage $(25,000) $(20,000) $(15,000) $(10,000) $(5,000) $- $5,000 $10,000 $15,000 $20,000 $25,000 $30,000 Significant Reduction in Cost to Society Overall Three sites went down significantly, one went up significantly No Significant Difference by Condition Cond x Site: 4 sig reduction, 2 sig Incr, 6 no sig dif (low power)

91 91 Cumulative Recovery Pattern at 30 months Source: Dennis et al, forthcoming 37% Sustained Problems 5% Sustained Recovery 19% Intermittent, currently in recovery 39% Intermittent, currently not in recovery The Majority of Adolescents Cycle in and out of Recovery Source: Dennis et al forthcoming

92 92 Environmental Factors are also the Major Predictors of Relapse Recovery Environment Risk Social Risk Family Conflict Family Cohesion Social Support Substance Use Substance- Related Problems Baseline.32.18 -.13.21 -.08.32.19.22.32.22.17.11.43.77.82.74.58 -.54 -.09.19 Source: Godley et al (2005) Model Fit CFI=.97 to.99 RMSEA=.04 to.06 AOD use in the home, family problems, homelessness, fighting, victimization, self help group participation, structure activities Peer AOD use, fighting, illegal activity, treatment, recovery, vocational activity The effects of adolescent treatment are mediated by the extent to which they lead to actual changes in the recovery environment or peer group

93 93 Crime/Violence and Substance Problems Interact to Predict Recidivism Low Mod. High Low Mod. High 0% 20% 40% 60% 80% 100% Source: CYT & ATM Data 12 month recidivism Crime/ Violence predicted recidivism Substance Problem Severity predicted recidivism Knowing both was the best predictor Substance Problem Scale Crime and Violence Scale

94 94 Crime/Violence and Substance Problems Interact to Predict Violent Crime or Arrest Low Mod. High Low Mod. High Source: CYT & ATM Data 12 month recidivism To violent crime or arrest Substance Problem Scale Crime and Violence Scale 0% 20% 40% 60% 80% 100% Crime/ Violence predicted violent recidivism (Intake) Substance Problem Severity did not predict violent recidivism Knowing both was the best predictor

95 95 Post Script on CYT The CYT interventions provide replicable models of brief (1.5 to 3 month) treatments that can be used to help the field maintain quality while expanding capacity. While a good start, the CYT interventions were still not an adequate dose of treatment for the majority of adolescents – including many who continued to vacillate in and out of recovery after discharge from CYT. Descriptive, outcome and economic analyses have been published All five interventions are currently being used in subsequent experiments The MET/CBT5 intervention is currently being replicated in a 38 site study and ACRA will be replicated in a multisite study slated to be funded next year. Over 40,000 copies of the CYT manuals have been distributed by NCADI and as many electronic copies have been distributed by CD or the website

96 96

97 97 Context Circa 1998-99 Few research studies of existing treatment programs and no published manuals to support replication for the few studies that were done Not clear whether research based treatment protocols were any better than what the better programs were already doing The purpose of ATM was to manualize existing programs that appeared promising, then to evaluate them using the same measures and methods as CYT (allowing quasi-experimental comparisons)

98 98 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.

99 99 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

100 100 Program Evaluation Data Level of CareClinicsAdolescents1+ FU* Outpatient/ Intensive Outpatient (OP/IOP) 856096% Long Term Residential (LTR)**439098% Short Term Residential (STR)** 459497% Total16154497% * 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

101 101 Length of Stay Varies by Level of Care Source: Adolescent Treatment Model (ATM) Data 0% 50% 100% 0 306090 120150180210240270 300330 360390 Length of Stay Percent Still in Treatment Long Term Residential (median=154 days; n=222) Short Term Residential (median=31 days; n=589) Outpatient (median= 88 days; n=554) About half of those in OP stay 90 or more days Over half the STR say more than 30 days

102 102 Adolescents more likely to transfer Source: Adolescent Treatment Model (ATM) Data Length of Stay Across Episodes of care is about 50% longer

103 103 Years of Use Source: Adolescent Treatment Model (ATM) data

104 104 Patterns of Weekly (13+/90) Use Source: Adolescent Treatment Model (ATM) data 61 71 83 56 57 72 20 29 43 4 7 14 1 4 9 0 20 40 60 80 100 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 7 21 17 Weekly Other Drug Use 29 44 41 13+ Days in Controlled Environment

105 105 Substance Use Severity Source: Adolescent Treatment Model (ATM) data

106 106 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. Residential programs start more severe, go down sharply, but then come back over time Note the sharp “hinge” in outcomes during the active phase of AOD treatment Short- Term Resid. \t,s,ts Long- Term Resid \t,ts Outpatient \t,s

107 107 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. LTR more like OP on symptoms count Short- Term Resid. \t,s,ts Long- Term Resid \t,ts Outpatient \t,s

108 108 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. Short- Term Resid. \t,s,ts Long- Term Resid \t,ts Outpatient \t,s Longer term outcomes are similar on substance use

109 109 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), 44 21 25 21 70 47 43 78 80 65 88 56 36 35 68 44 52 0 20 40 60 80 100 Conduct Disorder ADHDMajor Depressive Disorder Generalized Anxiety Disorder Traumatic Stress Disorder Any Co- Occurring Disorder OutpatientLong Term ResidentialShort Term Residential

110 110 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. Short- Term Resid. \t,s,ts Long- Term Resid \t,ts Outpatient \t,s Note the lack of a hinge; Effect is generally indirect (via reduced use) not specific

111 111 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) 0 3 6 12 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

112 112 Broad Range of Past Year Illegal Activity Source: Adolescent Treatment Model (ATM) data 74 78 82 69 71 68 86 65 85 80 81 93 95 0 10 20 30 40 50 60 70 80 90 100 OP/IOP (n=560)LTR (n=390)STR (n=594) Any illegal activityProperty crimesInterpersonal crimes Drug related crimesActs of physical violence

113 113 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. Short- Term Resid. \t,s,ts Long- Term Resid \t,ts Outpatient \t,s Residential Treatments have a specific effect Outpatient Treatments has an indirect effect

114 114 High Rates of Victimization were the Norm Source: Adolescent Treatment Model (ATM) data

115 115 Victimization and Level of Care Interact to Predict Outcomes Source: Funk, et al., 2003 0 5 10 15 20 25 30 35 40 Intake6 MonthsIntake6 Months Marijuana Use (Days of 90) OP -HighOP - Low/ModResid-HighResid - Low/Mod. CHS Outpatient CHS Residential Traumatized groups have higher severity High trauma group does not respond to OP Both groups respond to residential treatment

116 116 How do CHS OP’s high GVS outcomes compare with other OP programs on average? Source: CYT and ATM Outpatient Data Set Dennis 2005 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 IntakeMon 1-3Mon 4-6Mon 7-9Mon 10-12 Z-Score on Substance Frequency Scale (SFS) CYT Total (n=217; d=0.51) ATM Total (n=284; d=0.41) CHSOP (n=57; d=0.18) Other programs serve clients who have significantly higher severity And on average they have moderate effect sizes even with high GVS Green line is CHS OP’s High GVS adolescents; they have some initial gains but substantial relapse

117 117 Which 5 OP programs did the best with high GVS adolescents? Source: CYT and ATM Outpatient Data Set Dennis 2005 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 IntakeMon 1-3Mon 4-6Mon 7-9Mon 10-12 Z-Score on Substance Frequency Scale (SFS) 7 Challenges (n=42; d=1.21) Tucson Drug Court (n=27; d=0.65) MET/CBT5a (n=34; d=0.62) MET/CBT5b (n=40; d=0.55) FSN/MET/CBT12 (n=34; d=0.53) CHSOP (n=57; d=0.18) The two best were used with much higher severity adolescents and TDC was not manualized Next we can check to see if they are any more similar in severity

118 118 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 IntakeMon 1-3Mon 4-6Mon 7-9Mon 10-12 Z-Score on Substance Frequency Scale (SFS) MET/CBT5a (n=34; d=0.62) MET/CBT5b (n=40; d=0.55) FSN/MET/CBT12 (n=34; d=0.53) Epoch (n=72; d=0.33) TSAT (n=66; d=0.35) CHSOP (n=57; d=0.18) Which 5 OP Programs, of similar severity, did the best with high GVS adolescents? Source: CYT and ATM Outpatient Data Set Dennis 2005 Trying MET/CBT5 because it is stronger, cheaper, and easier to implement Not much improvement and they do not work quite as well Currently CHS is doing an experiment comparing its regular OP with MET/CBT5

119 119 Post script on ATM The ATM interventions represent a relatively unprecedented sharing of technology between programs and the rest of the field. By choosing to use the GAIN instrumentation to facilitate comparisons to each other and CYT, the ATM investigators started a movement…over half of the current generation of studies are being pooled to make a common data set of over 7000 adolescents entering treatment (with follow-up data 3 to 12 months latter) that is being used to support research on evidenced based practice. Site and multisite level findings from ATM have been published and more work is under way – including methodological work on to integrate experimental, quasi-experimental and non- experimental findings in a meta analytic synthesis All of the manuals are published and distributed via website and the CDs provided

120 Findings from the Assertive Continuing Care (ACC) Experiment 183 adolescents admitted to residential substance abuse treatment Treated for 30-90 days inpatient, then discharged to outpatient treatment Random assignment to usual continuing care (UCC) or “assertive continuing care” (ACC) Over 90% follow-up 3, 6, & 9 months post discharge Source: Godley et al 2002, forth coming

121 121 Time to Enter Continuing Care and Relapse after Residential Treatment (Age 12-17) Source: Godley et al., 2004 for relapse and 2000 Statewide Illinois DARTS data for CC admissions 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0102030405060708090 Days after Residential (capped at 90) Percent of Clients Cont. Care Admis. Relapse

122 122 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)

123 123 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.

124 124 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

125 125 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

126 126 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

127 127 Post script on ACC The ACC intervention improved adolescent adherence to the continuing care expectations of both residential and outpatient staff; doing so improved the rates of short term abstinence and, consequently, long term abstinence. Despite these GAINs, many adolescents in ACC (and more in UCC) did not adhere to continuing care plans. The ACC preliminary findings are published and the main findings are currently under review. Several CSAT grantees are also seeking to replicate ACC as part of the Adolescent Residential Treatment (ART) program A second ACC experiment is currently under way to evaluate whether providing contingency management will further improve outcomes The ACC manual is being distributed via the website and the CD you have been provided.

128 128 Meta Analysis of the Effectiveness of Programs for Juvenile Offenders N of Offender Sample Studies Preadjudication (prevention) 178 Probation216 Institutionalized 90 Aftercare 25 Total 509 Source: Adapted from Lipsey, 1997, 2005

129 129 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

130 130 Most programs have small effects but 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

131 131 Major Predictors of Bigger Effects 1. Chose a strong intervention protocol based on prior evidence 2. Used quality assurance to ensure protocol adherence and project implementation 3. Used proactive case supervision of individual 4. Used triage to focus on the highest severity subgroup

132 132 Impact of the numbers of Favorable features on Recidivism (509 JJ studies) Source: Adapted from Lipsey, 1997, 2005 Usual Practice has little or no effect

133 133 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

134 134 Program types with average or better effects on recidivism AVERAGE OR BETTERBETTER/BEST Preadjudication Drug/alcohol therapyInterpersonal skills training Parent training Employment/job training Tutoring Group counseling Probation Drug/alcohol therapyCognitive-behavioral therapy Family counseling Interpersonal skills training MentoringParent 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

135 135 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 Source: Adapted from Lipsey et al 2001, Waldron et al, 2001, Dennis et al, 2004 NOTE: There is generally little or no differences in mean effect size between these brand names

136 136 Implementation is Essential ( Reduction in Recidivism from.50 Control Group Rate) The effect of a well implemented weak program is as big as a strong program implemented poorly The best is to have a strong program implemented well Thus one should optimally pick the strongest intervention that one can implement well Source: Adapted from Lipsey, 1997, 2005

137 137 Some Concluding Thoughts

138 138 A Fearless Appraisal… 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 Effectiveness is related to severity, intervention strength, implementation/adherence, and how assertive we are in providing treatment As other therapies have caught up technologically, 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

139 139 Recommendations for Further Developments… We need to target the latter phases of treatment to impact the post-treatment recovery environment and/or social risk groups that are the main predictors of long term relapse We need to move beyond focusing on acute episodes of care to focus on continuing care and a recovery management paradigm We need to better understand the impact of involvement in juvenile justice system and how it can be harnessed to help More work is need on the use of schools as a location for providing primary treatment (they have entrée to the population and appear to be the venue of choice) and recovery-schools to provide support for those coming out of residential treatment

140 140 Common Strategies you can do NOW Standardize assessment and identify most common problems Pool knowledge about what staff have done in the past, whether it worked, and what the barriers were Identify system barriers (e.g., criteria to local access case management, mental health) that could be avoided if thought of in advance Identify existing materials that could help and make sure they are readily available on site Identify promising strategies for working with the adolescent, parents, or other providers Develop a 1-2 page checklist of things to do when this problem comes up Identify a more detailed protocol and trainer to address the problem, then go for a grant to support implementation

141 141 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. Beutler, L. E. (2000). David and Goliath When empirical and clinical standards of practice meet. American Psychologist, 55, 997-1007. 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, 36-40. 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, 197-213. 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. 10-12). Rockville, MD: Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment. Dennis, M. L., Scott, C. K., Funk, R. R., & Foss, M. A. (2005). The duration and correlates of addiction and treatment. Journal of Substance Abuse Treatment, 28 (2S), S49-S60.

142 142 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, 16-34.. 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. 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)421-459. 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, 36-45. 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), 129-139, 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, 21-32. 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, 35-48. 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.

143 143 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, 689-695. 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, 133-144. 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 1998. Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved, from http://www.samhsa.gov/statistics. Office of Applied Studies (OAS) (1999). Treatment Episode Data Set (TEDS) 1992-1997: National admissions to substance abuse treatment services. Rockville, MD: Author. [Available online at.] Office of Applied Studies (OAS) (2000). Treatment Episode Data Set (TEDS) 1993-1998: 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 1998. Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved, from http://www.samhsa.gov/statistics Office of Applied Studies 1992- 2002 Treatment Episode Data Set (TEDS) retrived from http://www.samhsa.gov/oas/dasis.htm Physician Leadership on National Drug Policy (PNLDP, 2002) Adolescent Substance Abuse: A Public Health Priority. Providence, RI: Brown University. Retrieved from http://www.plndp.org/Physician_Leadership/Resources/resources.html 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, 393-402. 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, 46-57. 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, 19-35. 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. White, M. K., White, W. L., & Dennis, M. L. (2004). Emerging models of effective adolescent substance abuse treatment. Counselor, 5(2), 24-28. D. Wright & N. Sathe (2005). State Estimates of Substance Use from the 2002 - 2003 National Survey on Drug Use and Health, Rockville, MD: OAS, SAMHSA (DHHS Publication No. SMA 05-3989, NSDUH Series H-26). http://oas.samhsa.gov/2k2State/PDFW/2k2SAEW.pdf


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