advances in adolescent substance abuse treatment effectiveness michael dennis, ph.d. chestnut health...

Advances in Adolescent Substance Abuse Treatment Effectiveness

Michael Dennis, Ph.D.Chestnut Health Systems, Normal, IL

Presentation on August 31-September 4, 2009 3rd Annual Georgia School or Addiction Studies, “Keys to Change: Prevention, Treatment and Recovery, Savannah, GA. This presentation reports on treatment & research funded by the Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA) under contracts 270-2003-00006 and 270-07-0191, as well as several individual CSAT, NIAAA, NIDA and private foundation 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 448 Wylie Drive, Normal, IL 61761, phone: (309) 451-7801, Fax: (309) 451-7763, e-mail: [email protected]

2

1. Examine the prevalence, course, and consequences of adolescent substance use, co-occurring disorders and the unmet need for treatment overall

2. Summarize major trends in the adolescent treatment system and Georgia

3. Highlight what it takes to move the field towards evidenced-based practice related to assessment, treatment, program evaluation and planning

4. Present the findings from several recent treatment studies on substance abuse treatment research, trauma and violence/crime

Goals of this Presentation are to

3

Part 1. Prevalence, course, and consequences of adolescent substance use, co-occurring disorders and the unmet need for treatment overall

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

Problems Vary by Age

Source: 2002 NSDUH and Dennis et al forthcoming

0

10

20

30

40

50

60

70

80

90

100

12-13

14-15

16-17

18-20

21-29

30-34

35-49

50-64

65+

No Alcohol or Drug Use

Light Alcohol Use Only

Any Infrequent Drug Use

Regular AOD Use

Abuse

Dependence

NSDUH Age Groups

Severity Category

Over 90% of use and

problems start between the ages of

12-20

It takes decades before most recover or die

People with drug dependence die an

average of 22.5 years sooner than those

without a diagnosis

6

Crime & Violence by Substance Severity

0%

10%

20%

30%

40%

50%

60%

Serious FightAt School

Fighting withGroup

Sold Drugs Attacked withintent to harm

Stole (>$50) CarriedHandgun

Dependence (3.9%) Abuse (4.2%)

Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)

Light Alc Use (12.4%) No PY AOD Use (64.3%)

Source: NSDUH 2006

Adolescents 12-17Substance use severity is related to crime and violence

7

Family, Vocational & MH by Substance Severity

Source: NSDUH 2006

0%

10%

20%

30%

40%

50%

60%

10 or MoreArguments with

Parents

Disliked School GPA = D orlower

MajorDepression

Any MHTreatment

Dependence (3.9%) Abuse (4.2%)

Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)

Light Alc Use (12.4%) No PY AOD Use (64.3%)

Adolescents 12-17..as well as family, school

and mental health problems

8

1-2 M in 3-4 5-6

6-7 7-8 8-9

9-10 10-20 20-30

1-2 M in 3-4 5-6

6-7 7-8 8-9

9-10 10-20 20-30

Brain Activity on PET Scan After Brain Activity on PET Scan After Using CocaineUsing Cocaine

Photo courtesy of Nora Volkow, Ph.D. Mapping cocaine binding sites in human and baboon brain in vivo. Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, Macgregor RIR, Hitzemann R, Logan J, Bendreim B, Gatley ST. et al. Synapse 1989;4(4):371-377.

Rapid rise in brain activity after taking

cocaine

Actually ends up lower than they

started

9

Normal

10 days of abstinence

100 days of abstinence

Source: Volkow ND, Hitzemann R, Wang C-I, Fowler IS, Wolf AP, Dewey SL. Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190, 1992; Volkow ND, Fowler JS, Wang G-J, Hitzemann R, Logan J, Schlyer D, Dewey 5, Wolf AP. Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177, 1993.

Prolonged Substance Use Injures The Brain:Prolonged Substance Use Injures The Brain:Healing Takes Time Healing Takes Time

Normal levels of brain activity in PET

scans show up in yellow to red

After 100 days of abstinence, we can

see brain activity “starting” to recover

Reduced brain activity after regular

use can be seen even after 10 days

of abstinence

10Image courtesy of Dr. GA Ricaurte, Johns Hopkins University School of Medicine

11

Photo courtesy of the NIDA Web site. From A Slide Teaching Packet: The Brain and the Actions of Cocaine, Opiates, and Marijuana.

pain

Adolescent Brain Development Occurs from the

Inside to Out and from Back to Front

12

People Entering Publicly Funded Treatment Generally Use For Decades

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence302520151050

Source: Dennis et al., 2005

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

It takes 27 years before half reach 1 or more years of abstinence or die

13

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

under 15

21+

15-20

Age of First Use*

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

60% longer

The Younger They Start, The Longer They Use

* p<.05

14

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

Years to first Treatment Admission*

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

20 or more years

0 to 9 years

10 to 19 years

57% quicker

The Sooner They Get The Treatment, The Quicker They Get To Abstinence

•p<.05

15

After Initial Treatment…

Relapse is common, particularly for those who: – Are Younger– Have already been to treatment multiple times – Have more mental health issues or pain

It takes an average of 3 to 4 treatment admissions over 9 years before half reach a year of abstinence

Yet over 2/3rds do eventually abstain

Treatment predicts who starts abstinence

Self help engagement predicts who stays abstinent

Source: Dennis et al., 2005, Scott et al 2005

16

8.9%

21.2%

7.3%

0.5% 1.0% 0.6%0%

5%

10%

15%

20%

25%

12 to 17 18 to 25 26+

Alcohol or Other Drug Abuse or Dependence Any Public or Private Treatment

Substance Use Disorders are Common,But Treatment Participation Rates Are Low

Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH

Over 88% of adolescent and young adult treatment and

over 50% of adult treatment is publicly funded

Few Get Treatment: 1 in 17 adolescents,

1 in 22 young adults, 1 in 12 adults

Much of the private funding is limited to 30 days or less and authorized day by day

or week by week

17

Key Implications

Adolescence is the peak period of risk for and actual on-set of substance use disorders

Adolescent substance use can have short and long terms costs to society

There are real and often lasting consequence of adolescent substance use on brain functioning and brain development

Earlier Intervention during adolescence and young adult hood can reduce the duration of addiction careers

Multiple episodes of treatment are the norm Less than 1 in 17 adolescents with abuse/dependence are

getting treated

18

Part 2a. Trends in the Adolescent Substance Abuse Treatment System in the United States (US)

19

Trends in Adolescent (Age 12-17) Treatment Trends in Adolescent (Age 12-17) Treatment Admissions in the U.S.: 1992-2006Admissions in the U.S.: 1992-2006

Source: Office of Applied Studies 1992- 2006 Treatment Episode Data Set (TEDS) http://www.samhsa.gov/oas/dasis.htm

95,0

17

95,2

71 109,

123

122,

910

129,

859

131,

194

139,

129

137,

596

140,

542

148,

772

160,

750

158,

752

157,

036

142,

646

136,

660

10,000

30,000

50,000

70,000

90,000

110,000

130,000

150,000

170,000

190,000

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Year of Admission

Num

ber

of A

dmis

sion

s A

ge 1

2-17

.

69% increase from95,017 in 1992

to 160,750 in 2002

15% drop off from 160,750 in 2002 to

136,660 in 2006

20

2002 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 .

0 30 60 90

Outpatient(37,048 discharges)

IOP(10,292 discharges)

Detox(3,185 discharges)

STR(5,152 discharges)

LTR(5,476 discharges)

Total(61,153 discharges)

Lev

el o

f C

are

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

21

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 .

0% 20% 40% 60% 80% 100%

Outpatient(37,048 discharges)

IOP(10,292 discharges)

Detox(3,185 discharges)

STR(5,152 discharges)

LTR(5,476 discharges)

Total(61,153 discharges)

Completed Transferred ASA/ Drop out AD/Terminated

Despite being widely recommended, only 10% step down after intensive treatment

22

Programs often LACK 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) Recovery environment and peer risk

23

No or Inconsistent Use of Placement Criteria (even with ASAM)

difficulty synthesizing multiple pieces of information inconsistencies between competing rules the lack of the full continuum of care or specific services to

refer people to having to negotiate with the participant, families and funders

over what they will do or pay for there is virtually no actual data on the expected outcomes by

level of care to inform decision making related to placement In practice, programs primarily refer people to the limited range

of services they have readily available. Knowing nothing about the person other than what door they

walked through we can correctly predict 75% (kappa=.51) of the adolescent level of care placements

24

Other Challenges in Substance Abuse Treatment Workforce and Organizations

High turnover workforce with variable education background related to diagnosis, placement and treatment planning.

Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care

Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning

Missing or misrepresented data that needs to be minimized and incorporated into interpretations

25

Summary of Problems in the US Treatment System

Less than 26% of Adolescents in US 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

Problems are often assessed in an unstandardized way that leads to under identification

Structural issues related to high turnover, complicated client needs, lack of data to inform clinical decision making and issues with missing or misrepresented data

26

Part 2b. Trends in the Adolescent Substance Abuse Treatment System in Georgia (GA)

27

Past Year Alcohol or Drug Abuse or Dependence

Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH

7.3% GA vs.9.8% National

Adolescents (12-17)

28

Georgia Population and Regions

Source: U.S. Census 2000 and OAS, 2006 – 2003, 2004, and 2005 NSDUH

• 8 million people in 57,906 square miles (141 people per square mile or ppsm)

• Ranges for over 1000 some areas to less than 15 ppsm in some rural areas

• 7 % age 12-17, 13 % age 18-25, 62 % age 26+

• 10 % speak language other than English at home

• Mix of Urban, Small Urban & Rural Systems

1

3 2

54

State Planning Regions

29

8.9%

7.3%

7.8%

7.5%

7.4%

6.9%

6.7%0.2%

0.2%

0.2%

0.2%

0.2%

0.2%

0.5%

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12%

National

Georgia

Region 1

Region 2

Region 3

Region 4

Region 5

AOD Disorder AOD TreatmentSource: OAS, 2006 from 2002, 2003, and 2004 NSDUH

Adolescent Substance Use Disorder & Treatment Participation Rates by Georgia State Planning Districts

Below National Average on

Abuse/Dependence

But also below in treatment

30

7.3%

17.9%

7.1%

0.2% 0.1% 0.7%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Age 12-17 Age 18 - 25 Age 26+

AOD Disorder AOD TreatmentSource: OAS, 2006 from 2002, 2003, and 2004 NSDUH

Substance Use Disorder & Treatment Participation Rates by Age in Georgia

1 in 179Young Adults

1 in 36Adolescents 1 in 10

Adults

31

Change in Adolescent Admissions by Level of Care in Georgia Public Treatment 1992-2005

Source: OAS, 2007 – 1992-2005 TEDS Data

709 82

9

871

890

866

701

526 64

4

1,06

5

1,60

8

1,77

9

1,95

7

1,61

5

2,55

7

-

500

1,000

1,500

2,000

2,500

3,00019

92

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

OP (268%)

IOP (511%)

Residential(95%)

Detox (69%)

386% growth since 1998

IOP and OP have grown

the most,Detox the least

Systems has had two major contractions

32

Change in Adolescent Referral Source in Georgia Public Treatment 1992-2005


-

500

1,000

1,500

2,000

2,500

3,00019

92

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Other (509%)

Other HealthProvider (42%)

School (-27%)

OtherCommunityReferral (167%)

Other AODProvider(27000%)

Self/Family(202%)

Juvenile Justice(340%)

Juvenile Justice is the largest

source of referral

33

Change in Adolescent Prior Tx Admissions in Georgia Public Treatment 1992-2005


-

500

1,000

1,500

2,000

2,500

3,00019

92

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

5 or more Tx (-63%)

4 Prior Tx (83%)

3 Prior Tx (274%)

2 Prior Tx (148%)

1 Prior Tx (216%)

No Prior Tx(315%)

1 in 5 Adolescents have been in

treatment before

34

Change in Adolescent Focal Problems in

Georgia Public Treatment 1992-2005


-

500

1,000

1,500

2,000

2,50019

92

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Marijuana (751%)

Alcohol (88%)

Cocaine (181%)

Methamphetamine(8040%)

Hallucinogens (-41%)

Stimulants(550%)

Psychotropics(1600%)

Opioids (1940%)

Inhalants (-20%)

Other (115%)

Primarily Marijuana and

Alcohol

But rapid growth in Methampethamine,

Opioids and Psychotropic's

35

Adolescent 2006 Length of Stay US vs. Georgia

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

US Georgia US Georgia US Georgia US Georgia

Residential IOP OP Total

366 DAYS OR MORE

181 TO 365 DAYS

121 TO 180 DAYS

91 TO 120 DAYS

61 TO 90 DAYS

46 TO 60 DAYS

31 TO 45 DAYS

0 TO 30 DAYS

Source: OAS 20072006 TEDS Episode Data

Median: 75 v. 115 days90+ Days: 41 vs. 52%

36

Adolescent 2006 Discharge Status US vs. Georgia

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

US Georgia US Georgia US Georgia US Georgia

Residential IOP OP Total

Other

AMA/ASA

TRANSFERRED

TREATMENTCOMPLETED

Source: OAS 20072006 TEDS Episode Data

Successful Discharge

56% vs. 44%

Transferred14% vs. 11%

37

Summary of Problems in the GA Treatment System

Less than 1 in 36 adolescents with abuse/dependence in Georgia are getting treated

The public systems is changing size, referral source, and focus

Marijuana and Alcohol are the most common drugs, but meth, opioids and pscyhotropics are growing fast

Other problems are often assessed in an unstandardized way that leads to under identification

About 48% of Adolescents in Georgia stay the 3 months recommended by NIDA researchers

About 56% have negative discharges After intensive treatment, only about 11% step down to

outpatient care

38

Part 3a. Highlight what it takes to move the field towards evidenced-based practice related to assessment, treatment, program evaluation and planning

39

So what does it mean to move the field towards Evidence Based Practice (EBP)?

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

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, performance monitoring and long term program planning

40

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

41

Impact of the numbers of Favorable features on Recidivism (509 JJ studies)

Source: Adapted from Lipsey, 1997, 2005

Average Practice

42

Cognitive Behavioral Therapy (CBT) Interventions that Typically do Better than Usual Practice in Reducing Recidivism (29% vs. 40%)

Adolescent Community Reinforcement Approach (ACRA) Aggression Replacement Training Assertive Continuing Care Brief Strategic Family Therapy (BSFT) Interpersonal Social Problem Solving Functional Family Therapy (FFT) MET/CBT combinations and Other manualized CBT Moral Reconation Therapy Multidimensional Family Therapy (MDFT) Multisystemic Therapy (MST) Reasoning & Rehabilitation Thinking for a Change

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

43

Other Protocols Targeted at Specific Issues:

Detoxification services and medication, particularly related to opioid and methamphetamine use

Tobacco cessation Adolescent psychiatric services related to depression,

anxiety, ADHD, and conduct disorder Trauma, suicide ideation, & parasuicidal behavior Need for child maltreatment interventions (not just

reporting protocols) HIV Intervention to reduce high risk pattern of sexual

behavior Anger Management Problems with family, school, work, and probation Recovery coaches, recovery schools, recovery housing and

other adolescent oriented self help groups / services

44

Impact of State Wide Screening in Washington Statewith the 2 page GAIN Short Screener

77% 86

%

73%

75%

61%67

%

83%

62%

75%

60%

57%

40% 46

%

12%

12%

47%

37%

35%

12%

11%

0%10%20%30%40%50%60%70%80%90%

100%

Substance AbuseTreatment(n=8,213)

Student AssistancePrograms(n=8,777)

Juvenile Justice(n=2,024)

Mental HealthTreatment (10,937)

Children'sAdministration

(n=239)

Either High on Mental Health High on Substance High on Both

Source: Lucenko et al (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

Hig

h (2

+)

Problems could be easily identified Comorbidity

is common

http://publications.rda.dshs.wa.gov/1392/

45

Validation of Hi Co-occurring from GAIN Short Screener to Clinical Records by Setting

37%

35%

12%

11%

56%

34%

15%

9%

47%

0%10%20%30%40%50%60%70%80%90%

100%

SubstanceAbuse

Treatment(n=8,213)

StudentAssistancePrograms(n=8,777)

Juvenile Justice(n=2,024)

Mental HealthTreatment(10,937)

Children'sAdministration

(n=239)

GAIN Short Screener Clinical Indicators

NotAvailble

Source: Lucenko et al (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

2 page screener relatively consistent with other clinical

indicators

http://publications.rda.dshs.wa.gov/1392/

46

On-site proactive urine testing can be used to reduce false negatives by more than half

Reduction in false negative reports at no

additional cost Effects grow when

protocol is repeated

47

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 wellSource: Adapted from Lipsey, 1997, 2005

48

Implications of Implementation Science

Can identify complex and simple protocols that improve outcomes

Interventions have to be reliably delivered in order to achieve reliable outcomes

Simple targeted protocols can make a big difference

Need for reliable assessment of need, implementation, and outcomes

49

Key Issues that we try to address with the Global Appraisal of Individual Needs (GAIN)

High turnover workforce with variable education background related to diagnosis, placement and treatment planning.

Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care

Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning

Missing or misrepresented data that needs to be minimized and incorporated into interpretations

50

GAIN Logic ModelH

eter

ogen

eous

Nee

ds

and

Sev

erit

y

• Multiple domains• Focus on most common problems• Participant self description of

characteristics, problems, needs, personal strengths and resources

• Behavior recency, breadth, frequency• Utilization lifetime, recency and

frequency• Dimensional measures• Interpretative cut points

• Items and cut points mapped onto DSM for diagnosis, ASAM for placement, and to multiple standards and evidence- based practices for treatment planning

• Computer generated scoring and reports• Treatment planning recommendations

and links to evidence-based practice• Basic and advanced clinical

interpretation training and certification

Com

preh

ensi

ve A

sses

smen

t

Issue Instrument Feature Protocol Feature Outcome

Hig

h T

urno

ver

Wor

kfor

cew

ith

Var

iabl

e E

duca

tion

• Standardized approach to asking questions across domains

• Questions spelled out and simple question format

• Lay wording mapped onto expert standards for given area

• Built in transition statements, prompts, and checks for inconsistent and missing information.

• Responses to frequently asked questions• Multiple training resources

• Formal training and certification protocols on administration, clinical interpretation, data management, project coordination, local, regional, and national “trainers”

• Above focuses on consistency across populations, level of care, staff and time

• On-going quality assurance and data monitoring for the reoccurrence or problems at the staff (site or item) level

• Availability of technical assistance

Impr

oved

Rel

iabi

lity

and

E

ffic

ienc

y

51

GAIN Logic Model (continued)Issue Instrument Feature Protocol Feature Outcome

Mis

sing

or

Mis

repr

esen

ted

Dat

a

• Assurances, time anchoring, definitions, transition, and question order to reduce confusion and increase valid responses

• Cognitive impairment check• Validity checks on missing, bad,

inconsistency and unlikely responses• Validity checks for atypical and overly

random symptom presentations• Validity ratings by staff

• Training on optimizing clinical rapport• Training on time anchoring• Training answering questions, resolving

vague or inconsistent responses, following assessment protocol and accurate documentation.

• Utilization and documentation of other sources of information

• Post hoc checks for on-going site, staff or item problems

Impr

oved

Val

idit

y

Lac

k of

Acc

ess

to o

r us

e of

D

ata

at th

e P

rogr

am L

evel • Data immediately available to support

clinical decision making for a case• Data can be transferred to other clinical

information system to support billing, progress reports, treatment planning and on-going monitoring

• Data can be exported and cleaned to support further analyses

• Data can be pooled with other sites to facilitate comparison and evaluation

• PC and (soon) web based software applications and support

• Formal training and certification on using data at the individual level and data management at the program level

• Data routine pooled to support comparisons across programs and secondary analysis

• Over two dozen scientists working with data to link to evidence-based practice Im

prov

ed P

rogr

am P

lann

ing

and

Out

com

es

52

Part 3b. What has CSAT found when it did this over the past decade?

5353

CSAT Adolescent Treatment Grant Programs and Sites Using the GAIN: 1998-2008

AK

AL

AR

AZ

CACO DE

FL

GA

HI

IA

IN

KS

LA

MD

ME

MI

MN

MO

MS

MT ND

NE

NH

NJ

NM

NV

NY

OH

OK

OR

PARI

SD

TN

TX

UT

VAWV

WY

ID

IL

KY

WA

WI

SC

NC

VT

MA

CT

DC

SAC\1

Grant AAFTARTATMCYT

JTDC\2

OtherEAT

OJJDP BIRT\3OJJDP RF

RCFSCYTCEYORP

\1 SAC data are not included in the CSAT 2008 Dataset\2 Includes Family Treatment Drug Courts\3 OJJDP BIRT data was not ready for the CSAT 2008 Dataset

5454

Current CSAT Data Set by Level of Care

Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,746)

LTR: Long Term Residential 11.9%,

(n=1,866)

STR: Short Term Residential 2.6%,

(n=403)

OP: Outpatient

69.2%, (n=10,904)

CC-OP: Continuing

Care – Outpatient 7.7%, (n= 1,213)

IOP: Intensive Outpatient 8.6%,

(n=1,360)

5555

Current CSAT Data Set by Treatment Type


Tx Man: Specific Manualized Treatment,

11.6%, (n=1,759)

MDFT: Multi-Dimensional

Family Therapy, 1.6%,

(n=249)

MET/CBT: Motivational Enhancement

Therapy/Cognitive-Behavioral Therapy 53.2%, (n=8,065)

Other: Non-manualized treatment, 11.4%, (n=1,722)

Other EBTx: Evidence Based Treatment, 6.7%,

(n=1,016)

7C: Seven Challenges, 1%, (n=124)

ACRA/ACC: Adolescent Community

Reinforcement Approach/ Assertive

Continuing Care, 14.6%, (n=2,214)

5656

CSAT Full GAIN Data

*Any Hispanic ethnicity separate from race group


50%

10%

73%

10%

19%

31%

42%

27%

16%

18%

28%

81%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Single Parent

Employed

In School

Ever Homeless or Runaway

Mod-High Health problems

15 to 17 years old

12 to 14 years old

Hispanic*

Mixed/Other

Caucasian

African American

Female

CSAT data dominated by male, minority,

age 15 to 17

5757

Substance Use Severity

82%

52%

32%

25%

68%

5%

26%

48%

93%0

%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Past Year Substance Diagnosis

3 or More Years of Use

Any Past Year Dependence

Any withdrawal symptoms in the past week

Severe withdrawal (11+ symptoms) in past week

Can Give 1+ Reasons to Quit*

Client believes Need ANY Treatment

Acknowledges having an AOD problem

Any prior substance abuse treatment

Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,713) *(n=8,670)

5858

Past Year Substance Severity by Level of Care

48%60%

73% 80%89%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP

IOP

CC

-OP

LT

R

STR

UseAbuseDependence


5959

Pattern of Weekly Use (13+/90 days) :

3%

2%

6%

2%

50%

27%

45%

15%

56%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Anything

Alcohol

Cannabis

Cocaine

Opioid

Other Drugs

Needle Use

Tobacco

Controlled Environment


6060

Past 90 day HIV Risk Behaviors


30%

62%

2%

63%

25%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sexually active

Multiple Sex partners

Any Unprotected Sex

Victimized Physically, Sexually, orEmotionally

Any Needle use

6161

Sexual Partners by Level of Care

27% 33% 27%42%

56%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP

IOP

CC

-OP

LT

R

STR

NoSexualPartnersOneSexualPartner

MultipleSexualPartners


6262

Co-Occurring Psychiatric Problems

51%

62%

32%

39%13%

17%

45%

13%

24%

34%

44%

67%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Any Co-occurring Psychiatric

Conduct Disorder

Attention Deficit/Hyperactivity Disorder

Major Depressive Disorder

Traumatic Stress Disorder

General Anxiety Disorder

Ever Physical, Sexual or Emotional Victimization

High severity victimization (GVS>3)

Ever Homeless or Runaway

Any homicidal/suicidal thoughts past year

Any Self Mutilation*

Prior Mental Health Treatment

Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,882) *(n=9,061)

6363

Recovery Environment - Home

27%

11%

26%

75%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Family Historyof Substance Use

Weekly AlcoholUse at Home

Weekly Drug useat Home

Weekly FamilyProblems


6464

Recovery Environment - Peers

31%

48%

27%

72%

64%

53%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Social Peers Getting Drunk Weekly+

School/Work Peers Getting DrunkWeekly+

Others at Home Getting DrunkWeekly+

Social Peers Using Drugs

School/Work Peers Using Drugs

Others at Home Using Drugs


6565

Past Year Violence & Crime

*Dealing, manufacturing, prostitution, gambling (does not include simple possession or use)


81%

69%

49%

73%

43%

85%

65%

46%

45%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Any violence or illegal activity

Physical Violence

Any Illegal Activity

Any Property Crimes

Other Drug Related Crimes*

Any Interpersonal/ Violent Crime

Lifetime Juvenile Justice Involvement

Current Juvenile Justice involvement

1+/90 days In Controlled Environment

6666

Type of Crime by Level of Care

39%49% 51%

59% 67%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP

IOP

CC

-OP

LT

R

ST

R

Drug UseonlyOtherCrime*ViolentCrime

Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,553)*Other crime includes vandalism, possession of stolen goods, forgery, and theft.

6767

Intensity of Juvenile Justice System Involvement


Other JJ/CJ status16%

Past arrest/JJ/CJ

status6%

In detention/jail 14-29 days

7%

In detention/jail 30+ days

10%

Past year illegal activity/SA use

18%

On prob/parole 14+ days w/ 1+ drug screens

25%

Other prob/parole/

detention18%

6868

Count of Major Clinical Problems at Intake

19%

34%

13%

24%

12%

44%

51%

62%

81%

16%

34%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Alcohol

Cannabis

Other drug disorder

Depression

Anxiety

Trauma

Suicide

ADHD

CD

Victimization

Violence/ illegal activity


6969

Number of Major Clinical Problems* at Intake by Gender

46% 42%56%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Tot

al

Mal

e

Fem

ale

None

One

Two

Three

Four

Five to Twelve


*Based on count of self reporting criteria to suggest Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity

7070

Number of Major Clinical Problems* at Intake by Level of Care

40%47%

58%68%

78%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP

IOP

CC

-OP

LT

R

ST

R

None

One

Two

Three

Four

Five to Twelve


*Based on count of self reporting criteria to suggest Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity

71

15%

45%

70%

0%10%20%30%40%50%60%70%80%90%

100%

Low (OR 1.0)

Mod.(OR=4.8)

High(OR=13.8)

NoneOneTwoThreeFourFive+

No. of Problems* by Severity of Victimization

Source: CSAT AT 2007 dataset subset to adolescent studies (N=15,254)

Those with high lifetime

levels of victimization

have 117 times higher odds of

having 5+ major

problems** (Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity)

Severity of Victimization

7272

Intake to Last Wave Percent Change in GPRA Outcomes by Level of Care

Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only (n=11,688)

OP IOP LTR STR

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%In

take

6 M

on

Inta

ke

6 M

on

Inta

ke

6 M

on

Inta

ke

6 M

on

VocationallyEngaged

Housed inCommunity

No Arrest

Abstinent

All improve abstinence and re-arrest,

Residential have negative impact on housing

73

Any Illegal Activity in the Next Six Months by Intake Severity on Crime/Violence and Substance Problem Scales

58%46%

36%53%

33%26%44%

27%20%

0%

20%

40%

60%

An

y I

leg

al

Ac

tiv

ity

(mo

nth

s1

-6)

High Mod Low LowMod

High

Crime/Violence Scale (Intake)

Substance Problem Scale

(Intake)

Source: CSAT 2008 V5 dataset Adolescents aged 12-17 with 3 and/or 6 month follow-up (N=9006)

Intake Crime/ Violence Severity

Predicts Recidivism

Intake Substance Problem Severity

Predicts Recidivism

Knowing both is a better predictor(high –high group is 5.5 times more

likely than low low)

While there is risk, most (42-80%) actually do not commit

additional crime

7474

NOMS Outcome: Early Treatment Outcomes

58%

72%

56%

85%

83%

71%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Initiation with 14 days

Evidenced Based Practice

Engagement for at least 6 weeks

Any Continuing Care (91-180 days)

Substance Use-Abstinent/Reduced 50% at 3Months

12 Month Cost Within Bands for Initial Typeof Treatment


7575

Performance: No Problems at Intake

Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only

37%

38%

39%

43%

98%

58%

77%

55%

37%

28%

8%

94%4%

1%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Abstinent*

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community

Family/Home Problems

Vocational Problems*

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School

* Variables measure the last 30 days. All others measure the past 90 days.

7676

Performance: Outcome Status at Last Wave

Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only

72%

75%80%

89%

79%62%

43%90%

99%

78%

75%

66%

12%

18%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Abstinent*

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community**

Family/Home Problems

Vocational Problems*

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School**

Reduced 50% orNo Problem*

No Problem*

* Variables measure the last 30 days. All others measure the past 90 days. **Represents an increase

7777

Performance: Count of Positive Outcomes(Last FU – Intake) By Level of Care


27% 33%23%

43% 45%

0%10%20%30%40%50%60%70%80%90%

100%O

P

IOP

CC

-OP

LT

R

ST

R

Five orMoreFour

Three

Two

One

None

NegativeoneLess than -1

78

Part 4. Findings from several recent treatment studies on substance abuse treatment research, trauma and violence/crime

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, ILUniversity of Miami, Miami, FLUniversity of Conn. Health Center, Farmington, CT

Sites:Univ. of Conn. Health Center, Farmington, CTOperation PAR, St. Petersburg, FLChestnut Health Systems, Madison County, ILChildren’s Hosp. of Philadelphia, Phil. ,PA

80

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

81

Randomly Assigns to:

MET/CBT5Motivational Enhancement Therapy/

Cognitive Behavioral Therapy (5 weeks)



FSN

Family Support Network

Plus MET/CBT12 (12 weeks)

Trial 2Trial 1Incremental Arm Alternative Arm

Two Effectiveness Experiments

ACRAAdolescent Community

Reinforcement Approach(12 weeks)

MDFTMultidimensional Family Therapy

Randomly Assigns to:



(12 weeks)


82

5

10

5

11

14

23

0

5

10

15

20

25

MET/CBT5

MET/CBT12

MET/CBT12 +

FSN

MET/CBT5

ACRA MDFT

Hou

rs

Day

s

CaseManagement

FamilyCounseling

Collateral only

Multi-Familygroup

Multi-ParticipantGroup

Participant only

Incremental Arm Alternative Arm

Actual Treatment Received by Condition


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

83

$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/C

BT5 (6.8

wee

ks)

MET/C

BT12 (1

3.4 w

eeks

)

FSN (14.2

wee

ks w

/family

)

MET/C

BT5 (6.5

wee

ks)

ACRA (12.8

wee

ks)

MDFT(1

3.2 w

eeks

w/fa

mily)

$1,776

$3,495

NTIES E

st (6

.7 wee

ks)

NTIES E

st.(1

3.1 w

eeks

)

Ave

rage

Cos

t P

er C

lien

t-E

pis

ode

of C

are

|--------------------------------------------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

84

CYT Increased Days Abstinent and Percent in Recovery*


0

10

20

30

40

50

60

70

80

90

Intake 3 6 9 12

Day

s A

bsti

nent

Per

Qua

rter

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

% in

Rec

over

y at

the

End

of

the

Qua

rter

Days Abstinent

Percent in Recovery

*no use, abuse or dependence problems in the past month while in living in the community

85

Similarity of Clinical Outcomes by Conditions


200

220

240

260

280

300

Tot

al d

ays

abst

inen

t.

over

12

mon

ths

0%

10%

20%

30%

40%

50%

Per

cent

in R

ecov

ery

. at

Mon

th 1

2

Total Days Abstinent* 269 256 260 251 265 257

Percent in Recovery** 0.28 0.17 0.22 0.23 0.34 0.19

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)

86

Moderate to large differences in Cost-Effectiveness by Condition


$0

$4

$8

$12

$16

$20

Cos

t per

day

of

abst

inen

ce o

ver

12 m

onth

s

$0

$4,000

$8,000

$12,000

$16,000

$20,000

Cos

t per

per

son

in r

ecov

ery

at m

onth

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/ CBT5MET/

CBT12FSN 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

87

Range of Effect Sizes (d) for Change in Days of Abstinence (intake to 12 months) by Site

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

4 CYT Sites (f=0.39)(median within site d=0.29)

36 EAT Sites (f=0.21)(median within site d=0.49)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Coh

en’s

d

Source: Dennis, Ives, & Muck, 2008

EAT Programs did Better than CYT on

average

75% above CYT median

6 programs completely above CYT

8888

Change in Abstinence (6 mo-Intake) After Adolescent CRA by Program

36%

24%

4%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

CYT AAFT Other

% P

oint

Cha

nge

in A

bsti

nenc

e

Source: CSAT 2008 SA Dataset subset to 6 Month Follow up (n=1,961)

(high monitoring) (mod. monitoring) (training only)

Effects associated with intensity of quality

assurance and monitoring

89Source: Morral and Stevens 2003al 2006

90

Program Evaluation Data

Level of Care Clinics Adolescents 1+ FU*

Outpatient/ Intensive Outpatient (OP/IOP)

8 560 96%

Long Term Residential (LTR)**

4 390 98%

Short Term Residential (STR)**

4 594 97%

Total 16 1544 97%

* 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

91

Adolescents more likely to transfer

Source: Adolescent Treatment Model (ATM) Data

0%

50%

100%0 30 60 90 120

150

180

210

240

270

300

330

360

390

Length of Stay

Perc

ent S

till i

n T

reat

men

t

Index Episode of Care (median=52 days; n=1380)

System Episode of Care (median=73 days; n=1380)

Length of Stay Across Episodes of care is about 50% longer

92

Change in Substance Frequency Scale 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.

40

50

60

Intake 3 6 9 12

Months from Intake

STR\t,s,ts

LTR\t,ts

OP\t,s,ts

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

93

Change in Substance Problem Scaleby Level of Care\a


Change in Substance Problem Index Past Month T-Score (TSPIM) by Level of Care\a

40

50

60

Intake 3 6 9 12

Months from Intake

STR\t,s,ts

LTR\t,s,ts

OP\t,s,ts

LTR more like OP on symptoms

count



Outpatient\t,s

94

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.

0%

20%

40%

60%

80%

100%

Intake 3 6 9 12

Months from Intake

STR\t,s,ts

LTR\t,ts

OP\t,s



Outpatient\t,s

Longer term outcomes are

similar on substance use

95

Change in Emotional Problem Scaleby Level of Care\a


40

50

60

Intake 3 6 9 12

Months from Intake

STR\t,s,ts

LTR\t,s,ts

OP\t,s



Outpatient\t,s

Note the lack of a hinge; Effect is generally indirect (via

reduced use) not specific

96

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

Nu

mb

er o

f P

ast

Mon

th S

ub

stan

ce P

rob

lem

s

2+ Co-occurring 1 Co-occurring No Co-occurring

Multi-morbid Adolescents start the highest, change the most, and relapse the most

97

Change in Illegal Activity Scaleby Level of Care\a


40

50

60

Intake 3 6 9 12

Months from Intake

STR\t,s,ts

LTR\t,ts

OP\s



Outpatient\t,s

Residential Treatments have a specific effect

Outpatient Treatments has an indirect effect

98

CSAT Adolescent Treatment GAIN Data from 203 level of care x site combinations

Outpatient

General Group Home

Short-Term Residential

Outpatient Continuing CareIntensive Outpatient

Long-term ResidentialModerate-Term Residential

Early InterventionOtherCorrections

Levels of Care

Source: Dennis, Funk & Hanes-Stevens, 2008

99

Ratings of Problem Severity (x-axis) by Treatment Utilization (y-axis) by Population Size (circle size)

12%

20%

14%

8%

14%

12%

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

-0.20 0.00 0.20 0.40 0.60 0.80 1.00

Average Current Problem Severity

Ave

rage

Cur

rent

Tre

atm

ent U

tili

zati

on

.

A Low-Low

B Low- Mod

C Mod-Mod

DHi-Low

EHi-Mod

F. Hi-Hi (CC)

G. Hi-Mod(Env Sx/ PH Tx)

9%

H. Hi-Hi(Intx Sx; PH/MH Tx) 12%

100

Variance Explained in NOMS Outcomes

\1 Past month \2 Past 90 days *All statistically Significant

26%

24%

11%

25%

15%

33%

26%

18%

14%

8%

24%

0% 5% 10% 15% 20% 25% 30% 35%

No AOD Use \1

No AOD related Prob.\1

No Health Problems \2

No Mental Health Prob.\2

No Illegal Activity \2

No JJ System Involve. \1

Living in Community \1

No Family Prob. \2

Vocationally Engaged \1

Social Support \2

Count of above

Percent of Variance Explained

101

Predicted Count of Positive Outcomes by Level of Care: Cluster A Low - Low (n=1,025)

2

3

4

5

6

7

8

9

10

Outpatient Higher LOC

2

3

4

5

6

7

8

9

10

Predicted Count of Positive Outcomes by Level of Care: Cluster A Low - Low (n=1,025)

102

Best Level of Care*: Cluster A Low - Low (n=1,025)Best Level of Care*:

Cluster A Low - Low (n=1,025)

99.6%

0.4%0%

20%

40%

60%

80%

100%

120%

Outpatient Higher LOC

% B

est P

redi

cted

Out

com

es

* Based on Maximum Predicted Count of Positive Outcomes

103

Best Level of Care*: Cluster C Mod-Mod (n=1209)

30.2%

7.6%

23.6%

38.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Outpatient IOP OPCC Residential

% B

est P

redi

cted

Out

com

es


104

Best Level of Care*: Cluster F Hi-Hi (CC) (n=968)

81.5%

8.6%

0.0%

9.9%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Outpatient IOP OPCC Residential

% B

est P

redi

cted

Out

com

es


105

Best Level of Care*: Cluster G Hi-Mod (Env/PH) (n=749)Best Level of Care*:

Cluster G Hi-Mod (Env/PH) (n=749)

94.1%

5.9%0.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Outpatient IOP/OPCC Residential


106

The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents

In the Community

Using (75% stable)

In Treatment (48% stable)

In Recovery (62% stable)

Incarcerated(46% stable)

5%

12%

7%

20%

24%

10%

26%

7 %

19%7%

27%

3%

Source: 2006 CSAT AT data set

Avg of 39% change status each quarter

P not the same in both directions

Treatment is the most likely path

to recoveryMore likely than adults to stay 90 days in treatment (OR=1.7)

More likely than adults to be diverted

to treatment (OR=4.0)

107

In the Community

Using (75% stable)

12%

27%

Probability of Going from Use to Early “Recovery” (+ good)-Age (0.8) + Female (1.7),- Frequency Of Use (0.23) + Non-White (1.6)

+ Self efficacy to resist relapse (1.4) + Substance Abuse Treatment Index (1.96)

* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home•** Proportion of social peers during transition period in school/work, treatment, recovery, and inverse of those using alcohol, drugs, fighting, or involved in illegal activity.

In Recovery(62% stable)

Probability of from Recovery to “Using” (+ good)- Freq. Of Use (0.0002) + Initial Weeks in Treatment (1.03)- Illegal Activity (0.70) + Treatment Received During Quarter (2.00)- Age (0.81) + Recovery Environment (r)* (1.45)

+ Positive Social Peers (r) (1.43)


108

In the Community

Using (75% stable)

In Treatment

(48 v 35% stable)

7%


Probability of Going from Use to “Treatment” (+ good)-Age (0.7) + Times urine Tested (1.7), + Treatment Motivation (1.6)

+ Weeks in a Controlled Environment (1.4)


109

In the Community

Using (75% stable)

In Treatment

(48 v 35% stable)



26% 19%


Probability of Going to Using vs. Early “Recovery” (+ good)-- Baseline Substance Use Severity (0.74) + Baseline Total Symptom Count (1.46)-- Past Month Substance Problems (0.48) + Times Urine Screened (1.56)-- Substance Frequency (0.48) + Recovery Environment (r)* (1.47)

+ Positive Social Peers (r)** (1.69)

* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home

** Proportion of social peers during transition period in school/work, treatment, recovery, and inverse of those using alcohol, drugs, fighting, or involved in illegal activity.

110

In the Community

Using (75% stable)



* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home

20% 10%

Incarcerated(46% stable)

Probability of Going to Using vs. Early “Recovery” (+ good)+ Recovery Environment (r)* (3.33)


111

Recovery* by Level of Care

* Recovery defined as no past month use, abuse, or dependence symptoms while living in the community. Percentages in parentheses are the treatment outcome (intake to 12 month change) and the stability of the outcomes (3months to 12 month change) Source: CSAT Adolescent Treatment Outcome Data Set (n-9,276)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Pre-Intake Mon 1-3 Mon 4-6 Mon 7-9 Mon 10-12

Per

cent

in P

ast

Mon

th R

ecov

ery* Outpatient (+79%, -1%)

Residential(+143%, +17%)

Post Corr/Res (+220%, +18%)

OP & Resid

Similar

CC better

112

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

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, 2007

114

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%

0 10 20 30 40 50 60 70 80 90

Days after Residential (capped at 90)

Per

cen

t of

Clie

nts

Cont.CareAdmis.

Relapse

115

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)

116

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.

117

ACC Improved Adherence


0% 10%

20%

30%

40%

50%

60%

70%

80%

Weekly Tx 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

118

GCCA Improved Early (0-3 mon.) Abstinence


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% 55%

High (7-12/12) GCCA * p<.05

119

Early (0-3 mon.) Abstinence Improved Sustained (4-9 mon.) Abstinence


19% 22% 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

120

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 ACC1 main findings are published and findings from two subsequent experiments are currently under review

CSAT is currently replicating ACRA/ACC in 32 sites

The ACC manual is being distributed via the website and the CD you have been provided.

121

Need for Tracks, Phases and Continuing Care

Almost a third of the adolescents are “returning” to treatment, 23% for the second or more time

We need to understand what did and did not work the last time and have alternative approaches

We need tracks or phases that recognize that they may need something different or be frustrated by repeating the same material again and again

We need to have better step down and continuing care protocols

122

Recommendations for Further Developments…

Evidenced based interventions can come from both research and practice

Evidence based interventions can improve implementation of treatment and treatment outcomes

Practice based evidence can be used to improve outcomes and is of equal importance

Evidenced based interventions and their outcomes can be replicated in practice

Continuing care and is a key determinant of long term outcomes

123

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

124

Resources for Finding Promising Programs:

Screeners and Other Measures related to adolescents: CSAT TIP 42- http://store.health.org/catalog/productDetails.aspx?ProductID=16979 NIAAA Handbook- pubs.niaaa.nih.gov/publications/Assesing%20Alcohol Drug Strategies Handbook- www.drugstrategies.com/teens GAIN Coordinating Center- www.chestnut.org/li/gain Co-Occurring Center for Excellence- www.coce.samhsa.gov/cod_resources/cb_assessment.htm

Prevention Programs related to adolescents: Substance use- modelprograms.samhsa.gov/ Suicide- www.sprc.org/ Violence- www.sshs.samhsa.gov/ Co-Occurring Cen. for Excel.- http://www.coce.samhsa.gov/cod_resources/cb_prevention.htm Other materials- http://www.health.org/

Treatment Programs related to adolescents: Substance use disorder (SUD)- www.chestnut.org/li/apss/CSAT/protocols Mental disorder (MD) & systems of care-

http://www.mentalhealth.samhsa.gov/cmhs/ChildrensCampaign/practices.asp Traumatic disorders and child maltreatment- www.nctsnet.org Co-Occurring Cen. for Excel.- www.coce.samhsa.gov/cod_resources/cb_treatmentservice.htm

http://store.health.org/catalog/productDetails.aspx?ProductID=16979

http://pubs.niaaa.nih.gov/publications/Assesing%20Alcohol

http://www.drugstrategies.com/teens

http://www.chestnut.org/li/gain

http://www.coce.samhsa.gov/cod_resources/cb_assessment.htm

http://modelprograms.samhsa.gov/

http://modelprograms.samhsa.gov/

http://www.sprc.org/

http://www.sshs.samhsa.gov/

http://www.coce.samhsa.gov/cod_resources/cb_prevention.htm

http://www.health.org/

http://www.chestnut.org/li/apss/CSAT/protocols

http://www.mentalhealth.samhsa.gov/cmhs/ChildrensCampaign/practices.asp

http://www.nctsnet.org/

http://www.coce.samhsa.gov/cod_resources/cb_treatmentservice.htm

advances in adolescent substance abuse treatment effectiveness michael dennis, ph.d. chestnut health...

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