understanding adolescent co-occurring disorders and the movement towards a more effective continuum...

Understanding Adolescent Co-occurring Disorders and the Movement towards a more Effective Continuum of Community Care

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

Presentation on November 4, 2008 at a conference on “Continuum of Community Care (Models of Systems of Care) for Adolescents with Co-Occurring Disorders: Best Practices and Model Programs from around the Country“ sponsored by OdysseyNH and the Cassey Foundation. 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 New Hampshire

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

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

4

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 CategoryAdolescent

OnsetRemission

Increasing rate of non-

users

5

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

Age 12-17

6

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%)

Age 12-17

7

Higher Severity is Associated with Higher Annual Cost to Society Per Person

Source: 2002 NSDUH

$0$231$231

$725$406

$0$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

No Alcohol orDrug Use

Light Alcohol

Use Only

AnyInfrequentDrug Use

Regular AODUse

AbuseDependence

Median (50th percentile)

$948

$1,613

$1,078$1,309

$1,528

$3,058Mean (95% CI)

This includes people who are in recovery, elderly, or do not use

because of health problemsHigher Costs

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 Brain Activity on PET Scan After Using CocaineAfter Using 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

Cocaine Abuser (10 days)

Cocaine Abuser (100 days)Photo courtesy of Nora Volkow, Ph.D. 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.

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

With repeated use, there is a cumulative

effect of reduced brain activity which

requires increasingly more stimulation (i.e.,

tolerance)

Even after 100 days of abstinence

activity is still low

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

Substance Use Careers Last for Decades C

um

ula

tive

Su

rviv

al

Years from first use to 1+ years abstinence302520151050

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

Median of 27 years from

first use to 1+ years

abstinence

Source: Dennis et al., 2005

13

Substance Use Careers are Longer the Younger the Age of First Use

Cu

mu

lati

ve S

urv

ival

Years from first use to 1+ years abstinence

under 15*

21+

15-20*

Age of 1st UseGroups

* p<.05 (different from 21+)

302520151050

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0


14

Substance Use Careers are Shorter the Sooner People Get to Treatment

Cu

mu

lati

ve S

urv

ival

20+

0-9*

10-19*

Year to 1st TxGroups

302520151050

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

* p<.05 (different from 20+)Source: Dennis et al., 2005

Years from first use to 1+ years abstinence

15

Treatment Careers Last for Years C

um

ula

tive

Su

rviv

al

Years from first Tx to 1+ years abstinence2520151050

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.10.0

Median of 3 to 4 episodes of treatment over 9 years


16

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

17

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

Source: Office of Applied Studies 1992- 2005 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

18

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

19

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

20

Past Year Alcohol or Drug Abuse or Dependence

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

7.7% NH vs.10.8% National

21

New Hampshire Population and Regions

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

<-US avg. 79.6

Northern - Carroll, Coos,

Grafton

Central - Belknap,

Merrimack, Strafford, Sullivan

Southern - Rockingham,

Cheshire, Hillsborugh

• 1,235,786 people in 9,3450 square miles (137.8 people per square mile or ppsm)

• Ranges for 18.8 ppsm in Coos County to 434.6 ppsm in Hillsborough County

• Approximately 9% age 12-17, 4% age 18-20, 71% age 21+

• Mix of Urban, Small Urban & Rural Systems

22

5.4

6.6

6.2

6.8

6.5

5.9

7.1

8.2

7.7

6.6

8.9

10.8

12.2

11.4

10.1

0 5 10 15

US

New Hampshire

Northern

Central

Southern

0 5 10 15

Drug Disorder

Alcohol Disorder

Any Disorder

Drug Treatment

Alcohol Treat.

Any Treatment

Adolescent Substance Use Disorder & Treatment Participation Rates

Less than 1 in 17 in US and 1 in 20 in NH get treatment

Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH NH Higher overall and in each region

23

246

328 36

4 416

649

758

909

654 70

9

513

363

481

560

488

489

-

100

200

300

400

500

600

700

800

900

1,000

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

OP (+136%)

IOP(+2167%)

Residential(-50%)

Detox(- 91%)

Change in NH Public Treatment Admissions:

Level of Care from 1992 to 2006

Source: OAS, 2006 – 1992-2006 TEDS Data

269% Growth from 1992 to 1998

46% decrease in the past

decade

Growth of IOP

24

-

100

200

300

400

500

600

700

800

900

1,000

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Other (-100%)

Other HealthProvider (-21%)

School (1860%)

OtherCommunityReferral (-17%)

Other AODProvider (36%)

Self/Family(363%)

Juvenile Justice(361%)


Referral Source from 1995 to 2006


No. from Juv. Justice Relatively Stable

Big Variation Caused by Changes

in School, Community, &

Family Referrals

25

-

100

200

300

400

500

600

700

800

900

1,000

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

5 or more Tx(-97%)

4 Prior Tx

(-100%)

3 Prior Tx(150%)

2 Prior Tx(175%)

1 Prior Tx(197%)

No Prior Tx(114%)


No. of Prior Admissions from 1995 to 2006


Major Shift from Multiple Admission to New Admissions

26

-

100

200

300

400

500

600

700

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Marijuana(189%)

Alcohol (148%)

Hallucinogens(-78%)Cocaine (50%)Opioids (1750%)

Stimulants(525%)

Methamphetamine(300%)

Psychotropics(700%)

Other(700%)


Focal Problems from 1995 to 2006


Opioid, Psychotropics, Stimulants/Meth, and other drugs are less common but growing fast

Marijuana and Alcohol are the most common problems

27

Summary of Problems in the Treatment System

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

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 Major problems are not reliably assessed (if at all) Difficult to link assessment data to placement or

treatment planning decisions

28

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

29

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

30

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

Source: Adapted from Lipsey, 1997, 2005

Average Practice

31

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

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

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

32

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

33

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

34

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

35

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

36

GAIN Clinical CollaboratorsAdolescent and Adult Treatment Program

10/07

GAIN State System

Virgin Islands

01 to 1011 to 25

26 to 130

Indiana

Kansas

MaineMontana

NebraskaNevada

North Dakota

Puerto Rico

Hawaii

New Mexico

South Dakota

Alabama

Arkansas

Iowa

Oklahoma

Rhode Island

South CarolinaDistrict Of ColumbiaTennessee

Utah

Louisiana

W. Virginia

Minnesota

Wisconsin

New Jersey

North Carolina

Alaska

Delaware

Maryland

Pennsylvania

Georgia

KentuckyVirginia

MichiganNew York

Oregon

Colorado

Texas

New Hampshire

Connecticut

Illinois

Missouri

Arizona

Florida

Ohio

Vermont

Idaho

Massachusetts

California

Washington

Wyoming

GAIN-SS State or County System

Number of GAIN SitesMississippi

37

CSAT GAIN Data (n=15,254)

*Any Hispanic ethnicity separate from race group.

Sources: CSAT AT 2007 dataset subset to adolescent studies (includes 2% 18 or older).

3%

17%

9%

71%

79%

28%

32%

42%

16%

27%

19%

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

Short Term Residential

Long Term Residential

Intensive Outpatient

Outpatient

15 to 17 years old

12 to 14 years old

Hispanic*

Mixed/Other

Caucasian

African American

Female

CSAT data dominated by

Male, Caucasians, age 15 to 17

CSAT data dominated by

Outpatient

CSAT residential more likely to be over 30 days

Admin

38

Substance Use Problems

83%

50%

29%

7%

34%

29%

26%

94%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Past Year Substance Diagnosis

Any Past Year Dependence

Any withdrawal symptoms in the past week

Severe withdrawal (11+ symptoms) in past week

Can Give 1+ Reasons to Quit

Any prior substance abuse treatment

Acknowledges having an AOD problem

Client believes Need ANY Treatment

Source: CSAT 2007 AT Outcome Data Set (n=12,601)

39

Past Year Substance Severity by Level of Care

38%

57%

72% 75%86%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

UseAbuseDependence

Note: OP=Outpatient, IOP=Intensive Outpatient; LTR= Long Term Residential (90+ days); MTR= Moderate Term Residential (30-90 days); STR=Short Term Residential (0-30 days)


40

Past 90 day HIV Risk Behaviors

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

64%

33%

29%

25%

20%

2%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Sexually active

Sex Under the Influence of AOD

Multiple Sex partners

Any Unprotected Sex

Victimized Physically, Sexually, orEmotionally

Any Needle use

41

Sexual Partners by Level of Care

27%33%

39% 38%52%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

No SexualPartners

OneSexualPartner

MultipleSexualPartners


42

Co-Occurring Psychiatric Problems


66%

50%

42%

35%

24%

14%

63%

45%

31%

22%

9%

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

43

Co-Occurring Psychiatric Diagnoses by Level of Care

29%42%

54% 52%68%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

None

One

Multiple


44

Severity of Victimization by Level of Care

38%

53%64% 59%

70%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

Low

Moderate

High


45

Severity of Victimization by Gender

41%55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Male Female

Low

Moderate

High


46

Past Year Violence & Crime

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


80%

68%

63%

48%

45%

43%

85%

71%

39%

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

47

Type of Crime by Level of Care

36%

53%64%

54%67%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

Drug Useonly

OtherCrime

ViolentCrime


48

Three

None

Five to Twelve

Four

Two

One

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Multiple Problems* are the Norm


Most acknowledge 1+ problems

Few present with just one problem (the

focus of traditional research)

In fact, 45%present acknowledging 5+

major problems

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

49

Number of Problems by Level of Care

39%50% 55%

67%78%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP LTR MTR STR

0 to 1

2 to 4

5 or more


50

Number of Problems by Level of Care

41%55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Male Female

0 to 1

2 to 4

5 or more


51

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


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

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

53

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

54

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)


55

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

56

$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

57

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

58

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)

59

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

60

36 Site Replication on MET/CBT5

AK

AL

ARAZ

CA CO

CT

DC

DE

FL

GA

HI

IA

ID

IL IN

KS KY

LA

MA

MD

ME

MI

MN

MO

MS

MT

NC

ND

NE

NH

NJ

NM

NV

NY

OH

OK

OR

PARI

SC

SD

TN

TX

UTVA

VTWA

WI

WV

WY

CYT: 4 Sites

EAT: 36 Sites

Source: Dennis, Ives, & Muck, 2008

61

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

62Source: Morral and Stevens 2003al 2006

63

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

64

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

65

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

66

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

67

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

68

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

69

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

70

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

71

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

72

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%

73

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

74

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)

75

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

76

Predicted Count of Positive Outcomes by Level of Care: Cluster C Mod-Mod (n=1209)

2

3

4

5

6

7

8

9

10

Outpatient Intensive Outpatient

Outpatient -Continuing Care

Residential

2

3

4

5

6

7

8

9

10

77

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


78

Predicted Count of Positive Outcomes by Level of Care: Cluster F Hi-Hi (CC) (n=968)

2

3

4

5

6

7

8

9

10

2

3

4

5

6

7

8

9

10

Outpatient Intensive Outpatient

Outpatient -Continuing Care

Residential

79

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


80

Predicted Count of Positive Outcomes by Level of Care: Cluster G. Hi-Mod (Env/PH) (n=749)

2

3

4

5

6

7

8

9

10

Outpatient IOP/OPCC Residential

2

3

4

5

6

7

8

9

10

Predicted Count of Positive Outcomes by Level of Care: Cluster Hi-Mod (Env/PH) (n=749)

81

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


82

Change in Days Abstinent (while in community) by Level of Care and Gender


0

10

20

30

40

50

60

70

80

90

Intake Last Followup

Day

s o

f A

bst

inen

ce

Female - OP (d=0.43)

Males - OP (d=0.33)

Female - Resid (d=0.82)

Males -Res (d=0.74)

83

MALES: Change in Days Abstinent in Community by type of Outpatient Approach


0

10

20

30

40

50

60

70

80

90

Intake Last Follow-up

Day

s of

abs

tine

nce

in C

omm

unit

y

MST (d=0.87) (n=25)

Other Mot. Interv (d=0.79) (n=130)

ACRA/ACC (d=0.53) (n=460)

Total (d=0.33) (n=6272)

CHS OP (d=0.15) (n=281)

MDFT (d=0.07) (n=99)

METCBT7 (d=-0.03) (n=93)

FSN (d=0.48) (n=337)

Other (d=0.43) (n=482)

EMPACT (d=0.4) (n=102)

METCBT5 (d=0.33) (n=3368)

Other CBT (d=0.32) (n=150)

Seven Challenges (d=0.27) (n=93)

METCBT12 (d=0.2) (n=506)

EPOCH (d=0.18) (n=146)

84

FEMALES: Change in Days Abstinent in Community by type of Outpatient Approach


0

10

20

30

40

50

60

70

80

90

Intake Last Follow-up

Day

s of

abs

tine

nce

in C

omm

unit

y

Total (d=0.42) (n=2339)

EMPACT (d=0.62) (n=31)

Other (d=0.52) (n=120)

CHS OP (d=0.48) (n=97)

METCBT12 (d=0.48) (n=174)

Seven Challenges (d=0.44) (n=51)

FSN (d=0.41) (n=96)

Other CBT (d=0.41) (n=35)

METCBT5 (d=0.4) (n=1491)

METCBT7 (d=0.38) (n=40)

MDFT (d=0.36) (n=28)

ACRA/ACC (d=0.35) (n=86)

EPOCH (d=0.02) (n=29)

Other Mot. Interv (d=0.87) (n=50)

MST (d=0.86) (n=11)

85

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)

86

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” (+ bad)+ Freq. Of Use (+5998.00) - Initial Weeks in Treatment (0.97)+ Illegal Activity (1.42) - Treatment Received During Quarter (0.50)+ Age (1.24) - Recovery Environment (r)* (0.69)

- Positive Social Peers (r) (0.70)


87

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)


88

In the Community

Using (75% stable)

In Treatment

(48 v 35% stable)

In Recovery (62% 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.

89

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

90

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

92

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

93

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)

94

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.

95

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

96

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

97

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

98

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.

99

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

100

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

101

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

102

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

understanding adolescent co-occurring disorders and the movement towards a more effective continuum...

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