addiction: what every judge should know michael l. dennis, ph.d. chestnut health systems normal, il...

Addiction: What Every Judge Should Know

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

Presentation at “Addiction: What Every Judge Should Know” workshop, March 5, 2009, Paul Brown Stadium, Cincinnati, Ohio. This presentation was supported by funds from Ohio Supreme Court and Bureau of Justice Assistance Edward Byrne Competitive National Interest Grant no 2008-DD-BX-0710 and using data from NIDA grants no. R01 DA15523, R37-DA11323 and CSAT contract no. 270-07-0191. It is available electronically at www.chestnut.org/li/posters . The opinions are those of the authors do not reflect official positions of the government. Please address comments or questions to the author at [email protected] or 309-820-3805.

2

1. Illustrate the Chronic Nature of Addiction and the Correlates of Recovery

2. Demonstrate the Feasibility of Managing Addiction Across Episodes of Treatment to Improve Long Term Outcomes

3. Identify the Common Gaps in the Existing Treatment System and What it Means to Move it Toward Evidenced Based Practice

4. Demonstrate the Usefulness of Practice Based Evidence to Inform Clinical Decision Making About Placement and Treatment Planning

Goals of this Presentation are to

3

Illustrate the Chronic Nature of Addiction and the Correlates of Recovery

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; Dennis & Scott 2007

5

Problems Vary by Age

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


6

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

$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


7

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

8

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

9Image courtesy of Dr. GA Ricaurte, Johns Hopkins University School of Medicine

Serotonin Present in Cerebral Cortex Neurons

Reduced in response to excessive use Still not back to normal after 7 years

10

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

pain

Adolescent Brain Development Occurs from the

Inside to Out and from Back to Front

11

Committing property crime, drug related crimes, gang related crimes, prostitution, and gambling to trade or get the money for alcohol or other drugs

Committing more impulsive and/or violent acts while under the influence of alcohol and other drugs

Crime levels peak between ages of 15-20 (periods or increased stimulation and low impulse control in the brain)

Adolescent crime is still the main predictor of adult crime Parent substance use is intertwined with child maltreatment and neglect –

which in turn is associated with more use, mental health problems and perpetration of violence on others

Overlap with Crime and Civil Issues

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

Lifetime Mental Health Diagnosis and Remission

Source: Dennis, Coleman, Scott & Funk forthcoming; National Co morbidity Study Replication

15% 13%8%

25%

10% 10% 8% 8%

46%

31%

7%

20%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Any

AO

D

Alc

ohol

Dru

g

Any

Ext

erna

lizi

ng

Con

duct

Opp

osit

iona

lD

efia

nt

Inte

rmit

tent

Exp

losi

ve

Att

enti

on D

efic

it

Any

Int

erna

lizi

ng

Anx

iety

:

Moo

d :

Pos

ttra

umat

icS

tres

s

Lifetime Diagnosis

10% 10% 15% 8% 9%4%

18%12% 11%

3%4%7%

Past Year Remission

66%

77%

83%

58%

89% 89%

45%50%

39%

56%48%40%

Remission Rate (% Remission / % Dependent)

SUD Remission Rates are BETTER than Most Major DSM Diagnoses

17

The Cyclical Course of Relapse, Incarceration, Treatment and Recovery (Adults)

In the Community

Using (53% stable)

In Treatment (21% stable)

In Recovery (58% stable)

Incarcerated(37% stable)

6%

28%

13%

30%

8%

25%

31%

4%

44%7%

29%

7%

Treatment is the most likely path

to recovery

P not the same in both directions

Over half change status annually

Source: Scott, Dennis, & Foss (2005)

18Source: Scott, Dennis, & Foss (2005)

Predictors of Change Also Vary by Direction

In the Community

Using (53% stable)


28%

29%

Probability of Sustaining Abstinence - times in treatment (0.83) + Female (1.72)- homelessness (0.61) + ASI legal composite (1.19)- number of arrests (0.89) + # of sober friend (1.22)

+ per 77 self help sessions (1.82)

Probability of Transitioning from Using to Abstinence - mental distress (0.88) + older at first use (1.12) -ASI legal composite (0.84) + homelessness (1.27)

+ # of sober friend (1.23)+ per 8 weeks in treatment (1.14)

19

Percent Sustaining Abstinence Through Year 8 by Duration of Abstinence at Year 7

36%

66%

86% 86%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 to 12 months(n=157; OR=1.0)

1 to 3 years(n=138; OR=3.4)

3 to 5 years(n=59; OR=11.2)

5+ years(n=96; OR=11.2)

Duration of Abstinence at Year 7

% S

usta

inin

g A

bsti

nent

thro

ugh

Yea

r 8

.

It takes a year of abstinence

before less than half relapse

Even after 3 to 7 years of abstinence about 14% relapse

Source: Dennis, Foss & Scott (2007)

1.22

20

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Using(N=661)

1 to 12 ms(N=232)

1 to 3 yrs(N=127)

3 to 5 yrs(N=65)

5 to 8 yrs(N=77)

% Days of Psych Prob (of 30 days)

% Above Poverty Line

% Days Worked For Pay (of 22)

% of Clean and Sober Friens

% Days of Illegal Activity (of 30 days)

Other Aspects of Recovery by Duration of Abstinence of 8 Years1-12 Months:

Immediate increase in clean and sober friend

1-3 Years: Decrease in

Illegal Activity; Increase in

Psych Problems

3-5 Years: Improved

Vocational and Financial Status

5-8 Years: Improved

Psychological Status

Source: Dennis, Foss & Scott (2007)

21

Death Rate by Years of Abstinence

Source: Scott, Dennis, & Funk (2008)

4.5%

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%

Household

(OR=1.00)

Less than 1

(OR=2.87)

1-3 Years

(OR=1.61)

4-8 Years

(OR=0.84)

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%

Household

(OR=1.00)

Less than 1

(OR=2.87)

1-3 Years

(OR=1.61)

4-8 Years

(OR=0.84)

Users/ Early Abstainers 2.87

times more likely to die in the next year

The Risk of Death goes down with

years of sustained abstinence

It takes 4 or more years of abstinence for

risk to get down to

community levels

11.9%

7.1%

3.8%

22

These studies provide converging evidence demonstrating that

Addiction is a brain disorder with the highest risk being during the period of adolescent to young adult brain development

Addiction is chronic in the sense that it often lasts for years, the risk of relapse is high, and multiple interventions are likely to be needed

Yet over two thirds of the people with addiction do achieve recovery

Treatment increases the likelihood of transitioning from use to recovery

Self help, peers and recovery environment help predict who stays there

Recovery is broader than just abstinence

23

Demonstrate the Feasibility of Managing Addiction Across Episodes of Treatment to Improve Long Term Outcomes

24

Lots of Geographic Variation in AOD Disorders

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

25

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

26

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

There Have Been Several Recent Reviews

Dennis & Scott (2007) review of evidenced related to understanding and managing addiction as a chronic condition

Marlowe (2008) and Bhati et al (2008) meta analyses of Drug Treatment Court Effectiveness and Cost-Effectiveness

Mckay’s (in press) review of 22 experiments and quasi experiments managing addiction over time found improved outcomes in 38% of those focused on less than 3 months, 44% on those that focused on 3 to 12 months and 100% of those that focused on more than 12 months

Experiments with Continuing Care

Assertive Continuing Care 1 (ACC-2) experiment with 183 adolescents discharged from residential substance abuse treatment and followed for 9 months in 1997-2004

Assertive Continuing Care 2 (ACC-2) experiment with 342 adolescents discharged from residential substance abuse treatment and followed for 12 months in 2005-2008

Assertive Outpatient Continuing Care Study (AOCCS) experiment with 320 adolescents admitted to outpatient substance abuse treatment and followed for 12 months in 2003-2008

29

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

30

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)

31

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.

32

ACC Improved Adherence

Source: Godley et al 2002, 2007

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

33

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

34

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

35

Relating Standards of Proof to Science

Beyond a Beyond a ReasonablReasonabl

e e DoubtDoubt

Clear andClear andConvincinConvincin

ggEvidenceEvidencePreponderancePreponderance

of the of the EvidenceEvidenceProbablProbabl

eeCauseCauseReasonablReasonabl

eeSuspicionSuspicion

LawLaw ScienceScienceMeta Analyses of Experiments/ Quasi Meta Analyses of Experiments/ Quasi

Experiments (Summary v Predictive, Experiments (Summary v Predictive, Specificity, Replicated, Consistency)Specificity, Replicated, Consistency)

Dismantling/ Matching study (What worked for Dismantling/ Matching study (What worked for whom)whom)

Experimental Studies (Multi-site,Experimental Studies (Multi-site, Independent,Independent, Replicated, Fidelity, Consistency)Replicated, Fidelity, Consistency)

Quasi-Experiments (Quality of Matching, Multi-Quasi-Experiments (Quality of Matching, Multi-site,site, Independent,Independent, Replicated, Consistency)Replicated, Consistency)

Pre-Post (multiple waves), Expert ConsensusPre-Post (multiple waves), Expert ConsensusCorrelation and Observational studiesCorrelation and Observational studiesCase Studies, Focus GroupsCase Studies, Focus GroupsPre-data Theories, Logic ModelsPre-data Theories, Logic ModelsAnecdotes, AnalogiesAnecdotes, Analogies

ST

RO

NG

ER

Source: Marlowe 2008

Weak Levels of

Expert Testimony

36

Meta Analyses of Experiments/ Quasi Meta Analyses of Experiments/ Quasi Experiments (Summary v Predictive, Experiments (Summary v Predictive, Specificity, Replicated, Consistency)Specificity, Replicated, Consistency)

Dismantling/ Matching study (What worked for Dismantling/ Matching study (What worked for whom)whom)

Experimental Studies (Multi-site,Experimental Studies (Multi-site, Independent,Independent, Replicated, Fidelity, Consistency)Replicated, Fidelity, Consistency)

Quasi-Experiments (Quality of Matching, Multi-Quasi-Experiments (Quality of Matching, Multi-site,site, Independent,Independent, Replicated, Consistency)Replicated, Consistency)

Pre-Post (multiple waves), Expert ConsensusPre-Post (multiple waves), Expert ConsensusCorrelation and Observational studiesCorrelation and Observational studiesCase Studies, Focus GroupsCase Studies, Focus GroupsPre-data Theories, Logic ModelsPre-data Theories, Logic ModelsAnecdotes, AnalogiesAnecdotes, Analogies

Relating Standards of Proof to Science

Beyond a Beyond a ReasonablReasonabl

e e DoubtDoubt

Clear andClear andConvincinConvincin

ggEvidenceEvidencePreponderancePreponderance

of the of the EvidenceEvidenceProbablProbabl

eeCauseCauseReasonablReasonabl

eeSuspicionSuspicion

LawLaw ScienceScience

ST

RO

NG

ER

Adult Drug Treatment Courts 5 meta analyses of 76 studies found crime reduced 7-26% with

$1.74 to $6.32 return on investment

Family Drug Treatment Courts – one multisite quasi experiment with positive findings for

parent and child

DWI Treatment Courts – one quasi experiment and five observational studies with effect sizes of 0 to .45 and one quasi experiment (effect size=.29

to .57)Juvenile Drug Treatment Courts, Mental Health Treatment Courts – multiple small studies with

mix of positive, null and negative findings

37

Potential Cost Savings of Expanding Diversion to Treatment Programs in Justice Settings

Currently treating about 55,000 people in these courts at a cost of $515 million with an average return on investment (ROI) of $2.14 per dollar

The ROI is higher (2.71) for those with more crime

It is estimated that there are at least twice as many people in need of drug court as getting it

Investing the $1 billion to treat them would likely produce a ROI of $2.17 billion to society

Source: Bhati et al (2008) To Treat or Not To Treat: Evidence on the Prospects of Expanding Treatment to Drug-Involved Offenders. Washington, DC: Urban Institute.

38

Experiments with Recovery Management Checkups to Manage Addiction Over Years

Early Re-Intervention (ERI) Experiment 1 – 448 adults entering treatment followed for 2-years from 2000-2002

Early Re-Intervention (ERI) Experiment 2 – 446 adults entering treatment followed for 5-years from 2004-2009

Women Offenders – 450 women coming out of Cook County jail and followed for 3-years from 2008-2013

Early Re-Intervention for Adolescents (ERI-A) – feasibility studies currently being conducted with over longitudinal data on over 4,000 adolescents

39

Recovery Management Checkup (RMC) Quarterly Screening to determining “Eligibility” and “Need” Linkage meeting/motivational interviewing to:

– provide personalized feedback to participants about their substance use and related problems,

– help the participant recognize the problem and consider returning to treatment,

– address existing barriers to treatment, and – schedule an assessment.

Linkage assistance– reminder calls and rescheduling– Transportation and being escorted as needed

Treatment Engagement Specialist

40

ERI-2 Time to Treatment Re-Entry

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 0 90 18

0270 36

0450

540

630

Days to Re-Admission (from 3 month interview)

Percent Readmitted 1+ Times

55% ERI-2 RMC* (n=221)

37% ERI-2 OM (n=224)

*Cohen's d=+0.41 Wilcoxon-Gehen

Statistic (df=1)=16.56, p <.0001

630-246 = -384 days

The size of the effect is growing every quarter

Source: Scott & Dennis (in press)

RMC increases the odds of transitioning from using to treatment within a quarter by 2.1

41

ERI-2: Impact on Outcomes at 45 Months

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Re-enteredTreatment(d=0.22)*

of 14 SubsequentQuarters in Need

(d= 0.26) *

of 1260 DaysAbstinent(d= 0.26)* (d= -0.32)*

Still in need of Tx at Mon 45 (d= -0.22) *

Per

cent

age

OM RMC

* p<.05

55%

41%

67%

50%

56%

38%

Fewer Seq.Quartersin Need

74%

More days of

abstinent

of 180 Daysof Treatment

71%

61%

RMC Increased Treatment Participation

RMC Increased Treatment Participation

47%

Less likely to be in

Need at 45m


42

In the Community

Using (75% stable)




4%

10%

10%

23%

8%

13%

35%

7%

25%6%

24%

3%

ERI 2: Average Quarterly Transitions over 3 years

34% Changed Status in an

Average Quarter

Again the Probability of

Entering Recovery is Higher from

Treatment

Source: Riley, Scott & Dennis, 2008

43

In the Community

Using (75% stable)


10%

In Recovery(58% stable)

35% 25%

Source: Riley, Scott & Dennis, 2008

ERI 2: Average Quarterly Transitions over 3 years

Transition to Tx (vs use)- Tx Resistance (0.93) + Freq. of Use (25.30)+ Desire for Help (1.23)+ Wks of Self Help (1.51)+ Self Help Act. (1.37)+ Prior Wks of Tx (1.07)+ RMC (2.08)

Transition Tx to Recovery (vs. relapse) - Freq. of Use (0.01) + Wks Self Help (1.39)-Tx Resistance (0.79) +Self Help Act. (1.31)

44

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

In the Community

Using (75% stable)




5%

12%

7%

20%

24%

10%

26%

7 %

19%7%

27%

3%

Source: Dennis et al 2007. 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)

45

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 Sustaining Recovery vs. Relapsing (+ 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)


46

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)



47

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.Source: Dennis et al 2007. 2006 CSAT AT data set

48

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%


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


49

These studies provide converging evidence demonstrating that

More assertive continuing care can increase adherence with continuing care expectations

A growing range of drug treatment courts are being found effective and cost effective

Recovery management checkups can identify people who have relapsed and get them back to treatment faster

That doing each improves short and long term outcomes That it appears feasible to extend recovery management

checkups to adolescents, but that there is a need to focus even more on recovery environment and peer groups

50

Identify the Common Gaps in the Existing Treatment System and What it Means to Move it Toward Evidenced Based Practice

51

Substance Use Disorder & Treatment Participation Rates by Age

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

5.4

8.1

1.8

5.9

17.3

6.2

8.9

21.2

7.3

0 5 10 15 20 25

12 to 17

18 to 25

26+

0 5 10 15 20 25

Drug Disorder

Alcohol Disorder

Any Disorder

Drug Treatment

Alcohol Treatment

Any Treatment

Less than 1 in 17 adolescents, 1 in 22 young adults, and 1 in 12 adults

52

The Majority Stay in Tx Less than 90 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 .

52

42

20

33

0

30

60

90

Outpatient IntensiveOutpatient

Short TermResidential

Long TermResidential

Level of Care

Med

ian

Len

gth

of S

tay

in D

ays

Half are gone within 8 weeks, less than 25%

stay the 90 days recommended by NIDA

researchers

53

Less Than Half Are Positively Discharged

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%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Outpatient IntensiveOutpatient

Short TermResidential

Long TermResidential

Level of Care

Dis

char

ge S

tatu

s

Other

Terminated

Dropped out

Completed

Transferred

Less than 10% are transferred

54

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

55

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

56

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

Introducing explicit interventions that have worked well on average and have explicit implementation/ quality assurance protocols at the program and individual level

Collecting practice based evidence to evaluate performance and outcomes for the program, protocol or staff over time, or relative to other interventions

Introducing reliable and valid assessment that can be used immediately to guide clinical judgments about diagnosis/severity, placement, treatment planning, implementation and the response to treatment

Pooling the above to drive needs assessment, performance monitoring and long term program evaluation and planning

57

What is Treatment? Motivational Interviewing and other protocols to help them understand how

their problems are related to their substance use and that they are solvable Residential, IOP and other types of structured environments to reduce short

term risk of relapse Detoxification and medication to reduce pain/risk of withdrawal and

relapse, including tobacco cessation Evaluation of antecedents and consequences of use Community Reinforcement Approaches (CRA) Relapse Prevention Planning Cognitive Behavioral Therapy (CBT) Proactive urine monitoring Motivational Incentives / Contingency Management Access to communities of recovery for long term support, including 12-

step, recovery coaches, recovery schools, recovery housing, workplace programs

Continuing care, phases for multiple admission

58

Other Specific Services that are Screened for and Needed by People in Treatment:

Tobacco cessation HIV Intervention to reduce high risk pattern of behavior

(sexual, violence, & needle use) Anger Management Psychiatric services related to depression, anxiety,

ADHD/Impulse control, conduct disorder/ ASPD/ BPD, Gambling

Trauma, suicide ideation, and para-suicidal behavior Child maltreatment and domestic violence interventions

(not just reporting protocols) Family, school and work problems Case management and work across multiple systems of

care and time

59

Components of Comprehensive Drug Components of Comprehensive Drug Addiction Treatment Recommended by NIDAAddiction Treatment Recommended by NIDA

www.drugabuse.gov

60

Two Key Resources Available from NIDATwo Key Resources Available from NIDA((http://www.drugabuse.gov ))

http://www.drugabuse.gov/

61

Major Predictors of Bigger Effects

1. A strong intervention protocol based on prior evidence

2. Quality assurance to ensure protocol adherence and project implementation

3. Proactive case supervision of individual

4. Triage to focus on the highest severity subgroup

62

Impact of the numbers of these Favorable features on Recidivism in 509 Juvenile Justice Studies in Lipsey Meta Analysis

Source: Adapted from Lipsey, 1997, 2005

Average Practice

The more features, the

lower the recidivism

63

Cognitive Behavioral Therapy (CBT) Interventions that Typically do Better than Usual Practice in Reducing Juvenile 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

64

15%

19%

5%3%

0%

5%

10%

15%

20%

25%

Mon 12 Mon 24

Off Site

On-SiteWithImmediateFeedback

Impact of Simple On-site Urine Protocol with Feedback On False Negative Urines


On-site Urine

Feedback Protocol

associated with Lower

False Negatives (19 v 3%)

65

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

66

Range of Effect Sizes (d) of MET/CBT for Change in Days of Abstinence by Site

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

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

36 Replication 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

Replication Sites Averaged Better than

Experiment

75% above medianof Experiment

6 programs completely

above Experiment

67

Number of Problems by Level of Care (Triage)

39%50% 55%

67%78%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Outpatient(OR=1)

IntensiveOutpatient(OR=1.6)

Long TermResidential(OR=1.9)

Med. TermResidential(OR=3.2)

Short TermResidential(OR=5.5)

0 to 1

2 to 4

5 or more

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

Source: Dennis et al 2009; CSAT 2007 Adolescent Treatment Outcome Data Set (n=12,824)

Clients entering Short Term Residential

(usually dual diagnosis) have 5.5 times higher

odds of having 5+ major problems*

68

15%

45%

70%

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

100%

Low (OR 1.0)

Mod.(OR=4.6)

High(OR=13.2)

NoneOneTwoThreeFourFive+

No. of Problems* by Severity of Victimization

Severity of Victimization

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

Source: Dennis et al 2009; CSAT 2007 Adolescent Treatment Outcome Data Set (n=12,824)

Those with high lifetime

levels of victimization have 13 times higher odds of

having 5+ major

problems*

69

Victimization and Level of Care Interact to Predict Outcomes

Source: Funk, et al., 2003

0

5

10

15

20

25

30

35

40

Intake 6 Months Intake 6 Months

Mar

ijua

na U

se (

Day

s of

90)

OP -High OP - Low/Mod Resid-High Resid - Low/Mod.

CHS Outpatient CHS Residential Traumatized groups have

higher severity

High trauma group does not respond to CHS OP

Both groups respond to residential treatment

70

Crime/Violence and Substance Problems Interact to Predict Any Recidivism

Low

Mod.

High

LowMod

.High0%

20%

40%

60%

80%

100%

Source: CYT & ATM Data

12 m

onth

rec

idiv

ism

Crime/ Violence predicted recidivism

Substance Problem Severity predicted

recidivismKnowing both was the

best predictor

Substance Problem

Scale

Crime and Violence

Scale

71

Crime/Violence and Substance Problems Interact Differently to Predict Recidivism to Violent Crime

Low

Mod.

High

LowMod

.High

Source: CYT & ATM Data

12 m

onth

rec

idiv

ism

T

o vi

olen

t cri

me

or a

rres

t

Substance Problem

Scale

Crime and Violence

Scale

0%

20%

40%

60%

80%

100%

Crime/ Violence predicted

violent recidivism

(Intake) Substance Problem Severity did

not predict violent recidivism

Knowing both was the best predictor

72

Only 5-10% of those with abuse/dependence are entering treatment Less than 75% stay the 90 days recommended by NIDA (half less than 50 days) Less than half are positively discharge Less than 10% leaving higher levels of care are transferred to outpatient continuing

care The majority of programs do NOT use standardized assessment, evidenced based

treatment, track the clinical fidelity of the treatment they provide or monitor their own performance in terms of client outcomes

Evidenced based practices can improve outcomes We can learn from practice based evidence

Problems With the Treatment System

73

Demonstrate the Usefulness of Practice Based Evidence to Inform Clinical Decision Making About Placement and Treatment Planning

74

No or Inconsistent Use of Placement Criteria

Average staff education is an Associate Degree and stay less than 2 years

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.

The American Society for Addiction Medicine (ASAM) has tried to recommend placement rules for deciding what level of care an adolescent should receive based on expert opinion, but run into many problems.

75

Examples of problems with placement (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

76

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

77

Global Appraisal of Individual Needs (GAIN)

The GAIN is a family of assessment tools ranging from a 5 minute screener to 20 minute quick assessment to a 1-2 hour comprehensive bio-psychosocial

The GAIN Recommendation and Referral Summary (GRRS) is a 6 to 8 page narrative report designed to help clinical staff generate diagnostic impressions, preliminary treatment planning recommendations, and level of care placement recommendations.

For each ASAM dimension, the GRRS includes narrative summaries of the client’s problems, treatment history, and treatment planning recommendations

This information can also be used to group individuals with similar presenting profiles

78

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%

79

While over 50% go to outpatient in 7 of 8 clusters, there are a range of placements in each cluster

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

A Low-Low

B Low-Mod

C Mod-Mod

D Hi-Low

E Hi-Mod

F Hi-Hi (CC)

G Hi-Mod (E/P)

H Hi-Hi (I/P/M)

Outpatient (OP) Intensive Outpatient (IOP)

Outpatient Continuing Care (OPCC) Short Term Residential (STR)

Long Term Residential (LTR)

80

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

No AOD related Problem

No Health Problems

No Mental Health Problems

No Illegal Activity

No JJ System Involve.

Living in Community

No Family Prob.

Vocationally Engaged

Social Support

Count of above

Percent of Variance Explained

81

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)

Person “A” does better in Outpatient

Person “B” does better in Higher Levels of Care

82

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

83

A Low-Low (n=1456): Top 10 Tx Needs

79% - Not close to anyone in recovery, assign a recovery coach73% - Assign to relapse prevention52% - Discuss recent school problems and how they can be resolved50% - Coordinating care with juvenile justice system50% - HIV Intervention to reduce high risk pattern of sexual behavior41% - Increase structure to reduce recovery environment risk33% - Discussing the consequences of behavior control problems, the plan

to change, and possible referrals to help.31% - Referral for tobacco cessation30% - Review prior treatment experiences to determine what did and not

work29% - Develop plan for reduction of family fighting

84

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


85

C Mod-Mod (n=1734): Top 10 Tx Needs93% - Increase structure and/or residential treatment to reduce recovery environment

risk

91% - Discussing the consequences of behavior control problems, the plan to change, and possible referrals to help.

85% - Referral for mental health treatment

85% - Refer to anger management intervention

84% - Follow agency protocol related to child maltreatment reporting; Refer for trauma related intervention

82% - Review prior treatment experiences to determine what did and not work

76% - HIV Intervention to reduce high risk pattern of sexual behavior

72% - Discuss recent school problems and how they can be resolved

70% - Coordinating care with juvenile justice system

62% - Not close to anyone in recovery, assign a recovery coach

86

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


87

F Hi-Hi (CC) (n=1402): Top 10 Tx Needs

98% - Refer to continuing care following discharge from controlled environment

97% - Referral for mental health treatment

94% - Develop plan for obtaining stable housing

87% - Increase structure and/or residential treatment to reduce recovery environment risk

85% - Coordinating care with juvenile justice system

81% - HIV Intervention to reduce high risk pattern of sexual behavior

78% - Develop community re-entry plan

78% - Follow agency protocol related to child maltreatment reporting; Refer for trauma related intervention

72% - Discussing the consequences of behavior control problems, the plan to change, and possible referrals to help.

64% - Refer to anger management intervention

88

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


89

G Hi-Mod (Env/PH) (n=1038): Top 10 Tx Needs

100%-Consider need for detoxification or withdrawal services100% Consider medication to reduce non-opioid withdrawal and relapse99% - Review participation (attendance, motivation, participation, etc.) of client,

participation in family therapy, day treatment or other interventions to increase structure.

93% - Increase structure and/or residential treatment to reduce recovery environment risk

91% - Referral for mental health treatment79% - HIV Intervention to reduce high risk pattern of sexual behavior79% - Referral for tobacco cessation79% - Discussing the consequences of behavior control problems, the plan to

change, and possible referrals to help.74% - Review prior treatment experiences to determine what did and not work74% - Follow agency protocol related to child maltreatment reporting; Refer for

trauma related intervention

90

Summary of Best Level Of Care Based on Cluster and Expected Outcome

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Higher than OP 0.4%

Residential 14.1% 7.6% 38.3% 88.3% 94.1% 17.2% 8.6%

IOP/OPCC 27.9% 0.0%

OPCC 0.4% 30.2% 1.1% 78.2% 81.5%

IOP 10.5% 23.6% 0.0% 4.6% 9.9%

OP 99.6% 75.1% 38.6% 33.8% 10.6% 5.9% 0.0% 0.0%

Cluster ALow - Low (n=1025)

Cluster BLow - Mod (n=1654)

Cluster CMod-Mod (n=1209)

Cluster DHi-Low (n=687)

Cluster EHi-Mod

(n=1190)

Cluster GHi-Mod

(Env/PH)

Cluster HHi-Hi

(Intx/PH/MH

Cluster FHi-Hi (CC) (n=968)

*

*

*

*

* *

91

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

Source: CSAT 2007 AT Outcome Data Set (n=11,013)

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)

92

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)

93

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)

94

These analyses of Practice Based Evidence

Suggest that it is feasible to group people by their presenting needs and predict outcomes

This can be done by level of care or by type of evidenced based protocol within level of care or a subgroup (e.g., gender)

Making this data available to patients, families, clinical staff and the courts have the potential to improve patient outcome

Summary counts of need also have the potential to impact program planning and development

95

Concluding thoughts…

We need to strengthen our focus on prevention and treatment of substance use by adolescents and young adults

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 both evidenced based practices, and practice based evidence to improve outcomes

96

Sources and Related Work Bhati et al (2008) To Treat or Not To Treat: Evidence on the Prospects of Expanding Treatment to Drug-Involved Offenders. Washington, DC: Urban

Institute. Dennis, M.L., Coleman, V., Scott, C.K & Funk, R (forthcoming). The Prevalence of Remission from Major Mental Health Disorder in the US: Findings

from the National Co morbidity Study Replication. Dennis, M.L., Foss, M.A., & Scott, C.K (2007). An eight-year perspective on the relationship between the duration of abstinence and other aspects of

recovery. Evaluation Review, 31(6), 585-612 Dennis, M.L., Funk, R.R. & Hanes-Stevens, L. (2008). Moving the field from ‘no wrong door’ to the ‘best door’: An actuarial estimate of expected

outcomes by level of care among adolescents presenting for substance abuse treatment. Joint Meeting on Adolescent Treatment Effectiveness, March 25-27, 2008, Washington, DC.

Dennis, M.L., Godley, S.H., Diamond, G., Tims, F.M., Babor, T., Donaldson, J., Liddle, H., Titus, J.C., Kaminer, Y., Webb, C., Hamilton, N. and Funk, R. (2004). The Cannabis Youth Treatment (CYT) Study: Main Findings from Two Randomized Trials. Journal of Substance Abuse Treatment,27, 197-213.

Dennis, M.L., Ives, M., White, M., & Muck, R. (2008). The Strengthening Communities for Youth (SCY) initiative: A cluster analysis of the services received, their correlates and how they are associated with outcomes. Journal of Psychoactive Drugs, 40(1), 3-16.

Dennis, M. L., Scott, C. K. (2007). Managing Addiction as a Chronic Condition. Addiction Science & Clinical Practice , 4(1), 45-55. Dennis, M. L., Scott, C. K., Funk, R., & Foss, M. A. (2005). The duration and correlates of addiction and treatment careers. Journal of Substance Abuse

Treatment, 28, S51-S62. Dennis, M. L., & Scott, C. K. (2007). Managing substance use disorders (SUD) as a chronic condition. NIDA Addiction Science and Clinical Practice, 4(1),

45-55 Dennis, M. L., Scott, C. K., & Funk, R. (2003). An experimental evaluation of recovery management checkups (RMC) for people with chronic substance

use disorders. Evaluation and Program Planning, 26(3), 339-352. Dennis, M.L., White, M., Ives, M.I (2009). Individual characteristics and needs associated with substance misuse of adolescents and young adults in

addiction treatment. In Carl Leukefeld, Tom Gullotta and Michele Staton Tindall (Ed.), Handbook on Adolescent Substance Abuse Prevention and Treatment: Evidence-Based Practice. New London, CT: Child and Family Agency Press.

97

Sources and Related Work Epstein, J. F. (2002). Substance dependence, abuse and treatment: Findings from the 2000 National Household Survey on Drug Abuse (NHSDA Series A-

16, DHHS Publication No. SMA 02-3642). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies. Retrieved from http://www.DrugAbuseStatistics.SAMHSA.gov.

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.

Funk, R. R., McDermeit (Ives), M., Godley, S. H., & Adams, L. (2003). Maltreatment issues by level of adolescent substance abuse treatment: The extent of the problem at intake and relationship to early outcomes. Journal of Child Maltreatment, 8, 36-45.

Godley, S. H., Dennis, M. L., Godley, M. D., & Funk, R. R. (2004). Thirty-month relapse trajectory cluster groups among adolescents discharged from outpatient treatment. Addiction, 99(2 suppl), 129-139.

Godley, M. D., Godley, S. H., Dennis, M. L., Funk, R., & Passetti, L. L. (2002). A randomized field trial of an assertive aftercare protocol for adolescents following discharge from residential substance abuse treatment: Preliminary Outcomes. Journal of Substance Abuse Treatment, 23(1), 21-32.

Godley, M.D., Godley, S.H., Dennis, M.L., Funk, R.R., & Passetti, L.L. (2007). The Effect of Assertive Continuing Care on Continuing Care Linkage, Adherence, and Abstinence Following Residential Treatment for Adolescents. Addiction, 102(1), 81-92.

Godley, M.D., Kahn, J.H., Dennis, M.L., Godley, S.H., & Funk, R.R. (2005). The stability and impact of environmental factors on substance use and problems after adolescent outpatient treatment. Psychology of Addictive Behaviors, 19(1), 62-70.

Lipsey, M. W. (1997). What can you build with thousands of bricks? Musings on the cumulation of knowledge in program evaluation. New Directions for Evaluation, 76, 7-23.

Lipsey, M. W. (2005). What works with juvenile offenders: Translating research into practice. Paper presented at the Adolescent Treatment Issues Conference, Tampa.

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