advances in adolescent substance abuse treatment effectiveness michael dennis, ph.d. chestnut health...
TRANSCRIPT
Advances in Adolescent Substance Abuse Treatment Effectiveness
Michael Dennis, Ph.D.Chestnut Health Systems, Normal, IL
Presentation on August 31-September 4, 2009 3rd Annual Georgia School or Addiction Studies, “Keys to Change: Prevention, Treatment and Recovery, Savannah, GA. This presentation reports on treatment & research funded by the Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA) under contracts 270-2003-00006 and 270-07-0191, as well as several individual CSAT, NIAAA, NIDA and private foundation grants. The opinions are those of the author and do not reflect official positions of the consortium or government. Available on line at www.chestnut.org/LI/Posters or by contacting Joan Unsicker at 448 Wylie Drive, Normal, IL 61761, phone: (309) 451-7801, Fax: (309) 451-7763, e-mail: [email protected]
2
1. Examine the prevalence, course, and consequences of adolescent substance use, co-occurring disorders and the unmet need for treatment overall
2. Summarize major trends in the adolescent treatment system and Georgia
3. Highlight what it takes to move the field towards evidenced-based practice related to assessment, treatment, program evaluation and planning
4. Present the findings from several recent treatment studies on substance abuse treatment research, trauma and violence/crime
Goals of this Presentation are to
3
Part 1. Prevalence, course, and consequences of adolescent substance use, co-occurring disorders and the unmet need for treatment overall
4
Severity of Past Year Substance Use/Disorders (2002 U.S. Household Population age 12+= 235,143,246)
Dependence 5%
Abuse 4%
Regular AOD Use 8%
Any Infrequent Drug Use 4%
Light Alcohol Use Only 47%
No Alcohol or Drug Use
32%
Source: 2002 NSDUH
5
Problems Vary by Age
Source: 2002 NSDUH and Dennis et al forthcoming
0
10
20
30
40
50
60
70
80
90
100
12-13
14-15
16-17
18-20
21-29
30-34
35-49
50-64
65+
No Alcohol or Drug Use
Light Alcohol Use Only
Any Infrequent Drug Use
Regular AOD Use
Abuse
Dependence
NSDUH Age Groups
Severity Category
Over 90% of use and
problems start between the ages of
12-20
It takes decades before most recover or die
People with drug dependence die an
average of 22.5 years sooner than those
without a diagnosis
6
Crime & Violence by Substance Severity
0%
10%
20%
30%
40%
50%
60%
Serious FightAt School
Fighting withGroup
Sold Drugs Attacked withintent to harm
Stole (>$50) CarriedHandgun
Dependence (3.9%) Abuse (4.2%)
Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)
Light Alc Use (12.4%) No PY AOD Use (64.3%)
Source: NSDUH 2006
Adolescents 12-17Substance use severity is related to crime and violence
7
Family, Vocational & MH by Substance Severity
Source: NSDUH 2006
0%
10%
20%
30%
40%
50%
60%
10 or MoreArguments with
Parents
Disliked School GPA = D orlower
MajorDepression
Any MHTreatment
Dependence (3.9%) Abuse (4.2%)
Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)
Light Alc Use (12.4%) No PY AOD Use (64.3%)
Adolescents 12-17..as well as family, school
and mental health problems
8
1-2 M in 3-4 5-6
6-7 7-8 8-9
9-10 10-20 20-30
1-2 M in 3-4 5-6
6-7 7-8 8-9
9-10 10-20 20-30
Brain Activity on PET Scan After Brain Activity on PET Scan After Using CocaineUsing Cocaine
Photo courtesy of Nora Volkow, Ph.D. Mapping cocaine binding sites in human and baboon brain in vivo. Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, Macgregor RIR, Hitzemann R, Logan J, Bendreim B, Gatley ST. et al. Synapse 1989;4(4):371-377.
Rapid rise in brain activity after taking
cocaine
Actually ends up lower than they
started
9
Normal
10 days of abstinence
100 days of abstinence
Source: Volkow ND, Hitzemann R, Wang C-I, Fowler IS, Wolf AP, Dewey SL. Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190, 1992; Volkow ND, Fowler JS, Wang G-J, Hitzemann R, Logan J, Schlyer D, Dewey 5, Wolf AP. Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177, 1993.
Prolonged Substance Use Injures The Brain:Prolonged Substance Use Injures The Brain:Healing Takes Time Healing Takes Time
Normal levels of brain activity in PET
scans show up in yellow to red
After 100 days of abstinence, we can
see brain activity “starting” to recover
Reduced brain activity after regular
use can be seen even after 10 days
of abstinence
10Image courtesy of Dr. GA Ricaurte, Johns Hopkins University School of Medicine
11
Photo courtesy of the NIDA Web site. From A Slide Teaching Packet: The Brain and the Actions of Cocaine, Opiates, and Marijuana.
pain
Adolescent Brain Development Occurs from the
Inside to Out and from Back to Front
12
People Entering Publicly Funded Treatment Generally Use For Decades
Per
cen
t st
ill u
sin
g
Years from first use to 1+ years of abstinence302520151050
Source: Dennis et al., 2005
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
It takes 27 years before half reach 1 or more years of abstinence or die
13
Per
cen
t st
ill u
sin
g
Years from first use to 1+ years of abstinence
under 15
21+
15-20
Age of First Use*
302520151050
Source: Dennis et al., 2005
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
60% longer
The Younger They Start, The Longer They Use
* p<.05
14
Per
cen
t st
ill u
sin
g
Years from first use to 1+ years of abstinence
Years to first Treatment Admission*
302520151050
Source: Dennis et al., 2005
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
20 or more years
0 to 9 years
10 to 19 years
57% quicker
The Sooner They Get The Treatment, The Quicker They Get To Abstinence
•p<.05
15
After Initial Treatment…
Relapse is common, particularly for those who: – Are Younger– Have already been to treatment multiple times – Have more mental health issues or pain
It takes an average of 3 to 4 treatment admissions over 9 years before half reach a year of abstinence
Yet over 2/3rds do eventually abstain
Treatment predicts who starts abstinence
Self help engagement predicts who stays abstinent
Source: Dennis et al., 2005, Scott et al 2005
16
8.9%
21.2%
7.3%
0.5% 1.0% 0.6%0%
5%
10%
15%
20%
25%
12 to 17 18 to 25 26+
Alcohol or Other Drug Abuse or Dependence Any Public or Private Treatment
Substance Use Disorders are Common,But Treatment Participation Rates Are Low
Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH
Over 88% of adolescent and young adult treatment and
over 50% of adult treatment is publicly funded
Few Get Treatment: 1 in 17 adolescents,
1 in 22 young adults, 1 in 12 adults
Much of the private funding is limited to 30 days or less and authorized day by day
or week by week
17
Key Implications
Adolescence is the peak period of risk for and actual on-set of substance use disorders
Adolescent substance use can have short and long terms costs to society
There are real and often lasting consequence of adolescent substance use on brain functioning and brain development
Earlier Intervention during adolescence and young adult hood can reduce the duration of addiction careers
Multiple episodes of treatment are the norm Less than 1 in 17 adolescents with abuse/dependence are
getting treated
18
Part 2a. Trends in the Adolescent Substance Abuse Treatment System in the United States (US)
19
Trends in Adolescent (Age 12-17) Treatment Trends in Adolescent (Age 12-17) Treatment Admissions in the U.S.: 1992-2006Admissions in the U.S.: 1992-2006
Source: Office of Applied Studies 1992- 2006 Treatment Episode Data Set (TEDS) http://www.samhsa.gov/oas/dasis.htm
95,0
17
95,2
71 109,
123
122,
910
129,
859
131,
194
139,
129
137,
596
140,
542
148,
772
160,
750
158,
752
157,
036
142,
646
136,
660
10,000
30,000
50,000
70,000
90,000
110,000
130,000
150,000
170,000
190,000
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year of Admission
Num
ber
of A
dmis
sion
s A
ge 1
2-17
.
69% increase from95,017 in 1992
to 160,750 in 2002
15% drop off from 160,750 in 2002 to
136,660 in 2006
20
2002 Median Length of Stay is only 50 days
Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf .
0 30 60 90
Outpatient(37,048 discharges)
IOP(10,292 discharges)
Detox(3,185 discharges)
STR(5,152 discharges)
LTR(5,476 discharges)
Total(61,153 discharges)
Lev
el o
f C
are
Median Length of Stay
50 days
49 days
46 days
59 days
21 days
3 days
Less than 25% stay the
90 days or longer time
recommended by NIDA
Researchers
21
53% Have Unfavorable Discharges
Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf .
0% 20% 40% 60% 80% 100%
Outpatient(37,048 discharges)
IOP(10,292 discharges)
Detox(3,185 discharges)
STR(5,152 discharges)
LTR(5,476 discharges)
Total(61,153 discharges)
Completed Transferred ASA/ Drop out AD/Terminated
Despite being widely recommended, only 10% step down after intensive treatment
22
Programs often LACK Standardized Assessment for…
Substance use disorders (e.g., abuse, dependence, withdrawal), readiness for change, relapse potential and recovery environment
Common mental health disorders (e.g., conduct, attention deficit-hyperactivity, depression, anxiety, trauma, self-mutilation and suicidality)
Crime and violence (e.g., inter-personal violence, drug related crime, property crime, violent crime)
HIV risk behaviors (needle use, sexual risk, victimization)
Child maltreatment (physical, sexual, emotional) Recovery environment and peer risk
23
No or Inconsistent Use of Placement Criteria (even with ASAM)
difficulty synthesizing multiple pieces of information inconsistencies between competing rules the lack of the full continuum of care or specific services to
refer people to having to negotiate with the participant, families and funders
over what they will do or pay for there is virtually no actual data on the expected outcomes by
level of care to inform decision making related to placement In practice, programs primarily refer people to the limited range
of services they have readily available. Knowing nothing about the person other than what door they
walked through we can correctly predict 75% (kappa=.51) of the adolescent level of care placements
24
Other Challenges in Substance Abuse Treatment Workforce and Organizations
High turnover workforce with variable education background related to diagnosis, placement and treatment planning.
Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care
Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning
Missing or misrepresented data that needs to be minimized and incorporated into interpretations
25
Summary of Problems in the US Treatment System
Less than 26% of Adolescents in US stay the 3 months recommended by NIDA researchers
Less than half have positive discharges
After intensive treatment, less than 10% step down to outpatient care
Problems are often assessed in an unstandardized way that leads to under identification
Structural issues related to high turnover, complicated client needs, lack of data to inform clinical decision making and issues with missing or misrepresented data
26
Part 2b. Trends in the Adolescent Substance Abuse Treatment System in Georgia (GA)
27
Past Year Alcohol or Drug Abuse or Dependence
Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH
7.3% GA vs.9.8% National
Adolescents (12-17)
28
Georgia Population and Regions
Source: U.S. Census 2000 and OAS, 2006 – 2003, 2004, and 2005 NSDUH
• 8 million people in 57,906 square miles (141 people per square mile or ppsm)
• Ranges for over 1000 some areas to less than 15 ppsm in some rural areas
• 7 % age 12-17, 13 % age 18-25, 62 % age 26+
• 10 % speak language other than English at home
• Mix of Urban, Small Urban & Rural Systems
1
3 2
54
State Planning Regions
29
8.9%
7.3%
7.8%
7.5%
7.4%
6.9%
6.7%0.2%
0.2%
0.2%
0.2%
0.2%
0.2%
0.5%
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12%
National
Georgia
Region 1
Region 2
Region 3
Region 4
Region 5
AOD Disorder AOD TreatmentSource: OAS, 2006 from 2002, 2003, and 2004 NSDUH
Adolescent Substance Use Disorder & Treatment Participation Rates by Georgia State Planning Districts
Below National Average on
Abuse/Dependence
But also below in treatment
30
7.3%
17.9%
7.1%
0.2% 0.1% 0.7%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Age 12-17 Age 18 - 25 Age 26+
AOD Disorder AOD TreatmentSource: OAS, 2006 from 2002, 2003, and 2004 NSDUH
Substance Use Disorder & Treatment Participation Rates by Age in Georgia
1 in 179Young Adults
1 in 36Adolescents 1 in 10
Adults
31
Change in Adolescent Admissions by Level of Care in Georgia Public Treatment 1992-2005
Source: OAS, 2007 – 1992-2005 TEDS Data
709 82
9
871
890
866
701
526 64
4
1,06
5
1,60
8
1,77
9
1,95
7
1,61
5
2,55
7
-
500
1,000
1,500
2,000
2,500
3,00019
92
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
OP (268%)
IOP (511%)
Residential(95%)
Detox (69%)
386% growth since 1998
IOP and OP have grown
the most,Detox the least
Systems has had two major contractions
32
Change in Adolescent Referral Source in Georgia Public Treatment 1992-2005
Source: OAS, 2007 – 1992-2005 TEDS Data
-
500
1,000
1,500
2,000
2,500
3,00019
92
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Other (509%)
Other HealthProvider (42%)
School (-27%)
OtherCommunityReferral (167%)
Other AODProvider(27000%)
Self/Family(202%)
Juvenile Justice(340%)
Juvenile Justice is the largest
source of referral
33
Change in Adolescent Prior Tx Admissions in Georgia Public Treatment 1992-2005
Source: OAS, 2007 – 1992-2005 TEDS Data
-
500
1,000
1,500
2,000
2,500
3,00019
92
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
5 or more Tx (-63%)
4 Prior Tx (83%)
3 Prior Tx (274%)
2 Prior Tx (148%)
1 Prior Tx (216%)
No Prior Tx(315%)
1 in 5 Adolescents have been in
treatment before
34
Change in Adolescent Focal Problems in
Georgia Public Treatment 1992-2005
Source: OAS, 2007 – 1992-2005 TEDS Data
-
500
1,000
1,500
2,000
2,50019
92
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Marijuana (751%)
Alcohol (88%)
Cocaine (181%)
Methamphetamine(8040%)
Hallucinogens (-41%)
Stimulants(550%)
Psychotropics(1600%)
Opioids (1940%)
Inhalants (-20%)
Other (115%)
Primarily Marijuana and
Alcohol
But rapid growth in Methampethamine,
Opioids and Psychotropic's
35
Adolescent 2006 Length of Stay US vs. Georgia
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
US Georgia US Georgia US Georgia US Georgia
Residential IOP OP Total
366 DAYS OR MORE
181 TO 365 DAYS
121 TO 180 DAYS
91 TO 120 DAYS
61 TO 90 DAYS
46 TO 60 DAYS
31 TO 45 DAYS
0 TO 30 DAYS
Source: OAS 20072006 TEDS Episode Data
Median: 75 v. 115 days90+ Days: 41 vs. 52%
36
Adolescent 2006 Discharge Status US vs. Georgia
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
US Georgia US Georgia US Georgia US Georgia
Residential IOP OP Total
Other
AMA/ASA
TRANSFERRED
TREATMENTCOMPLETED
Source: OAS 20072006 TEDS Episode Data
Successful Discharge
56% vs. 44%
Transferred14% vs. 11%
37
Summary of Problems in the GA Treatment System
Less than 1 in 36 adolescents with abuse/dependence in Georgia are getting treated
The public systems is changing size, referral source, and focus
Marijuana and Alcohol are the most common drugs, but meth, opioids and pscyhotropics are growing fast
Other problems are often assessed in an unstandardized way that leads to under identification
About 48% of Adolescents in Georgia stay the 3 months recommended by NIDA researchers
About 56% have negative discharges After intensive treatment, only about 11% step down to
outpatient care
38
Part 3a. Highlight what it takes to move the field towards evidenced-based practice related to assessment, treatment, program evaluation and planning
39
So what does it mean to move the field towards Evidence Based Practice (EBP)?
Introducing explicit intervention protocols that are– Targeted at specific problems/subgroups and outcomes– Having explicit quality assurance procedures to cause adherence
at the individual level and implementation at the program level
Having the ability to evaluate performance and outcomes – For the same program over time, – Relative to other interventions
Introducing reliable and valid assessment that can be used – At the individual level to immediately guide clinical judgments
about diagnosis/severity, placement, treatment planning, and the response to treatment
– At the program level to drive program evaluation, needs assessment, performance monitoring and long term program planning
40
Major Predictors of Bigger Effects
1. Chose a strong intervention protocol based on prior evidence
2. Used quality assurance to ensure protocol adherence and project implementation
3. Used proactive case supervision of individual
4. Used triage to focus on the highest severity subgroup
41
Impact of the numbers of Favorable features on Recidivism (509 JJ studies)
Source: Adapted from Lipsey, 1997, 2005
Average Practice
42
Cognitive Behavioral Therapy (CBT) Interventions that Typically do Better than Usual Practice in Reducing Recidivism (29% vs. 40%)
Adolescent Community Reinforcement Approach (ACRA) Aggression Replacement Training Assertive Continuing Care Brief Strategic Family Therapy (BSFT) Interpersonal Social Problem Solving Functional Family Therapy (FFT) MET/CBT combinations and Other manualized CBT Moral Reconation Therapy Multidimensional Family Therapy (MDFT) Multisystemic Therapy (MST) Reasoning & Rehabilitation Thinking for a Change
Source: Adapted from Lipsey et al 2001, Waldron et al, 2001, Dennis et al, 2004
NOTE: There is generally little or no differences in mean effect size between these brand names
43
Other Protocols Targeted at Specific Issues:
Detoxification services and medication, particularly related to opioid and methamphetamine use
Tobacco cessation Adolescent psychiatric services related to depression,
anxiety, ADHD, and conduct disorder Trauma, suicide ideation, & parasuicidal behavior Need for child maltreatment interventions (not just
reporting protocols) HIV Intervention to reduce high risk pattern of sexual
behavior Anger Management Problems with family, school, work, and probation Recovery coaches, recovery schools, recovery housing and
other adolescent oriented self help groups / services
44
Impact of State Wide Screening in Washington Statewith the 2 page GAIN Short Screener
77% 86
%
73%
75%
61%67
%
83%
62%
75%
60%
57%
40% 46
%
12%
12%
47%
37%
35%
12%
11%
0%10%20%30%40%50%60%70%80%90%
100%
Substance AbuseTreatment(n=8,213)
Student AssistancePrograms(n=8,777)
Juvenile Justice(n=2,024)
Mental HealthTreatment (10,937)
Children'sAdministration
(n=239)
Either High on Mental Health High on Substance High on Both
Source: Lucenko et al (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/
Hig
h (2
+)
Problems could be easily identified Comorbidity
is common
45
Validation of Hi Co-occurring from GAIN Short Screener to Clinical Records by Setting
37%
35%
12%
11%
56%
34%
15%
9%
47%
0%10%20%30%40%50%60%70%80%90%
100%
SubstanceAbuse
Treatment(n=8,213)
StudentAssistancePrograms(n=8,777)
Juvenile Justice(n=2,024)
Mental HealthTreatment(10,937)
Children'sAdministration
(n=239)
GAIN Short Screener Clinical Indicators
NotAvailble
Source: Lucenko et al (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/
2 page screener relatively consistent with other clinical
indicators
46
On-site proactive urine testing can be used to reduce false negatives by more than half
Reduction in false negative reports at no
additional cost Effects grow when
protocol is repeated
47
Implementation is Essential (Reduction in Recidivism from .50 Control Group Rate)
The effect of a well implemented weak program is
as big as a strong program implemented poorly
The best is to have a strong
program implemented
well
Thus one should optimally pick the strongest intervention that one can
implement wellSource: Adapted from Lipsey, 1997, 2005
48
Implications of Implementation Science
Can identify complex and simple protocols that improve outcomes
Interventions have to be reliably delivered in order to achieve reliable outcomes
Simple targeted protocols can make a big difference
Need for reliable assessment of need, implementation, and outcomes
49
Key Issues that we try to address with the Global Appraisal of Individual Needs (GAIN)
High turnover workforce with variable education background related to diagnosis, placement and treatment planning.
Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care
Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning
Missing or misrepresented data that needs to be minimized and incorporated into interpretations
50
GAIN Logic ModelH
eter
ogen
eous
Nee
ds
and
Sev
erit
y
• Multiple domains• Focus on most common problems• Participant self description of
characteristics, problems, needs, personal strengths and resources
• Behavior recency, breadth, frequency• Utilization lifetime, recency and
frequency• Dimensional measures• Interpretative cut points
• Items and cut points mapped onto DSM for diagnosis, ASAM for placement, and to multiple standards and evidence- based practices for treatment planning
• Computer generated scoring and reports• Treatment planning recommendations
and links to evidence-based practice• Basic and advanced clinical
interpretation training and certification
Com
preh
ensi
ve A
sses
smen
t
Issue Instrument Feature Protocol Feature Outcome
Hig
h T
urno
ver
Wor
kfor
cew
ith
Var
iabl
e E
duca
tion
• Standardized approach to asking questions across domains
• Questions spelled out and simple question format
• Lay wording mapped onto expert standards for given area
• Built in transition statements, prompts, and checks for inconsistent and missing information.
• Responses to frequently asked questions• Multiple training resources
• Formal training and certification protocols on administration, clinical interpretation, data management, project coordination, local, regional, and national “trainers”
• Above focuses on consistency across populations, level of care, staff and time
• On-going quality assurance and data monitoring for the reoccurrence or problems at the staff (site or item) level
• Availability of technical assistance
Impr
oved
Rel
iabi
lity
and
E
ffic
ienc
y
51
GAIN Logic Model (continued)Issue Instrument Feature Protocol Feature Outcome
Mis
sing
or
Mis
repr
esen
ted
Dat
a
• Assurances, time anchoring, definitions, transition, and question order to reduce confusion and increase valid responses
• Cognitive impairment check• Validity checks on missing, bad,
inconsistency and unlikely responses• Validity checks for atypical and overly
random symptom presentations• Validity ratings by staff
• Training on optimizing clinical rapport• Training on time anchoring• Training answering questions, resolving
vague or inconsistent responses, following assessment protocol and accurate documentation.
• Utilization and documentation of other sources of information
• Post hoc checks for on-going site, staff or item problems
Impr
oved
Val
idit
y
Lac
k of
Acc
ess
to o
r us
e of
D
ata
at th
e P
rogr
am L
evel • Data immediately available to support
clinical decision making for a case• Data can be transferred to other clinical
information system to support billing, progress reports, treatment planning and on-going monitoring
• Data can be exported and cleaned to support further analyses
• Data can be pooled with other sites to facilitate comparison and evaluation
• PC and (soon) web based software applications and support
• Formal training and certification on using data at the individual level and data management at the program level
• Data routine pooled to support comparisons across programs and secondary analysis
• Over two dozen scientists working with data to link to evidence-based practice Im
prov
ed P
rogr
am P
lann
ing
and
Out
com
es
52
Part 3b. What has CSAT found when it did this over the past decade?
5353
CSAT Adolescent Treatment Grant Programs and Sites Using the GAIN: 1998-2008
AK
AL
AR
AZ
CACO DE
FL
GA
HI
IA
IN
KS
LA
MD
ME
MI
MN
MO
MS
MT ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PARI
SD
TN
TX
UT
VAWV
WY
ID
IL
KY
WA
WI
SC
NC
VT
MA
CT
DC
SAC\1
Grant AAFTARTATMCYT
JTDC\2
OtherEAT
OJJDP BIRT\3OJJDP RF
RCFSCYTCEYORP
\1 SAC data are not included in the CSAT 2008 Dataset\2 Includes Family Treatment Drug Courts\3 OJJDP BIRT data was not ready for the CSAT 2008 Dataset
5454
Current CSAT Data Set by Level of Care
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,746)
LTR: Long Term Residential 11.9%,
(n=1,866)
STR: Short Term Residential 2.6%,
(n=403)
OP: Outpatient
69.2%, (n=10,904)
CC-OP: Continuing
Care – Outpatient 7.7%, (n= 1,213)
IOP: Intensive Outpatient 8.6%,
(n=1,360)
5555
Current CSAT Data Set by Treatment Type
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,746)
Tx Man: Specific Manualized Treatment,
11.6%, (n=1,759)
MDFT: Multi-Dimensional
Family Therapy, 1.6%,
(n=249)
MET/CBT: Motivational Enhancement
Therapy/Cognitive-Behavioral Therapy 53.2%, (n=8,065)
Other: Non-manualized treatment, 11.4%, (n=1,722)
Other EBTx: Evidence Based Treatment, 6.7%,
(n=1,016)
7C: Seven Challenges, 1%, (n=124)
ACRA/ACC: Adolescent Community
Reinforcement Approach/ Assertive
Continuing Care, 14.6%, (n=2,214)
5656
CSAT Full GAIN Data
*Any Hispanic ethnicity separate from race group
Source: CSAT 2008 SA Dataset Adolescent Subset (n=16,006)
50%
10%
73%
10%
19%
31%
42%
27%
16%
18%
28%
81%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Single Parent
Employed
In School
Ever Homeless or Runaway
Mod-High Health problems
15 to 17 years old
12 to 14 years old
Hispanic*
Mixed/Other
Caucasian
African American
Female
CSAT data dominated by male, minority,
age 15 to 17
5757
Substance Use Severity
82%
52%
32%
25%
68%
5%
26%
48%
93%0
%
10
%
20
%
30
%
40
%
50
%
60
%
70
%
80
%
90
%
10
0%
Past Year Substance Diagnosis
3 or More Years of Use
Any Past Year Dependence
Any withdrawal symptoms in the past week
Severe withdrawal (11+ symptoms) in past week
Can Give 1+ Reasons to Quit*
Client believes Need ANY Treatment
Acknowledges having an AOD problem
Any prior substance abuse treatment
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,713) *(n=8,670)
5858
Past Year Substance Severity by Level of Care
48%60%
73% 80%89%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
OP
IOP
CC
-OP
LT
R
STR
UseAbuseDependence
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,508)
5959
Pattern of Weekly Use (13+/90 days) :
3%
2%
6%
2%
50%
27%
45%
15%
56%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Anything
Alcohol
Cannabis
Cocaine
Opioid
Other Drugs
Needle Use
Tobacco
Controlled Environment
Source: CSAT 2008 SA Dataset Adolescent Subset (n=14,294)
6060
Past 90 day HIV Risk Behaviors
Source: CSAT 2008 SA Dataset Adolescent Subset (n=14,557)
30%
62%
2%
63%
25%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sexually active
Multiple Sex partners
Any Unprotected Sex
Victimized Physically, Sexually, orEmotionally
Any Needle use
6161
Sexual Partners by Level of Care
27% 33% 27%42%
56%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
OP
IOP
CC
-OP
LT
R
STR
NoSexualPartnersOneSexualPartner
MultipleSexualPartners
Source: CSAT 2008 SA Dataset Adolescent Subset (n=13,311)
6262
Co-Occurring Psychiatric Problems
51%
62%
32%
39%13%
17%
45%
13%
24%
34%
44%
67%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any Co-occurring Psychiatric
Conduct Disorder
Attention Deficit/Hyperactivity Disorder
Major Depressive Disorder
Traumatic Stress Disorder
General Anxiety Disorder
Ever Physical, Sexual or Emotional Victimization
High severity victimization (GVS>3)
Ever Homeless or Runaway
Any homicidal/suicidal thoughts past year
Any Self Mutilation*
Prior Mental Health Treatment
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,882) *(n=9,061)
6363
Recovery Environment - Home
27%
11%
26%
75%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Family Historyof Substance Use
Weekly AlcoholUse at Home
Weekly Drug useat Home
Weekly FamilyProblems
Source: CSAT 2008 SA Dataset Adolescent Subset (n=14,782)
6464
Recovery Environment - Peers
31%
48%
27%
72%
64%
53%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Social Peers Getting Drunk Weekly+
School/Work Peers Getting DrunkWeekly+
Others at Home Getting DrunkWeekly+
Social Peers Using Drugs
School/Work Peers Using Drugs
Others at Home Using Drugs
Source: CSAT 2008 SA Dataset Adolescent Subset (n=14,832)
6565
Past Year Violence & Crime
*Dealing, manufacturing, prostitution, gambling (does not include simple possession or use)
Source: CSAT 2008 SA Dataset Adolescent Subset (n=14,016)
81%
69%
49%
73%
43%
85%
65%
46%
45%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any violence or illegal activity
Physical Violence
Any Illegal Activity
Any Property Crimes
Other Drug Related Crimes*
Any Interpersonal/ Violent Crime
Lifetime Juvenile Justice Involvement
Current Juvenile Justice involvement
1+/90 days In Controlled Environment
6666
Type of Crime by Level of Care
39%49% 51%
59% 67%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
OP
IOP
CC
-OP
LT
R
ST
R
Drug UseonlyOtherCrime*ViolentCrime
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,553)*Other crime includes vandalism, possession of stolen goods, forgery, and theft.
6767
Intensity of Juvenile Justice System Involvement
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,887)
Other JJ/CJ status16%
Past arrest/JJ/CJ
status6%
In detention/jail 14-29 days
7%
In detention/jail 30+ days
10%
Past year illegal activity/SA use
18%
On prob/parole 14+ days w/ 1+ drug screens
25%
Other prob/parole/
detention18%
6868
Count of Major Clinical Problems at Intake
19%
34%
13%
24%
12%
44%
51%
62%
81%
16%
34%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Alcohol
Cannabis
Other drug disorder
Depression
Anxiety
Trauma
Suicide
ADHD
CD
Victimization
Violence/ illegal activity
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,211)
6969
Number of Major Clinical Problems* at Intake by Gender
46% 42%56%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Tot
al
Mal
e
Fem
ale
None
One
Two
Three
Four
Five to Twelve
Source: CSAT 2008 SA Dataset Adolescent Subset (n=16,006)
*Based on count of self reporting criteria to suggest Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity
7070
Number of Major Clinical Problems* at Intake by Level of Care
40%47%
58%68%
78%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
OP
IOP
CC
-OP
LT
R
ST
R
None
One
Two
Three
Four
Five to Twelve
Source: CSAT 2008 SA Dataset Adolescent Subset (n=15,746)
*Based on count of self reporting criteria to suggest Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity
71
15%
45%
70%
0%10%20%30%40%50%60%70%80%90%
100%
Low (OR 1.0)
Mod.(OR=4.8)
High(OR=13.8)
NoneOneTwoThreeFourFive+
No. of Problems* by Severity of Victimization
Source: CSAT AT 2007 dataset subset to adolescent studies (N=15,254)
Those with high lifetime
levels of victimization
have 117 times higher odds of
having 5+ major
problems** (Alcohol, cannabis, or other drug disorder, depression, anxiety, trauma, suicide, ADHD, CD, victimization, violence/ illegal activity)
Severity of Victimization
7272
Intake to Last Wave Percent Change in GPRA Outcomes by Level of Care
Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only (n=11,688)
OP IOP LTR STR
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%In
take
6 M
on
Inta
ke
6 M
on
Inta
ke
6 M
on
Inta
ke
6 M
on
VocationallyEngaged
Housed inCommunity
No Arrest
Abstinent
All improve abstinence and re-arrest,
Residential have negative impact on housing
73
Any Illegal Activity in the Next Six Months by Intake Severity on Crime/Violence and Substance Problem Scales
58%46%
36%53%
33%26%44%
27%20%
0%
20%
40%
60%
An
y I
leg
al
Ac
tiv
ity
(mo
nth
s1
-6)
High Mod Low LowMod
High
Crime/Violence Scale (Intake)
Substance Problem Scale
(Intake)
Source: CSAT 2008 V5 dataset Adolescents aged 12-17 with 3 and/or 6 month follow-up (N=9006)
Intake Crime/ Violence Severity
Predicts Recidivism
Intake Substance Problem Severity
Predicts Recidivism
Knowing both is a better predictor(high –high group is 5.5 times more
likely than low low)
While there is risk, most (42-80%) actually do not commit
additional crime
7474
NOMS Outcome: Early Treatment Outcomes
58%
72%
56%
85%
83%
71%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Initiation with 14 days
Evidenced Based Practice
Engagement for at least 6 weeks
Any Continuing Care (91-180 days)
Substance Use-Abstinent/Reduced 50% at 3Months
12 Month Cost Within Bands for Initial Typeof Treatment
Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only (n=9,636)
7575
Performance: No Problems at Intake
Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only
37%
38%
39%
43%
98%
58%
77%
55%
37%
28%
8%
94%4%
1%
0%
10
%
20
%
30
%
40
%
50
%
60
%
70
%
80
%
90
%
10
0%
Abstinent*
Abuse/Dependence Sx*
Physical Health
Mental Health
Nights of Psychiatric Inpatient
Illegal Activity
Arrests
Housed in Community
Family/Home Problems
Vocational Problems*
Social Support/Engagement
Recovery Environment Risk
Quarterly Cost to Society
In Work/School
* Variables measure the last 30 days. All others measure the past 90 days.
7676
Performance: Outcome Status at Last Wave
Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only
72%
75%80%
89%
79%62%
43%90%
99%
78%
75%
66%
12%
18%
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Abstinent*
Abuse/Dependence Sx*
Physical Health
Mental Health
Nights of Psychiatric Inpatient
Illegal Activity
Arrests
Housed in Community**
Family/Home Problems
Vocational Problems*
Social Support/Engagement
Recovery Environment Risk
Quarterly Cost to Society
In Work/School**
Reduced 50% orNo Problem*
No Problem*
* Variables measure the last 30 days. All others measure the past 90 days. **Represents an increase
7777
Performance: Count of Positive Outcomes(Last FU – Intake) By Level of Care
Source: CSAT 2008 SA Dataset Subset to 1+ Follow ups and Adolescent only (n=13,381)
27% 33%23%
43% 45%
0%10%20%30%40%50%60%70%80%90%
100%O
P
IOP
CC
-OP
LT
R
ST
R
Five orMoreFour
Three
Two
One
None
NegativeoneLess than -1
78
Part 4. Findings from several recent treatment studies on substance abuse treatment research, trauma and violence/crime
CYT Cannabis Youth Treatment Randomized Field Trial
Sponsored by: Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services
Coordinating Center:Chestnut Health Systems, Bloomington, IL, and Chicago, ILUniversity of Miami, Miami, FLUniversity of Conn. Health Center, Farmington, CT
Sites:Univ. of Conn. Health Center, Farmington, CTOperation PAR, St. Petersburg, FLChestnut Health Systems, Madison County, ILChildren’s Hosp. of Philadelphia, Phil. ,PA
80
Context Circa 1997 Cannabis had become more potent, was associated with a wide of
problems (particularly when combined with alcohol), and had become the leading substances mentioned in arrests, emergency room admissions, autopsies, and treatment admissions (doubling in in 5 years)
Over 80% of adolescents with Cannabis problems were being seen in outpatient setting
The median length of stay was 6 weeks, with only 25% making it 3 months
There were no published manuals targeting adolescent marijuana users in outpatient treatment
The purpose of CYT was to manualize five promising protocols, field test their relative effectiveness, cost, and benefit-cost and provide them to the field
Source: Dennis et al, 2002
81
Randomly Assigns to:
MET/CBT5Motivational Enhancement Therapy/
Cognitive Behavioral Therapy (5 weeks)
MET/CBT12Motivational Enhancement Therapy/
Cognitive Behavioral Therapy (12 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:
MET/CBT5Motivational Enhancement Therapy/
Cognitive Behavioral Therapy (5 weeks)
(12 weeks)
Source: Dennis et al, 2002
82
5
10
5
11
14
23
0
5
10
15
20
25
MET/CBT5
MET/CBT12
MET/CBT12 +
FSN
MET/CBT5
ACRA MDFT
Hou
rs
Day
s
CaseManagement
FamilyCounseling
Collateral only
Multi-Familygroup
Multi-ParticipantGroup
Participant only
Incremental Arm Alternative Arm
Actual Treatment Received by Condition
Source: Dennis et al, 2004
MET/CBT12 adds 7 more sessions of
group
FSN adds multi family group,
family home visits and more case management
ACRA and MDFT both rely on
individual, family and case management instead of group
With ACRA using more individual therapy
And MDFT using more
family therapy
83
$1,559$1,413
$1,984
$3,322
$1,197$1,126
$-
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
MET/C
BT5 (6.8
wee
ks)
MET/C
BT12 (1
3.4 w
eeks
)
FSN (14.2
wee
ks w
/family
)
MET/C
BT5 (6.5
wee
ks)
ACRA (12.8
wee
ks)
MDFT(1
3.2 w
eeks
w/fa
mily)
$1,776
$3,495
NTIES E
st (6
.7 wee
ks)
NTIES E
st.(1
3.1 w
eeks
)
Ave
rage
Cos
t P
er C
lien
t-E
pis
ode
of C
are
|--------------------------------------------Economic Cost-------------------------------------------|-------- Director Estimate-----|
Average Episode Cost ($US) of Treatment
Source: French et al., 2002
Less than average
for 6 weeks
Less than average
for 12 weeks
Integrating family therapy
was less expensive
than adding it
84
CYT Increased Days Abstinent and Percent in Recovery*
Source: Dennis et al., 2004
0
10
20
30
40
50
60
70
80
90
Intake 3 6 9 12
Day
s A
bsti
nent
Per
Qua
rter
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
% in
Rec
over
y at
the
End
of
the
Qua
rter
Days Abstinent
Percent in Recovery
*no use, abuse or dependence problems in the past month while in living in the community
85
Similarity of Clinical Outcomes by Conditions
Source: Dennis et al., 2004
200
220
240
260
280
300
Tot
al d
ays
abst
inen
t.
over
12
mon
ths
0%
10%
20%
30%
40%
50%
Per
cent
in R
ecov
ery
. at
Mon
th 1
2
Total Days Abstinent* 269 256 260 251 265 257
Percent in Recovery** 0.28 0.17 0.22 0.23 0.34 0.19
MET/ CBT5 (n=102)
MET/ CBT12
FSN (n=102)
MET/ CBT5 (n=99)
ACRA (n=100)
MDFT (n=99)
Trial 1 Trial 2
* n.s.d., effect size f=0.06** n.s.d., effect size f=0.12
* n.s.d., effect size f=0.06 ** n.s.d., effect size f=0.16
Not significantly different by condition.
But better than the average for OP in ATM (200 days of
abstinence)
86
Moderate to large differences in Cost-Effectiveness by Condition
Source: Dennis et al., 2004
$0
$4
$8
$12
$16
$20
Cos
t per
day
of
abst
inen
ce o
ver
12 m
onth
s
$0
$4,000
$8,000
$12,000
$16,000
$20,000
Cos
t per
per
son
in r
ecov
ery
at m
onth
12
CPDA* $4.91 $6.15 $15.13 $9.00 $6.62 $10.38
CPPR** $3,958 $7,377 $15,116 $6,611 $4,460 $11,775
MET/ CBT5MET/
CBT12FSN MET/ CBT5 ACRA MDFT
* p<.05 effect size f=0.48** p<.05, effect size f=0.72
Trial 1 Trial 2
* p<.05 effect size f=0.22 ** p<.05, effect size f=0.78
MET/CBT5 and 12 did better
than FSN
ACRA did better than MET/CBT5, and both did better than MDFT
87
Range of Effect Sizes (d) for Change in Days of Abstinence (intake to 12 months) by Site
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
4 CYT Sites (f=0.39)(median within site d=0.29)
36 EAT Sites (f=0.21)(median within site d=0.49)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
Coh
en’s
d
Source: Dennis, Ives, & Muck, 2008
EAT Programs did Better than CYT on
average
75% above CYT median
6 programs completely above CYT
8888
Change in Abstinence (6 mo-Intake) After Adolescent CRA by Program
36%
24%
4%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
CYT AAFT Other
% P
oint
Cha
nge
in A
bsti
nenc
e
Source: CSAT 2008 SA Dataset subset to 6 Month Follow up (n=1,961)
(high monitoring) (mod. monitoring) (training only)
Effects associated with intensity of quality
assurance and monitoring
89Source: Morral and Stevens 2003al 2006
90
Program Evaluation Data
Level of Care Clinics Adolescents 1+ FU*
Outpatient/ Intensive Outpatient (OP/IOP)
8 560 96%
Long Term Residential (LTR)**
4 390 98%
Short Term Residential (STR)**
4 594 97%
Total 16 1544 97%
* Completed follow-up calculated as 1+ interviews over those due-done, with site varying between 2-4 planned follow-up interviews. Of those due and alive, 89% completed with 2+ follow-ups, 88% completed 3+ and 78% completed 4.
** Both LTR and STR include programs using CD and therapeutic community models
91
Adolescents more likely to transfer
Source: Adolescent Treatment Model (ATM) Data
0%
50%
100%0 30 60 90 120
150
180
210
240
270
300
330
360
390
Length of Stay
Perc
ent S
till i
n T
reat
men
t
Index Episode of Care (median=52 days; n=1380)
System Episode of Care (median=73 days; n=1380)
Length of Stay Across Episodes of care is about 50% longer
92
Change in Substance Frequency Scale by Level of Care\a
\a Source: Adolescent Treatment Model (ATM) data; Levels of care coded as Long Term Residential (LTR, n=390), Short Term Residential (STR, n=594), Outpatient/Intensive and Outpatient (OP/IOP, n=560);. T scores are normalized on the ATM outpatient intake mean and standard deviation. Significance (p<.05) marked as \t for time effect, \s for site effect, and \ts for time x site effect.
40
50
60
Intake 3 6 9 12
Months from Intake
STR\t,s,ts
LTR\t,ts
OP\t,s,ts
Residential programs start more severe, go down sharply,
but then come back over time
Note the sharp “hinge” in outcomes
during the active phase of AOD
treatment
Short- Term Resid. \t,s,ts
Long- Term Resid\t,ts
Outpatient\t,s
93
Change in Substance Problem Scaleby Level of Care\a
\a Source: Adolescent Treatment Model (ATM) data; Levels of care coded as Long Term Residential (LTR, n=390), Short Term Residential (STR, n=594), Outpatient/Intensive and Outpatient (OP/IOP, n=560);. T scores are normalized on the ATM outpatient intake mean and standard deviation. Significance (p<.05) marked as \t for time effect, \s for site effect, and \ts for time x site effect.
Change in Substance Problem Index 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
Short- Term Resid. \t,s,ts
Long- Term Resid\t,ts
Outpatient\t,s
94
Percent in Recovery (no past month use or problems while living in the community)
\a Source: Adolescent Treatment Model (ATM) data; Levels of cares coded as Long Term Residential (LTR, n=390), Short Term Residential (STR, n=594), Outpatient/Intensive and Outpatient (OP/IOP, n=560);. T scores are normalized on the ATM outpatient intake mean and standard deviation. Significance (p<.05) marked as \t for time effect, \s for site effect, and \ts for time x site effect.
0%
20%
40%
60%
80%
100%
Intake 3 6 9 12
Months from Intake
STR\t,s,ts
LTR\t,ts
OP\t,s
Short- Term Resid. \t,s,ts
Long- Term Resid\t,ts
Outpatient\t,s
Longer term outcomes are
similar on substance use
95
Change in Emotional Problem Scaleby 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,s,ts
OP\t,s
Short- Term Resid. \t,s,ts
Long- Term Resid\t,ts
Outpatient\t,s
Note the lack of a hinge; Effect is generally indirect (via
reduced use) not specific
96
Pattern of SA Outcomes is Related to the Pattern of Psychiatric Multi-morbidity
Source: Shane et al 2003, PETSA data
Months Post Intake (Residential only)0 3 6 12
Nu
mb
er o
f P
ast
Mon
th S
ub
stan
ce P
rob
lem
s
2+ Co-occurring 1 Co-occurring No Co-occurring
Multi-morbid Adolescents start the highest, change the most, and relapse the most
97
Change in Illegal Activity Scaleby Level of Care\a
\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\s
Short- Term Resid. \t,s,ts
Long- Term Resid\t,ts
Outpatient\t,s
Residential Treatments have a specific effect
Outpatient Treatments has an indirect effect
98
CSAT Adolescent Treatment GAIN Data from 203 level of care x site combinations
Outpatient
General Group Home
Short-Term Residential
Outpatient Continuing CareIntensive Outpatient
Long-term ResidentialModerate-Term Residential
Early InterventionOtherCorrections
Levels of Care
Source: Dennis, Funk & Hanes-Stevens, 2008
99
Ratings of Problem Severity (x-axis) by Treatment Utilization (y-axis) by Population Size (circle size)
12%
20%
14%
8%
14%
12%
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
-0.20 0.00 0.20 0.40 0.60 0.80 1.00
Average Current Problem Severity
Ave
rage
Cur
rent
Tre
atm
ent U
tili
zati
on
.
A Low-Low
B Low- Mod
C Mod-Mod
DHi-Low
EHi-Mod
F. Hi-Hi (CC)
G. Hi-Mod(Env Sx/ PH Tx)
9%
H. Hi-Hi(Intx Sx; PH/MH Tx) 12%
100
Variance Explained in NOMS Outcomes
\1 Past month \2 Past 90 days *All statistically Significant
26%
24%
11%
25%
15%
33%
26%
18%
14%
8%
24%
0% 5% 10% 15% 20% 25% 30% 35%
No AOD Use \1
No AOD related Prob.\1
No Health Problems \2
No Mental Health Prob.\2
No Illegal Activity \2
No JJ System Involve. \1
Living in Community \1
No Family Prob. \2
Vocationally Engaged \1
Social Support \2
Count of above
Percent of Variance Explained
101
Predicted Count of Positive Outcomes by Level of Care: Cluster A Low - Low (n=1,025)
2
3
4
5
6
7
8
9
10
Outpatient Higher LOC
2
3
4
5
6
7
8
9
10
Predicted Count of Positive Outcomes by Level of Care: Cluster A Low - Low (n=1,025)
102
Best Level of Care*: Cluster A Low - Low (n=1,025)Best Level of Care*:
Cluster A Low - Low (n=1,025)
99.6%
0.4%0%
20%
40%
60%
80%
100%
120%
Outpatient Higher LOC
% B
est P
redi
cted
Out
com
es
* Based on Maximum Predicted Count of Positive Outcomes
103
Best Level of Care*: Cluster C Mod-Mod (n=1209)
30.2%
7.6%
23.6%
38.6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Outpatient IOP OPCC Residential
% B
est P
redi
cted
Out
com
es
* Based on Maximum Predicted Count of Positive Outcomes
104
Best Level of Care*: Cluster F Hi-Hi (CC) (n=968)
81.5%
8.6%
0.0%
9.9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Outpatient IOP OPCC Residential
% B
est P
redi
cted
Out
com
es
* Based on Maximum Predicted Count of Positive Outcomes
105
Best Level of Care*: Cluster G Hi-Mod (Env/PH) (n=749)Best Level of Care*:
Cluster G Hi-Mod (Env/PH) (n=749)
94.1%
5.9%0.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Outpatient IOP/OPCC Residential
* Based on Maximum Predicted Count of Positive Outcomes
106
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents
In the Community
Using (75% stable)
In Treatment (48% stable)
In Recovery (62% stable)
Incarcerated(46% stable)
5%
12%
7%
20%
24%
10%
26%
7 %
19%7%
27%
3%
Source: 2006 CSAT AT data set
Avg of 39% change status each quarter
P not the same in both directions
Treatment is the most likely path
to recoveryMore likely than adults to stay 90 days in treatment (OR=1.7)
More likely than adults to be diverted
to treatment (OR=4.0)
107
In the Community
Using (75% stable)
12%
27%
Probability of Going from Use to Early “Recovery” (+ good)-Age (0.8) + Female (1.7),- Frequency Of Use (0.23) + Non-White (1.6)
+ Self efficacy to resist relapse (1.4) + Substance Abuse Treatment Index (1.96)
* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home•** Proportion of social peers during transition period in school/work, treatment, recovery, and inverse of those using alcohol, drugs, fighting, or involved in illegal activity.
In Recovery(62% stable)
Probability of from Recovery to “Using” (+ good)- Freq. Of Use (0.0002) + Initial Weeks in Treatment (1.03)- Illegal Activity (0.70) + Treatment Received During Quarter (2.00)- Age (0.81) + Recovery Environment (r)* (1.45)
+ Positive Social Peers (r) (1.43)
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents
108
In the Community
Using (75% stable)
In Treatment
(48 v 35% stable)
7%
Source: 2006 CSAT AT data set
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)
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents
109
In the Community
Using (75% stable)
In Treatment
(48 v 35% stable)
In Recovery (62% stable)
Source: 2006 CSAT AT data set
26% 19%
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents
Probability of Going to Using vs. Early “Recovery” (+ good)-- Baseline Substance Use Severity (0.74) + Baseline Total Symptom Count (1.46)-- Past Month Substance Problems (0.48) + Times Urine Screened (1.56)-- Substance Frequency (0.48) + Recovery Environment (r)* (1.47)
+ Positive Social Peers (r)** (1.69)
* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home
** Proportion of social peers during transition period in school/work, treatment, recovery, and inverse of those using alcohol, drugs, fighting, or involved in illegal activity.
110
In the Community
Using (75% stable)
In Recovery (62% stable)
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery: Adolescents
* Average days during transition period of participation in self help, AOD free structured activities and inverse of AOD involved activities, violence, victimization, homelessness, fighting at home, alcohol or drug use by others in home
20% 10%
Incarcerated(46% stable)
Probability of Going to Using vs. Early “Recovery” (+ good)+ Recovery Environment (r)* (3.33)
Source: 2006 CSAT AT data set
111
Recovery* by Level of Care
* Recovery defined as no past month use, abuse, or dependence symptoms while living in the community. Percentages in parentheses are the treatment outcome (intake to 12 month change) and the stability of the outcomes (3months to 12 month change) Source: CSAT Adolescent Treatment Outcome Data Set (n-9,276)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pre-Intake Mon 1-3 Mon 4-6 Mon 7-9 Mon 10-12
Per
cent
in P
ast
Mon
th R
ecov
ery* Outpatient (+79%, -1%)
Residential(+143%, +17%)
Post Corr/Res (+220%, +18%)
OP & Resid
Similar
CC better
112
Cumulative Recovery Pattern at 30 months
Source: Dennis et al, forthcoming
37% Sustained Problems
5% Sustained Recovery
19% Intermittent, currently in
recovery
39% Intermittent, currently not in
recovery
The Majority of Adolescents Cycle in and out of Recovery
Findings from the Assertive Continuing Care (ACC)
Experiment
183 adolescents admitted to residential substance abuse treatment
Treated for 30-90 days inpatient, then discharged to outpatient treatment
Random assignment to usual continuing care (UCC) or “assertive continuing care” (ACC)
Over 90% follow-up 3, 6, & 9 months post discharge
Source: Godley et al 2002, 2007
114
Time to Enter Continuing Care and Relapse after Residential Treatment (Age 12-17)
Source: Godley et al., 2004 for relapse and 2000 Statewide Illinois DARTS data for CC admissions
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 10 20 30 40 50 60 70 80 90
Days after Residential (capped at 90)
Per
cen
t of
Clie
nts
Cont.CareAdmis.
Relapse
115
ACC Enhancements
Continue to participate in UCC
Home Visits
Sessions for adolescent, parents, and together
Sessions based on ACRA manual (Godley, Meyers et al., 2001)
Case Management based on ACC manual (Godley et al, 2001) to assist with other issues (e.g., job finding, medication evaluation)
116
Assertive Continuing Care (ACC)Hypotheses
Assertive Continuin
g Care
General Continuin
g Care Adherence
Relative to UCC, ACC will increase General Continuing Care Adherence (GCCA)
Early Abstinence
GCCA (whether due to UCC or ACC) will be associated with higher rates of early abstinence
Sustained Abstinence
Early abstinence will be associated with higher rates of long term abstinence.
117
ACC Improved Adherence
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
118
GCCA Improved Early (0-3 mon.) Abstinence
Source: Godley et al 2002, 2007
24%
36% 38%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any AOD (OR=2.16*) Alcohol (OR=1.94*) Marijuana (OR=1.98*)
Low (0-6/12) GCCA
43%
55% 55%
High (7-12/12) GCCA * p<.05
119
Early (0-3 mon.) Abstinence Improved Sustained (4-9 mon.) Abstinence
Source: Godley et al 2002, 2007
19% 22% 22%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any AOD (OR=11.16*) Alcohol (OR=5.47*) Marijuana (OR=11.15*)
Early(0-3 mon.) Relapse
69%
59%
73%
Early (0-3 mon.) Abstainer * p<.05
120
Post script on ACC
The ACC intervention improved adolescent adherence to the continuing care expectations of both residential and outpatient staff; doing so improved the rates of short term abstinence and, consequently, long term abstinence.
Despite these GAINs, many adolescents in ACC (and more in UCC) did not adhere to continuing care plans.
The ACC1 main findings are published and findings from two subsequent experiments are currently under review
CSAT is currently replicating ACRA/ACC in 32 sites
The ACC manual is being distributed via the website and the CD you have been provided.
121
Need for Tracks, Phases and Continuing Care
Almost a third of the adolescents are “returning” to treatment, 23% for the second or more time
We need to understand what did and did not work the last time and have alternative approaches
We need tracks or phases that recognize that they may need something different or be frustrated by repeating the same material again and again
We need to have better step down and continuing care protocols
122
Recommendations for Further Developments…
Evidenced based interventions can come from both research and practice
Evidence based interventions can improve implementation of treatment and treatment outcomes
Practice based evidence can be used to improve outcomes and is of equal importance
Evidenced based interventions and their outcomes can be replicated in practice
Continuing care and is a key determinant of long term outcomes
123
Recommendations for Further Developments…
We need to target the latter phases of treatment to impact the post-treatment recovery environment and/or social risk groups that are the main predictors of long term relapse
We need to move beyond focusing on acute episodes of care to focus on continuing care and a recovery management paradigm
We need to better understand the impact of involvement in juvenile justice system and how it can be harnessed to help
More work is need on the use of schools as a location for providing primary treatment (they have entrée to the population and appear to be the venue of choice) and recovery-schools to provide support for those coming out of residential treatment
124
Resources for Finding Promising Programs:
Screeners and Other Measures related to adolescents: CSAT TIP 42- http://store.health.org/catalog/productDetails.aspx?ProductID=16979 NIAAA Handbook- pubs.niaaa.nih.gov/publications/Assesing%20Alcohol Drug Strategies Handbook- www.drugstrategies.com/teens GAIN Coordinating Center- www.chestnut.org/li/gain Co-Occurring Center for Excellence- www.coce.samhsa.gov/cod_resources/cb_assessment.htm
Prevention Programs related to adolescents: Substance use- modelprograms.samhsa.gov/ Suicide- www.sprc.org/ Violence- www.sshs.samhsa.gov/ Co-Occurring Cen. for Excel.- http://www.coce.samhsa.gov/cod_resources/cb_prevention.htm Other materials- http://www.health.org/
Treatment Programs related to adolescents: Substance use disorder (SUD)- www.chestnut.org/li/apss/CSAT/protocols Mental disorder (MD) & systems of care-
http://www.mentalhealth.samhsa.gov/cmhs/ChildrensCampaign/practices.asp Traumatic disorders and child maltreatment- www.nctsnet.org Co-Occurring Cen. for Excel.- www.coce.samhsa.gov/cod_resources/cb_treatmentservice.htm