1. 1 Findings from the Pathways to Recovery and Recovery Management Checkups (RMC) Experiments Michael L. Dennis, Ph.D. & Christy K Scott, Ph.D. Chestnut Health Systems Bloomington and Chicago, IL Presentation at the Haymarket Center's 15th Annual Summer Institute On Addictions, Oakbrook Terrace, IL, June 9-11, 2009.. This presentation was supported by funds from NIDA grants no. R13 DA027269, 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 mdennis@chestnut.org or 309-820-3805.www.chestnut.org/li/postersmdennis@chestnut.org.

2. 2 Problem and Purpose Over the past several decades there has been a growing recognition that a subset of substance users suffers from a chronic condition that requires multiple episodes of care over several years. This presentation will present 1.Epidemiological data to illustrate the chronic nature of substance disorders and how it relates to a broader understanding of recovery 2.The results of two experiments designed to improve the ways in which recovery is managed across time and multiple episodes of care.

3. 3 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: 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

4. 4 Alcohol and Other Drug Abuse, Dependence and Problem Use Peaks at Age 20 Source: 2002 NSDUH and Dennis & Scott, 2007, Neumark et al., 2000 0 10 20 30 40 50 60 70 80 90 100 12-1314-1516-1718-2021-2930-3435-4950-64 65+ Other drug or heavy alcohol use Alcohol or Drug Use (AOD) Abuse or Dependence Age Severity Category Over 90% of use and problems start between the ages of 12-20 It takes decades before most recover or die *2002 U.S. Household Population estimated to be 235,143,246 People with drug dependence die an average of 22.5 years sooner than those without a diagnosis

5. 5 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

6. 6 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 OutpatientIntensive Outpatient Short Term Residential Long Term Residential Level of Care Median Length of Stay in Days Half are gone within 8 weeks, less than 25% stay the 90 days recommended by NIDA researchers

7. 7 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% OutpatientIntensive Outpatient Short Term Residential Long Term Residential Level of Care Discharge Status Other Terminated Dropped out Completed Transferred Less than 10% are transferred

8. 8 Multiple Co-occurring Problems are Correlated with Severity and Contribute to Chronicity 0% 20%40%60%80% 100% Health Distress Internal Disorders External Disorders Crime/Violence Criminal Justice System Involvement Dependent (n=1221) Abuse/Other (n=385) 0% 20% 40%60%80% 100% Dependent (n=3135) Abuse/Other (n=2617) Adolescents Adults Source: GAIN Coordinating Center Data Set Adolescents More likely to have externalizing disorders Adults more likely to have internalizing disorders[

9. 9 Nine Year Pathways to Recovery Study (Scott & Dennis) Recruitment: 1995 to 1997 Sample: 1,326 participants from sequential admissions to a stratified sample of 22 treatment units in 12 facilities, administered by 10 agencies on Chicago's west side. Substance:Cocaine (33%), heroin (31%), alcohol (27%), marijuana (7%). Levels of Care: Adult OP, IOP, MTP, HH, STR, LTR Instrument:Augmented version of the Addiction Severity Index (A-ASI) Follow-up:Of those alive and due, follow-up interviews were completed with 94 to 98% in annual interviews out to 9 years; over 80% completed within +/- 1 week of target date. Funding: CSAT grant # T100664, contract # 270-97-7011 NIDA grant 1R01 DA15523

10. 10 Pathways to Recovery Sample Characteristics 0% 20%40%60%80% 100% African American Age 30-49 Female Current CJ Involved Past Year Dependence Prior Treatment Residential Treatment Other Mental Disorders Homeless Physical Health Problems The sample is predominately African American, Middle Age, Female, With Dependence, and Prior Treatment Source: Dennis, Scott, Funk & Foss ( 2005) (n=1,271)

11. 11 People Entering Publicly Funded Treatment Generally Use For Decades P e r c e n t s t i l l u s i n g Years from first use to 1+ years of abstinence 302520151050 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

12. 12 Percent still using 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

13. 13 Percent still using 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% shorter The Sooner They Get The Treatment, The Shorter They Use

14. 14 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

15. 15 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)

16. 16 Source: Scott, Dennis, & Foss (2005) Predictors of Change Also Vary by Direction In the Community Using (53% stable) In Recovery (58% 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)

17. 17 The Likelihood of Sustaining Abstinence Another Year Grows Over Time 36% 66% 86% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 to 12 months1 to 3 years4 to 7 years Duration of Abstinence % Sustaining Abstinence Another Year. After 1 to 3 years of abstinence, 2/3rds will make it another year After 4 years of abstinence, about 86% will make it another year Source: Dennis, Foss & Scott (2007) Only a third of people with 1 to 12 months of abstinence will sustain it another year But even after 7 years of abstinence, about 14% relapse each year

18. 18 Source: Dennis, Foss & Scott (2007) What does recovery look like on average? Duration of Abstinence 1-12 Months 1-3 Years 4-7 Years More social and spiritual support Better mental health Housing and living situations continue to improve Dramatic rise in employment and income Dramatic drop in people living below the poverty line Virtual elimination of illegal activity and illegal income Better housing and living situations Increasing employment and income More clean and sober friends Less illegal activity and incarceration Less homelessness, violence and victimization Less use by others at home, work, and by social peers

19. 19 Sustained Abstinence Also Reduces The Risk of Death Source: Scott, Dennis, Simeone & Funk (forthcoming) - Users/Early Abstainers more likely to die in the next 12 months 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 (Matched on Gender, Race & Age)

20. 20 Other factors related to death rates Death is more likely for those who –Are older –Are engaged in illegal activity –Have chronic health conditions –Spend a lot of time in hospitals –Spend a lot of time in and out of substance abuse treatment Death is less common for those who –Have a greater percent of time abstinent –Have longer periods of continuous abstinence –Get back to treatment sooner after relapse

21. 21 False Negative Rates of Self-Reported Past Week Use vs. Urine by Feedback Condition 0% 5% 10% 15% 20% 25% 30% 35% Any DrugCocaine OpioidsCannabis % False Negative No Feedback Control (n=207) Historical & Urine Feedback (n=201) * Bars connected by a line are not significantly different from each other. Source: Scott, Dennis, & Foss (2007) Historical Feedback Only (n=191) Urine Feedback Only (n=160)

22. 22 Post Script on the Pathways Study There is clearly a subset of people for whom substance use disorders are a chronic condition that last for many years Rather than a single transition, most people cycle through abstinence, relapse, incarceration and treatment 3 to 4 times before reaching a sustained recovery. It is possible to predict the likelihood risk of when people will transition Treatment predicts who transitions from use to recovery and self help group participation predicts who stays in recovery. “Recovery” is broader than abstinence and often takes several years after initial abstinence

23. 23 The Early Re-Intervention (ERI) Experiments (Dennis & Scott) ERI 1ERI 2 RecruitmentRecruited 448 from Community Based Treatment in Chicago in 2000 (84% of eligible recruited) Recruited 446 from Community Based Treatment in Chicago in 2004 (93% of eligible recruited) DesignRandom assignment to Recovery Management Checkups (RMC) or control Follow-UpQuarterly for 2 years (95-97% per wave) Quarterly for 4 years (95 to 97% per wave) Data SourcesGAIN, CEST, Urine, Salvia Staff logs GAIN, CEST, CAI, Neo, CRI, Urine, Staff logs PublicationDennis, Scott & Funk 2003; Scott, Dennis & Foss, 2005 Dennis & Scott (in press); Scott & Dennis, (under review) Funding Source NIDA grant R37-DA11323

24. 24 Sample Characteristics of ERI-1 & -2 Experiments 0% 20%40%60%80% 100% African American Age 30-49 Female Current CJ Involved Past Year Dependence Prior Treatment Residential Treatment Other Mental Disorders Homeless Physical Health Problems ERI 1 (n=448) ERI 2 (n=446) Source: Dennis, Scott & Funk, 2003; Scott & Dennis (under review)

25. 25 Recovery Management Checkups (RMC) in both ERI 1 & 2 included: 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

26. 26 Impact of On-site Urine On False Negative Urines 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% OpiatesMarijuanaCocaineAny Drug Tested ERI 1ERI 2 At 24 months FN were at 19% for any drug Introducing the new protocol in ERI 2 dropped the 24 month FN rate to 3% Source: Scott & Dennis (2009)

27. 27 RMC Protocol Adherence Rate by Experiment 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Follow-up Interview (93 vs. 96%) d=0.18 Treatment Need (30 vs. 44%) d=0.31* Linkage Attendance (75 vs. 99%) d=1.45* Agreed to Assessment (44 vs. 45%) d=0.02 Showed to Assessment (30 vs. 42%) d=0.26* Showed to Treatment (25 vs. 30%) d=0.18* Treatment Engagement (39 vs. 58%) d=0.43* Range of rates by quarter * P(H: RMC1=RMC2)<.05 ERI-1 ERI-2 ERI 2 Generally averaged as well or better than ERI 1 Improved Screening Improved Tx Engagement Quality assurance and transportation assistance reduced the variance Source: Scott & Dennis (2009)

28. 28 ERI-1 Time to Treatment Re-Entry 0%0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 090180270 360450540630 Days to Re-Admission (from 3 month interview) Percent Readmitted 1+ Times 60% ERI-1 RMC* (n=221) 51% ERI-1 OM (n=224) *Cohen's d=+0.22 Wilcoxon-Gehen Statistic (df=1) =5.15, p <.05 630-403 = -200 days Revisions to the protocol Source: Dennis, Scott & Funk, 2003; Scott & Dennis (2009)

29. 29 ERI-2 Time to Treatment Re-Entry 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 090 180 270 360450540 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 (2009)

30. 30 ERI-1: Impact on Outcomes 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% of 630 Days Abstinent (d=0.04) of 7 Subsequent Quarters in Need (d= -0.19) * of 90 Days Abstinent (d= -0.05) of 11 Sx of Abuse/Dependence (d=-0.02) Still in need of Tx (d= -0.21) * Percentage OM RMC * p<.05 79% 33% 80% 21% 44% 79% 27% 79% 21% 34% RMC Broke the Run Less Likely to be in Need of Treatment Months 4-24 Final Interview No effect on Abstinence/Symptoms Source: Dennis, Scott, & Funk, 2003; Scott & Dennis (2009)

31. 31 ERI-2: Impact on Outcomes at 45 Months 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Re-entered Treatment (d=0.22)* of 14 Subsequent Quarters in Need (d= 0.26) * of 1260 Days Abstinent (d= 0.26)*(d= -0.32)* Still in need of Tx at Mon 45 (d= -0.22) * Percentage OMRMC * p<.05 55% 41% 67% 50% 56% 38% Fewer Seq. Quarters in Need 74% More days of abstinent of 180 Days of Treatment 71% 61% RMC Increased Treatment Participation 47% Less likely to be in Need at 45m Source: Scott & Dennis (2009)

32. 32 ERI1&2: Impact Treatment Re-entry by Comorbidity and condition* 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage OMRMC * p<.05 47% 53% 33% Returning to treatment varied by Comorbidity* RMC’s Impact on Treatment Participation was robust across levels of Comorbidity Source: Rush, Dennis, Scott, Castel, & Funk (2008) Substance Use Disorder (SUD) (d=0.23) Substance Use + Internalizing + Externalizing Disorders (d=0.31) Substance Use + Internalizing Disorders (d=0.38) 62% 63% 49%

33. 33 In the Community Using (71% stable) In Treatment (35% stable) In Recovery (76% stable) Incarcerated (60% stable) 3% 18% 8% 15% 9% 16% 27% 4% 33% 5% 17% 2% ERI 1: Impact on Primary Quarterly Pathways to Recovery over 2 years 32% Changed Status in an Average Quarter Again the Probability of Entering Recovery is Higher from Treatment Source: Scott et al 2005, Dennis & Scott, 2007

34. 34 18% In the Community Using (71% stable) In Treatment (35% stable) 8% In Recovery (76% stable) Source: Scott et al 2005, Dennis & Scott, 2007 ERI 1: Impact on Primary Quarterly Pathways to Recovery over 2 years Transition to Tx vs. Continued Use - Freq. of Use (0.7) + Prob. Orient. (1.4) + Desire for Help (1.6) + RMC (3.22) Transition to Recovery vs Continued Use - Freq. of Use (0.7) + Prob. Orient. (1.3) - Dep/Abs Prob (0.7) + Self Efficacy (1.2) - Recovery Env. (0.8) + Self Help Hist (1.2) - Access Barriers (0.8) + per 10 wks Tx (1.2) 8%

35. 35 In the Community Using (75% stable) In Treatment (32% stable) In Recovery (58% stable) Incarcerated (56% stable) 4% 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

36. 36 In the Community Using (75% stable) In Treatment (32% stable) In Recovery (58% stable) 10% 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) + Self Help Act. (1.31) - Tx Resistance (0.79) + Wks Self Help (1.39)

37. 37 Positive Consequences of Early ReAdmission Checkups and Early Readmission to Treatment were associated with: –Less substance use and problems –Shorter periods of time using in the community –More days of abstinence –Longer periods of abstinence –More attendance and engagement in self help activities Above were associated with: –Fewer HIV risk behaviours –Less illegal activity, arrests, and time incarcerated –Fewer mental health problems –Less health care utilization –Less costs to society Source: Scott & Dennis (2009)

38. 38 Post Script on ERI experiments Again, severity was inversely related to returning to treatment on your own and treatment was the key predictor of transitioning to recovery The ERI experiments demonstrate that the cycle of relapse, treatment re-entry and recovery can be shortened through more proactive intervention Working to ensure identification, showing to treatment, and engagement for at least 14 days upon readmission helped to improve outcomes ERI 2 also demonstrated the value of on-site proactive urine testing versus the traditional practice of sending off urine for post interview testing

39. 39 Source: French et al., 2008; Chandler et al., 2009; Capriccioso, 2004 Cost of Substance Abuse Treatment Episode $22,000 / year to incarcerate an adult $30,000/ child-year in foster care $70,000/year to keep a child in detention $750 per night in Detox $1,115 per night in hospital $13,000 per week in intensive care for premature baby $27,000 per robbery $67,000 per assault

40. 40 Investing in Treatment has a Positive Annual Return on Investment (ROI) Substance abuse treatment has been shown to have a ROI of between $1.28 to $7.26 per dollar invested Treatment drug courts have an average ROI of $2.14 to $2.71 per dollar invested Source: Bhati et al., (2008); Ettner et al., (2006)

41. 41 Summary Points Addiction is a chronic condition that can last for decades Recovery is likely Identifying and treating addiction early gets people to recovery faster Monitoring for relapse and early re-intervention reduces use and increases abstinence Getting and staying well from addiction is associated with: –Improved housing, jobs, income, mental and physical health –Reductions in HIV risk behaviors, illegal activity, legal problems, incarceration and death –Reduced costs to society

42. 42 Implications for Health Care Reform Financing for addiction care should ideally be modeled after financing for other chronic conditions This means being more assertive in finding and getting people into treatment initially Expanded treatment capacity to reduce demand Improved step down and continuing care Better linkage to self help and recovery services Several years of post treatment monitoring Teaching self management and monitoring Assertive early re-intervention when people relapse

43. 43 References 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. Capriccioso, R. (2004). Foster care: No cure for mental illness. Connect for Kids. Accessed on 6/3/09 from http://www.connectforkids.org/node/571 http://www.connectforkids.org/node/571 Chandler, R.K., Fletcher, B.W., Volkow, N.D. (2009). Treating drug abuse and addiction in the criminal justice system: Improving public health and safety. Journal American Medical Association, 301(2), 183-190 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., 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. (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., 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. Ettner, S.L., Huang, D., Evans, E., Ash, D.R., Hardy, M., Jourabchi, M., & Hser, Y.I. (2006). Benefit Cost in the California Treatment Outcome Project: Does Substance Abuse Treatment Pay for Itself?. Health Services Research, 41(1), 192-213. 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.http://www.DrugAbuseStatistics.SAMHSA.gov French, M.T., Popovici, I., & Tapsell, L. (2008). The economic costs of substance abuse treatment: Updated estimates of cost bands for program assessment and reimbursement. Journal of Substance Abuse Treatment, 35, 462-469 Neumark, Y.D., Van Etten, M.L., & Anthony, J.C. (2000). Drug dependence and death: Survival analysis of the Baltimore ECA sample from 1981 to 1995. Substance Use and Misuse, 35, 313-327. Office Applied Studies (2002). Analysis of the 2002 National Survey on Drug Use and Health (NSDUH) on line at http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00064.xml. http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00064.xml Office Applied Studies (2002). Analysis of the 2002 Treatment Episode Data Set (TEDS) on line data at http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00056.xml) Office of Applied Studies (2006). Results from the 2005 National Survey on Drug Use and Health: National Findings Rockville, MD: Substance Abuse and Mental Health Services Administration. http://www.oas.samhsa.gov/NSDUH/2k5NSDUH/2k5results.htm#7.3.1 http://www.oas.samhsa.gov/NSDUH/2k5NSDUH/2k5results.htm#7.3.1

44. 44 References Riley, B.B.,, Scott, C.K, & Dennis, M.L. (2008). The effect of recovery management checkups on transitions from substance use to substance abuse treatment and from treatment to recovery. Poster presented at the UCLA Center for Advancing Longitudinal Drug Abuse Research Annual Conference, August 13-15, 2008, Los Angles, CA. www.caldar.org.www.caldar.org Rush, B., Dennis, M.L., Scott, C.K, Castel, S., & Funk, R.R. (2008). The Interaction of Co-Occurring Mental Disorders and Recovery Management Checkusp on Treatment Participation and Recovery. Scott, C. K., & Dennis, M. L. (in press). Results from Two Randomized Clinical Trials evaluating the impact of Quarterly Recovery Management Checkups with Adult Chronic Substance Users. Addiction. Scott, C. K., Dennis, M. L., & Funk, R.R. (2008). Predicting the relative risk of death over 9 years based on treatment completion and duration of abstinence. Poster 119 at the College of Problems on Drug Dependence (CPDD) Annual Meeting, San Juan, PR, June 16, 2008. Available at www.chestnut.org/li/posters. Scott, C. K., Dennis, M. L., Simeone, R., & Funk R. (forthcoming). Predicting the likelihood of death of substance users over 9 years based on baseline risk, treatment and duration of abstinence. Chicago, IL: Chestnut Health Systems. Scott, C. K., Foss, M. A., & Dennis, M. L. (2005). Pathways in the relapse, treatment, and recovery cycle over three years. Journal of Substance Abuse Treatment, 28, S61-S70. Volkow N.D., Fowler J.S., Wang G-J., Hitzemann R., Logan J., Schlyer D., Dewey 5., Wolf A.P. (1993). Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177. Volkow, N.D., Hitzemann R., Wang C-I., Fowler I.S., Wolf A.P., Dewey S.L. (1992). Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190.