Findings from the Pathways to Recovery and Recovery Management Checkups (RMC) Experiments

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. .

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 • Epidemiological data to illustrate the chronic nature of substance disorders and how it relates to a broader understanding of recovery • The results of two experiments designed to improve the ways in which recovery is managed across time and multiple episodes of care.

3. Prolonged Substance Use Injures The Brain: Healing Takes Time Normal levels of brain activity in PET scans show up in yellow to red Normal Reduced brain activity after regular use can be seen even after 10 days of abstinence 10 days of abstinence After 100 days of abstinence, we can see brain activity “starting” to recover 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.

4. Over 90% of use and problems start between the ages of 12-20 It takes decades before most recover or die Alcohol and Other Drug Abuse, Dependence and Problem Use Peaks at Age 20 100 People with drug dependence die an average of 22.5 years sooner than those without a diagnosis 90 80 70 60 Severity Category 50 Other drug or heavy alcohol use 40 30 Alcohol or Drug Use (AOD) Abuse or Dependence 20 10 0 *2002 U.S. Household Population estimated to be 235,143,246 65+ 12-13 14-15 16-17 18-20 21-29 30-34 35-49 50-64 Age Source: 2002 NSDUH and Dennis & Scott, 2007, Neumark et al., 2000

5. Few Get Treatment: 1 in 17 adolescents, 1 in 22 young adults, 1 in 12 adults Treatment Participation Rates Are Low Over 88% of adolescent and young adult treatment and over 50% of adult treatment is publicly funded Much of the private funding is limited to 30 days or less and authorized day by day or week by week Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH

6. The Majority Stay in Tx Less than 90 days 90 Half are gone within 8 weeks, less than 25% stay the 90 days recommended by NIDA researchers 60 52 42 Median Length of Stay in Days 33 30 20 0 Outpatient Intensive Short Term Long Term Outpatient Residential Residential Level of Care 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 .

7. Less Than Half Are Positively Discharged 100% 90% Other 80% 70% Terminated 60% Discharge Status Dropped out 50% 40% Completed 30% 20% Transferred 10% 0% Less than 10% are transferred Outpatient Intensive Short Term Long Term Outpatient Residential Residential Level of Care 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 .

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

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

11. People Entering Publicly Funded Treatment Generally Use For Decades It takes 27 years before half reach 1 or more years of abstinence or die 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percent still using Years from first use to 1+ years of abstinence 0 5 10 15 20 25 30 Source: Dennis et al., 2005

12. The Younger They Start, The Longer They Use 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percent still using Age of First Use Years from first use to 1+ years of abstinence under 15 60% longer 15-20 21+ 0 5 10 15 20 25 30 Source: Dennis et al., 2005

13. The Sooner They Get The Treatment, The Shorter They Use Years to first Treatment Admission 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percent still using 20 or more years Years from first use to 1+ years of abstinence 57% shorter 10 to 19 years 0 to 9 years 0 5 10 15 20 25 30 Source: Dennis et al., 2005

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. The Cyclical Course of Relapse, Incarceration, Treatment and Recovery (Adults) P not the same in both directions 6% 7% 25% 30% 8% 28% 29% 4% 7% 44% 31% 13% Treatment is the most likely path to recovery Over half change status annually Incarcerated (37% stable) In the In Recovery Community (58% stable) Using (53% stable) In Treatment (21% stable) Source: Scott, Dennis, & Foss (2005)

16. Predictors of Change Also Vary by Direction • 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) In the 28% In Recovery Community (58% stable) Using 29% (53% stable) 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) Source: Scott, Dennis, & Foss (2005)

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

18. What does recovery look like on average? Duration of Abstinence 1-12 Months 1-3 Years 4-7 Years • 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 • Virtual elimination of illegal activity and illegal • income • Better housing and living situations • Increasing employment and income • 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 Source: Dennis, Foss & Scott (2007)

19. The Risk of Death goes down with years of sustained abstinence Sustained Abstinence Also ReducesThe Risk of Death Users/Early Abstainers more likely to die in the next 12 months It takes 4 or more years of abstinence for risk to get down to community levels - (Matched on Gender, Race & Age) Source: Scott, Dennis, Simeone & Funk (forthcoming)

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

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. The Early Re-Intervention (ERI) Experiments (Dennis & Scott) Funding Source NIDA grant R37-DA11323

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

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

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

28. 630-403 = -200 days ERI-1 Time to Treatment Re-Entry 100% 90% 80% 70% (n=221) 60% ERI-1 RMC* Percent Readmitted 1+ Times 60% 51% ERI-1 OM (n=224) 50% 40% 30% Revisions to the protocol 20% *Cohen's d=+0.22 10% Wilcoxon-Gehen 0% Statistic (df=1) 630 270 360 450 540 180 90 0 =5.15, p <.05 Days to Re-Admission (from 3 month interview) Source: Dennis, Scott & Funk, 2003; Scott & Dennis (2009)

29. 100% The size of the effect is growing every quarter 90% 80% 70% 630-246 = -384 days 60% 50% 40% 30% 20% 10% 0% 630 270 360 450 540 180 90 0 ERI-2 Time to Treatment Re-Entry Percent Readmitted 1+ Times (n=221) 55% ERI-2 RMC* 37% ERI-2 OM (n=224) *Cohen's d=+0.41 Wilcoxon-Gehen Statistic (df=1) =16.56, p <.0001 Days to Re-Admission (from 3 month interview) Source: Scott & Dennis (2009)

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

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

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

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

34. 8% ERI 1: Impact on Primary Quarterly Pathways to Recovery over 2 years • 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) In the 18% In Recovery Community (76% stable) Using (71% stable) 8% Transition to Tx vs. Continued Use - Freq. of Use (0.7) + Prob. Orient. (1.4) + Desire for Help (1.6) + RMC (3.22) In Treatment (35% stable) Source: Scott et al 2005, Dennis & Scott, 2007

35. 4% 3% 13% 23% 8% 10% 24% 7% 6% 25% 35% 10% Again the Probability of Entering Recovery is Higher from Treatment ERI 2: Average Quarterly Transitions over 3 years 34% Changed Status in an Average Quarter Incarcerated (56% stable) In the In Recovery Community (58% stable) Using (75% stable) In Treatment (32% stable) Source: Riley, Scott & Dennis, 2008

36. ERI 2: Average Quarterly Transitions over 3 years • 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) In the In Recovery Community (58% stable) Using (75% stable) 25% 35% 10% 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) In Treatment (32% stable) Source: Riley, Scott & Dennis, 2008

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. 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. Cost of Substance Abuse Treatment Episode • $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 $70,000/year to keep a child in detention $22,000 / year to incarcerate an adult $30,000/ child-year in foster care Source: French et al., 2008; Chandler et al., 2009; Capriccioso, 2004

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. 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. 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. 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 • 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. • 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 theBaltimore 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 . • 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

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 . • 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.