1. Abstinence Incentive Effects in Psychosocial Counseling Patients Testing Stimulant Positive vs Negative at Treatment Entry Maxine L. Stitzer Johns Hopkins Univ SOM National Drug Abuse Treatment Clinical Trials Network MIEDAR Study Team

2. Background CTN Motivational Incentives Study Incentive therapies offer reinforcers for therapeutically desirable behavior change Abstinence incentives have a strong evidence-base from small-sample efficacy research across a range of abused substances (stimulants, opiates, alcohol, marijuana) National Drug Abuse Treatment Clinical Trials Network multi-site effectiveness study –8 psychosocial counseling community clinics –N = 415 stimulant abusers; cocaine or methamphetamine

3. Background CTN Motivational Incentives Study “Fishbowl” method offered drawings for prizes based on stimulant-negative urines; max earnings = $400 Random assignment to usual care with or without incentives over 12-week evaluation Prize-based incentives found effective for stimulant abusers enrolled in community drug abuse treatment –Improved retention in psychosocial counseling Petry et al., Arch Gen Psychiat, Oct, 2005 –Reduced stimulant drug use in methadone maintenance Peirce et al. Arch Gen Psychiat, Feb. 2006

4. Background Regression analysis conducted to identify outcome predictors Stimulant urine test result (pos/neg) at study entry emerged as strongest predictor of response to incentive procedure (R 2 =.26)

5. Objective Examine overall impact of intake stimulant urine test result on treatment outcome Determine whether incentive effects differ for those who enter the study with stimulant positive vs negative urines

6. Methods Grouping variable = first study urine stimulant positive vs negative –Stimulant = both cocaine & methamphetamine –Psychosocial counseling patients were new clinic intakes

7. Methods Outcome measures examined A) Study retention - time to last urine sample provided prior to 30-days with no contact B) Percent submitted samples stimulant negative twice weekly data collection Data analysis –Survival (A) –GEE (B) for main effects of group (stim pos/neg) and interaction of study treatments with intake urine

8. Retention Percentage Retained 100 80 60 40 20 0 01 2457911 1210 863 Stimulant Negative (n = 306) Stimulant Positive (n = 108) Study Weeks At study intake: HR =1.71 (1.26-2.31)

9. Retention HR = 1.86 (1.35- 2.56) HR = 1.19 ns Study Week 100 80 60 40 20 0 100 80 60 40 20 0 Stimulant Negative (n = 306) Stimulant Positive (n = 108) Incentive Usual Care Incentive Usual Care 42681012 426 8 10 12 Percentage Retained

10. 26 81012 0 20 40 60 80 100 4 26 810 12 0 100 4 20 80 40 60 Stimulant Negative (n = 306) Stimulant Positive (n = 108) Study Weeks Incentive Usual Care Incentive Usual Care Percentage of Samples Stimulant Negative Stimulant Drug Use Percent submitted samples stimulant negative; missing urines considered missing

11. 100 80 60 40 20 0 2 4 6 8 10 12 100 80 60 40 20 0 2 4 6 8 10 12 Study Week Stimulant Negative (n = 306) Stimulant Positive (n = 108) Incentive Usual Care Incentive Usual Care Stimulant Drug Use Percent submitted samples stimulant negative; missing urines considered positive OR =.95 (0.51-1.77) OR =1.90 (1.4 - 2.6)

12. Summary: Main Effect of Initial Urine Test Result Stimulant positive at study entry confers a poor outcome prognosis –consistent with prior research ( e.g Alterman et al., 1996, 1997; Ehrman et al., 2001; Sofuoglu et a., 2003 )

13. Summary: Interaction of Incentives with Initial Urine Test Result Improved retention in psychosocial counseling only for those stimulant negative at study start –Limited opportunity for stimulant positive to contact reinforcers?

14. Treatment Implications Importance of initial urinalysis results in psychosocial counseling programs Implications for treatment selection –Incentives for counseling patients entering tx stimulant negative –Special treatment (not abstinence incentives) for counseling patients entering tx stimulant positive

15. Acknowledgements NIDA CTN for funding MIEDAR study team for successful conduct of the multi-site study Jessica Peirce for prediction analysis Ken Kolodner and Rui Li for statistical support; Joe Harrison for graphics