1. Impact of Online Counseling Farrokh Alemi, Ph.D.

2. Nature of Online Counseling Online motivational counseling Online motivational counseling Counselor initiated scripted email Counselor initiated scripted email Leading question Leading question Motivational Interviewing Motivational Interviewing Urine testing for substance use Urine testing for substance use Administered by the subject’s probation officer Administered by the subject’s probation officer Rare cases the study staff. Rare cases the study staff. Phone counseling Phone counseling When email contact was ineffective When email contact was ineffective

3. Published Details

4. Does it Work?

5. Counselor Training and Proximity Resided in same site as patient Resided in same site as patient Trained on motivational interviewing Trained on motivational interviewing Trained in relapse prevention Trained in relapse prevention Trained in online contacts Trained in online contacts

6. Informed Consent and Recruitment Sites Sites Washington, DC Washington, DC Newark, NJ Newark, NJ Alexandria, VA Alexandria, VA Eagle Butte, SD Eagle Butte, SD Consent Consent Index subject Index subject Family members Family members

7. Description of Subjects Eagle Butte SDNewark NJ Alexandria VAWashington DCOverall Number of cases1030172279 # experimental cases51591039 Referral sourceIndian Reservation clinic Halfway house & family court Probation agency Substance abuse & mental health clinic Varied Percent White0%13%6%18%11% Percent Black0%83%88%59%67% Percent Hispanic0%3%6%14%6% Percent American Indian100%0% 9%15% Percent male40%10%71%50%38% Years of education (St. Dev)12.0 (.9)11.9 (1.9)12.6 (2.1)12.6 (2.2)12.3 (1.9) Percent days worked26%12%39%48%28% Percent in probation30%20%100%27%40% Percent with medication10%20%12%32%20%

8. Random Assignment Clients were randomly assigned to either the control or experimental

9. Data Collection Self report (ASI) Self report (ASI) Baseline and exit Baseline and exit Urine tests Urine tests Probation officer Probation officer Study personnel Study personnel System use System use Computer Computer

10. Days of Use in Last 30 Days prior to Baseline Control (40 subjects) Experimental (39 subjects) Alcohol use to intoxification0.62 (2.73)0.61 (1.93) Opiate (heroin, methadone & other opiates) use 1.57 (6.61)1.23 (5.45) Other sedatives/ hypnotics/tranquilizers use 0.82 (4.75)0.10 (0.64) Cocaine0.25 (1.42)0.77 (3.00) Amphetamines0.07 (0.47)0.02 (0.16) Cannabis0.17 (1.10)0.28 (0.94) More than one drug0.67 (0.47)0.72 (0.60) Total (any drug)4.62 (11.63)4.51 (7.87)

11. Extent of Online Contacts 39 experimental subjects: 39 experimental subjects: 10 (26%) were not reached at all 10 (26%) were not reached at all 12 (31%) reached irregularly (<15 emails) 12 (31%) reached irregularly (<15 emails) 17 (44%) reached regularly (≥15 emails) 17 (44%) reached regularly (≥15 emails) Regular subjects: Regular subjects: 98 communications (stdev = 124 messages) 98 communications (stdev = 124 messages) Over 7.48 months (stdev = 3.17 months) Over 7.48 months (stdev = 3.17 months) One email per 4.19 days (stdev =3.46 days) One email per 4.19 days (stdev =3.46 days) Included periods of relapse Included periods of relapse

12. Attrition Of the 79 subjects recruited Of the 79 subjects recruited 55 completed either 55 completed either Drop out rate of 30% Drop out rate of 30% 29 provided at least 2 urine tests 29 provided at least 2 urine tests Drop out rate of 63% Drop out rate of 63% 43 completed exit interview 43 completed exit interview Drop out rate of 46% Drop out rate of 46%

13. Impact on Drug Use Depends on data used Depends on data used Self report or urine tests Self report or urine tests Depends on length of follow-up Depends on length of follow-up Self report last month Self report last month Urine tests over 3.43 months Urine tests over 3.43 months Method of analysis Method of analysis Percent of positive tests Percent of positive tests Days of use Days of use

14. Method of Analysis of Urine Tests Same percent of positive drug tests but different daily probability of use

15. Calculation of Days of Drug Use from Urine Tests Preceding test values Current test values Test resultsDays drug free Days of drug use Days of follow-up MissingRtRt Not available Missing 0 RmRm RtRt Both tests positive 0m-t RmRm RtRt Both tests negative m-t0 RmRm RtRt One test positive(m-t)/2(m-t)/2m-t

16. Analysis of Number of Tests Study Group Positive Tests Negative tests Total Number of Tests Experimental104757 Control124759

17. Analysis of Days of Drug Use Study Group Drug use days Drug free daysTotal Experimental113.51154.51268 Control43512811716 Chi-square statistic = 130.94 p-value <.001

18. Analysis of Daily Probability of Use Experimental ControlTest of Difference Daily rate Follow -up days # of cases Daily rate Follow -up days # of cases Standard Error z statistic p- value Drug UseDrug Use Urine test 8.95%12681525.35%1716140.0112.410.00 Self- report 6.94%30247.01%30190.070.010.99 Self- report or urine test 7.71%12682914.79%1716260.016.220.00 Self-reported Alcohol Use 2.36%30241.75%30190.040.170.10

19. Does it work? Maybe, depends on how you analyze the data

20. Concerns How should treatment data be analyzed?