Impact of Online Impact of Online CounselingCounseling

Farrokh Alemi, Ph.D.Farrokh Alemi, Ph.D.

Nature of Online CounselingNature of Online Counseling

Online motivational counseling Online motivational counseling Counselor initiated scripted emailCounselor 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 Administered by the subject’s probation

officerofficer Rare cases the study staff. Rare cases the study staff.

Phone counseling Phone counseling When email contact was ineffectiveWhen email contact was ineffective

Published DetailsPublished Details

Does it Work?Does it Work?

Counselor Training and Counselor Training and ProximityProximity

Resided in same site as patientResided in same site as patient Trained on motivational Trained on motivational

interviewinginterviewing Trained in relapse preventionTrained in relapse prevention Trained in online contactsTrained in online contacts

Informed Consent and Informed Consent and RecruitmentRecruitment

SitesSites Washington, DCWashington, DC Newark, NJNewark, NJ Alexandria, VAAlexandria, VA Eagle Butte, SD Eagle Butte, SD

ConsentConsent Index subjectIndex subject Family membersFamily members

Description of SubjectsDescription of Subjects

Eagle Butte SD Newark NJ

Alexandria VA Washington DC Overall

Number of cases 10 30 17 22 79

# experimental cases 5 15 9 10 39

Referral source Indian Reservation

clinic

Halfway house &

family court

Probation agency

Substance abuse & mental

health clinic

Varied

Percent White 0% 13% 6% 18% 11%

Percent Black 0% 83% 88% 59% 67%

Percent Hispanic 0% 3% 6% 14% 6%

Percent American Indian 100% 0% 0% 9% 15%

Percent male 40% 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 worked 26% 12% 39% 48% 28%

Percent in probation 30% 20% 100% 27% 40%

Percent with medication 10% 20% 12% 32% 20%

Random AssignmentRandom Assignment

Clients were randomly assigned to Clients were randomly assigned to either the control or experimental either the control or experimental

Data CollectionData Collection

Self report (ASI)Self report (ASI) Baseline and exitBaseline and exit

Urine testsUrine tests Probation officerProbation officer Study personnelStudy personnel

System useSystem use ComputerComputer

Days of Use in Days of Use in Last 30 Days prior to BaselineLast 30 Days prior to Baseline

Control (40 subjects)

Experimental (39 subjects)

Alcohol use to intoxification 0.62 (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)

Cocaine 0.25 (1.42) 0.77 (3.00)

Amphetamines 0.07 (0.47) 0.02 (0.16)

Cannabis 0.17 (1.10) 0.28 (0.94)

More than one drug 0.67 (0.47) 0.72 (0.60)

Total (any drug) 4.62 (11.63) 4.51 (7.87)

Extent of Online ContactsExtent 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 98 communications (stdev = 124

messages) 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 One email per 4.19 days (stdev =3.46

days) days) Included periods of relapseIncluded periods of relapse

AttritionAttrition

Of the 79 subjects recruitedOf the 79 subjects recruited 55 completed either55 completed either

Drop out rate of 30%Drop out rate of 30% 29 provided at least 2 urine tests29 provided at least 2 urine tests

Drop out rate of 63%Drop out rate of 63% 43 completed exit interview43 completed exit interview

Drop out rate of 46%Drop out rate of 46%

Impact on Drug UseImpact on Drug Use

Depends on data usedDepends on data used Self report or urine testsSelf report or urine tests

Depends on length of follow-upDepends on length of follow-up Self report last monthSelf report last month Urine tests over 3.43 monthsUrine tests over 3.43 months

Method of analysisMethod of analysis Percent of positive testsPercent of positive tests Days of useDays of use

Method of Analysis of Urine Method of Analysis of Urine TestsTests

Patient A

+ + -

Patient B

+ + -

Patient A

+ + -

Patient B

+ + -

Patient B

+ + -

Same percent of positive drug tests but different daily probability of use

Calculation of Days of Drug Calculation of Days of Drug Use from Urine TestsUse from Urine Tests

2

tm

Preceding test values

Current test values

Test results

Days drug free

Days of drug use

Days of follow-up

Missing Rt Not available

Missing Missing 0

Rm Rt Both tests positive

0 m-t m-t

Rm Rt Both tests negative

m-t 0 m-t

Rm Rt One test positive

(m-t)/2(m-t)/2 (m-t)/2(m-t)/2 m-t

Analysis of Number of TestsAnalysis of Number of Tests

Study GroupPositive

TestsNegative

testsTotal Number of

Tests

Experimental 10 47 57

Control 12 47 59

Analysis of Days of Drug Analysis of Days of Drug UseUse

Study GroupDrug use

daysDrug free

days Total

Experimental 113.5 1154.5 1268

Control 435 1281 1716

Chi-square statistic = 130.94p-value < .001

Analysis of Daily Probability Analysis of Daily Probability of Useof Use

  Experimental  Control Test of Difference

Daily rate

Follow-up

days # of

casesDaily rate

Follow-up

days# of

casesStandard

Errorz

statisticp-

value

Drug

Use

Urine test

8.95% 1268 15 25.35% 1716 14 0.01 12.41 0.00

Self-report

6.94% 30 24 7.01% 30 19 0.07 0.01 0.99

Self-report or

urine test

7.71% 1268 29 14.79% 1716 26 0.01 6.22 0.00

Self-reported Alcohol Use

2.36% 30 24 1.75% 30 19 0.04 0.17 0.10

Does it work?Does it work?

Maybe, depends on how you Maybe, depends on how you analyze the dataanalyze the data

ConcernsConcerns

How should treatment data be How should treatment data be analyzed?analyzed?