Farrokh Alemi, Ph.D., Mary Haack, Ph.D., Susie Nemes, Ph.D., Angela Harge, M.Ed., Heibatollah Baghi,...

Farrokh Alemi, Ph.D., Mary Haack, Ph.D., Susie Nemes, Ph.D., Angela Harge, M.Ed., Heibatollah Baghi, Ph.D. This research was supported by a grant from Robert Wood Johnson Foundation’s Substance Abuse Policy Research Program

Unmet Demand13 to 16 million people in the US need

treatment3 million receive careOnline counseling as a low cost

compliment of face to face therapy

Unmet Demand13 to 16 million people in the US need

treatment3 million receive careOnline counseling as a low cost

replacementreplacement of face to face therapy

Experience with Online SUD ServicesOnline services retention in face to face

treatmentOnline self-help groups healthcare

utilizationGiven a choice, most patients maintain

online and not face to face contact

Experience with Online SUD ServicesOnline services retentionOnline self-help groups healthcare

utilizationGiven a choice, most patients maintain

online and not face to face contact

What Is Online Counseling? Daily email/phone contact

Motivational Interviewing

Weekly relapse prevention assessment On demand peer-to-peer anonymous support Within 24 hours answers to questions Bi-weekly urine tests On demand visits This definition is

different from others

Online counseling Face to face counselingFrequency Near daily Less frequentAvailability On demand By appointmentInitiated by Mostly by provider PatientMethod Motivational interviewing VariesContent Today & tomorrow Varies

No need to duplicate features of face to face therapy. Two different modalities.Different contentDifferent methodsSame outcomes

Delivery ModeFree net appliance installed in patients homesProvided to both experimental and control groupOnly experimental group received 4 months of online counseling

Population ServedEagle Butte

SDNewark

NJ Alexandria

VA Washington

DC

Number of cases 10 30 17 22

Number of experimental cases 5 15 9 10

Referral source Indian Reservation

clinic

Halfway house & drug court

Probation agency

Substance abuse & mental

health clinic

Percent White (not Hispanic origin) 0% 13% 6% 18%

Percent Black (not Hispanic origin) 0% 83% 88% 59%

Percent Hispanic 0% 3% 6% 14%

Percent American Indian 100% 0% 0% 9%

Percent male 40% 10% 71% 50%

Average years of education 12.0 11.9 12.6 12.6

Percent days worked in last 30 days 26% 12% 39% 48%

Percent currently on probation/parole 30% 20% 100% 27%

Percent medicated 10% 20% 12% 32%

Population Served 1. Poor2. Under-educated3. Unemployed4. Psychiatric

problems5. Involved with

criminal justice system

Population Served 1. Poor2. Under-educated3. Unemployed4. Psychiatric

problems5. Involved with

criminal justice system

Random assignmentwithin each

site

No difference in ASI components at baseline

Participation in Face to Face Treatment

Experimental Control

Percent of days in treatment 30 days prior to exit 45% 43%

Percent of clients in controlled environment 30 days prior to exit

21% 21%

No difference in face to face treatment

Study AttritionUrine tests available

on 62% of subjects

Maybe biased

Study AttritionUrine tests available on 62% of subjectsExit surveys available

on 54% of the subjects

Maybe biased

Study AttritionUrine tests on 62% of subjectsExit surveys on 54% of the subjects Either self report or urine test results

75% of subjects

Measurement of Drug Use

TestsLastFirstbetweenDaysofNumber

DaysUseDrugofNumberPu &

30

30 daysLastinUseofDaysP

S

Drug Tests

Self Report

PC =

Pu If only urine tests was available

Ps If only self report was available

(Pu+Ps)/2 If both urine & self report were available

Missing if neither urine or self report was available

Combined

Drug Use

Experimental Control

Daily probability

of useNumber of cases

Daily probability

of use

Number of

cases

Drug Use

Urine tests 8.95% 13 25.35% 14

Self-reported drug use 6.94% 24 7.01% 19

Both 7.65% 29 14.79% 26

Self-reported alcohol use 2.36% 24 1.75% 19

Drug Use

Experimental Control

Daily probability

of useNumber of cases

Daily probability

of use

Number of

cases

Drug Use

Urine tests 8.95% 13 25.35% 14

Self-reported drug use 6.94% 24 7.01% 19

Both 7.65% 29 14.79% 26

Self-reported alcohol use 2.36% 24 1.75% 19

Wide Variations in Results at Different Sites

ConclusionsPatients want computer services & feel

entitled to it, once availableIt is possible to deliver online treatment

to under privileged populationsThere is wide variation in delivery of

online services by different clinicians

Reduces Drug Use