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.

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Presentation transcript:

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 Demand  13 to 16 million people in the US need treatment  3 million receive care  Online counseling as a low cost compliment of face to face therapy

Unmet Demand  13 to 16 million people in the US need treatment  3 million receive care replacement  Online counseling as a low cost replacement of face to face therapy

Experience with Online SUD Services  Online services  retention in face to face treatment  Online self-help groups  healthcare utilization  Given a choice, most patients maintain online and not face to face contact

Experience with Online SUD Services  Online services  retention  Online self-help groups  healthcare utilization  Given a choice, most patients maintain online and not face to face contact

What Is Online Counseling?  Daily /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

 No need to duplicate features of face to face therapy. Two different modalities.  Different content  Different methods  Same outcomes

Delivery Mode Free net appliance installed in patients homes Provided to both experimental and control group Only experimental group received 4 months of online counseling

Population Served Eagle Butte SD Newark NJ Alexandria VA Washington DC Number of cases Number of experimental cases Referral sourceIndian 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 Hispanic0%3%6%14% Percent American Indian100%0% 9% Percent male40%10%71%50% Average years of education Percent days worked in last 30 days26%12%39%48% Percent currently on probation/parole30%20%100%27% Percent medicated10%20%12%32%

Population Served 1.Poor 2.Under-educated 3.Unemployed 4.Psychiatric problems 5.Involved with criminal justice system

Population Served 1.Poor 2.Under-educated 3.Unemployed 4.Psychiatric problems 5.Involved with criminal justice system Random assignment within each site No difference in ASI components at baseline

Participation in Face to Face Treatment Experimenta lControl Percent of days in treatment 30 days prior to exit45%43% Percent of clients in controlled environment 30 days prior to exit 21% No difference in face to face treatment

Study Attrition  Urine tests available on 62% of subjects Maybe biased

Study Attrition  Urine tests available on 62% of subjects  Exit surveys available on 54% of the subjects Maybe biased

Study Attrition  Urine tests on 62% of subjects  Exit surveys on 54% of the subjects  Either self report or urine test results 75% of subjects

Measurement of Drug Use Drug Tests Self Report P C = P u If only urine tests was available P s If only self report was available (P u +P s )/2 If both urine & self report were available Missing if neither urine or self report was available Combined

Drug Use ExperimentalControl Daily probability of use Number of cases Daily probability of use Number of cases Drug Use Urine tests8.95% %14 Self-reported drug use6.94%247.01%19 Both7.65% %26 Self-reported alcohol use2.36%241.75%19

Drug Use ExperimentalControl Daily probability of use Number of cases Daily probability of use Number of cases Drug Use Urine tests8.95% %14 Self-reported drug use6.94%247.01%19 Both7.65% %26 Self-reported alcohol use2.36%241.75%19 Wide Variations in Results at Different Sites

Conclusions  Patients want computer services & feel entitled to it, once available  It is possible to deliver online treatment to under privileged populations  There is wide variation in delivery of online services by different clinicians

Reduces Drug Use