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A Behavioral Model for Maintenance of Drug Abstinence DA 017444

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Title: A Behavioral Model for Maintenance of Drug Abstinence DA 017444


1
A Behavioral Model for Maintenance of Drug
AbstinenceDA 017444
Kimberly C. Kirby, Ph.D. Lois A. Benishek ,
Ph.D. James R. McKay, Ph.D. MaryLouise Kerwin ,
Ph.D. A. Thomas McLellan , Ph.D. Tanya
Christoffel, M.Ed. Douglas B. Marlowe , J.D.,
Ph.D Treatment Research Institute and the
University of Pennsylvania Population
Opiate-dependent, cocaine-using adults Setting
Methadone Maintenance Clinic
2
Primary Research Questions
  • Do longer durations of contingency management
    (CM) result in a greater abstinence 2 yrs
    post-tx?
  • Does a longer duration of CM result in increases
    in non-drug using activities?
  • Do increases in the number of non-drug using
    activities predict better long-term drug
    abstinence?
  • Are better long-term outcomes associated with
    more natural contingencies of reinforcement for
    non-drug using activities?

3
Contingency Management
Escalating Schedule of Reinforcement Base value
2.50 3 row bonus 10 Increments 1.25
Pos. urine gt reset 2.50 Max. value 40.00 5
row neg gt return Patients Randomly Assigned
to Usual CM (3 mo) Extended CM (9 mo) Both
Groups then Receive Aftercare for 3 mo 1 lottery
ticket/clean urine
4
Logic Model
Reinforce drug-free urines
Longer-term abstinence less relapse
Increased abstinence during treatment
Contact natural contingencies of reinforcement?
Type?
Type 1
Yes
More likely to relapse
Increase non-drug using activities
Type 2
No
5
Outcome Measures
ComQolComprehensive Quality of Life
Scale Q-LES-QQuality of Life Enjoyment/Satisfacti
on PES Pleasant/Unpleasant Events Life
ChangesLifestyle Changes Questionnaire
6
Cross-Cutting Activities
  • Investigator groups on common themes
  • Similar populations
  • Mediators or moderators of change
  • Similar intervention elements
  • Advising/problem-solving methodological issues
  • Maintaining follow-up
  • Monitoring treatment fidelity
  • Data analysis challenges (e.g., missing data,
    mediating variables)
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