BACKGROUND: New approaches are needed to bolster the modest effects of campus drinking prevention programs. However, more definitive research on new paradigms is very expensive, and in the current economic climate, progress can be made by evaluating smaller pilot studies. This study describes one such approach. METHODS:A sample of 18-year-old or older, healthy, drinking freshmen at our university was assigned to 2 groups stratified to be similar on demography, drinking histories, and their level of response (LR) to alcohol. In the spring quarter of the school year, the 32 subjects in each of 2 groups viewed four 45-minute Internet-based videotapes as part of 4 prevention sessions. All 8 modules were based on the same techniques and general content, but the 4 videos for the first group were structured around the validated model of how a low LR affects heavy drinking (the low level of response-based [LRB] Group), with partial mediation by heavier drinking peers, positive alcohol expectancies, and drinking to cope with stress. Videos for the state-of-the-art (SOTA) comparison group did not place the similar prevention messages into the low LR framework. Changes in drinking were evaluated at 3 times: before Module 1, before Module 4, and 1 month after Module 4. RESULTS: Usual and maximum drinks per occasion decreased over time for both high and low LR subjects in both LRB and SOTA groups. As predicted, the low LR students showed greater decreases in the LRB Group, while high LR students showed greater decreases in the more generic SOTA Group. CONCLUSIONS: The results support the hypothesis that tailoring prevention efforts to address specific predisposing factors, such as a low LR, may be associated with beneficial effects on drinking quantity. We hope that these data will encourage additional efforts to validate the low LR-based prevention paradigm and test other interventions that are targeted toward predisposing phenotypes such as impulsivity and negative affect.
RCT Entities:
BACKGROUND: New approaches are needed to bolster the modest effects of campus drinking prevention programs. However, more definitive research on new paradigms is very expensive, and in the current economic climate, progress can be made by evaluating smaller pilot studies. This study describes one such approach. METHODS: A sample of 18-year-old or older, healthy, drinking freshmen at our university was assigned to 2 groups stratified to be similar on demography, drinking histories, and their level of response (LR) to alcohol. In the spring quarter of the school year, the 32 subjects in each of 2 groups viewed four 45-minute Internet-based videotapes as part of 4 prevention sessions. All 8 modules were based on the same techniques and general content, but the 4 videos for the first group were structured around the validated model of how a low LR affects heavy drinking (the low level of response-based [LRB] Group), with partial mediation by heavier drinking peers, positive alcohol expectancies, and drinking to cope with stress. Videos for the state-of-the-art (SOTA) comparison group did not place the similar prevention messages into the low LR framework. Changes in drinking were evaluated at 3 times: before Module 1, before Module 4, and 1 month after Module 4. RESULTS: Usual and maximum drinks per occasion decreased over time for both high and low LR subjects in both LRB and SOTA groups. As predicted, the low LR students showed greater decreases in the LRB Group, while high LR students showed greater decreases in the more generic SOTA Group. CONCLUSIONS: The results support the hypothesis that tailoring prevention efforts to address specific predisposing factors, such as a low LR, may be associated with beneficial effects on drinking quantity. We hope that these data will encourage additional efforts to validate the low LR-based prevention paradigm and test other interventions that are targeted toward predisposing phenotypes such as impulsivity and negative affect.
Authors: Marc A Schuckit; Tom L Smith; Jelger Kalmijn; Ryan S Trim; Erin Cesario; Gretchen Saunders; Courtney Sanchez; Nicole Campbell Journal: J Stud Alcohol Drugs Date: 2012-03 Impact factor: 2.582
Authors: Marc A Schuckit; Tom L Smith; Peyton Clausen; Kim Fromme; Jessica Skidmore; Alexandra Shafir; Jelger Kalmijn Journal: J Stud Alcohol Drugs Date: 2016-01 Impact factor: 2.582
Authors: Marc A Schuckit; Tom L Smith; George P Danko; Kathleen K Bucholz; Arpana Agrawal; Danielle M Dick; John I Nurnberger; John Kramer; Michie Hesselbrock; Gretchen Saunders; Victor Hesselbrock Journal: J Stud Alcohol Drugs Date: 2014-01 Impact factor: 2.582
Authors: Jeanne E Savage; Elizabeth C Long; Sally I-Chun Kuo; Megan E Cooke; Jinni Su; Peter B Barr; Jessica E Salvatore Journal: Policy Insights Behav Brain Sci Date: 2017-08-24
Authors: Martin P Paulus; Marc A Schuckit; Susan F Tapert; Neil J Tolentino; Scott C Matthews; Tom L Smith; Ryan S Trim; Shana A Hall; Alan N Simmons Journal: Biol Psychiatry Date: 2012-05-16 Impact factor: 13.382
Authors: Marc A Schuckit; Tom L Smith; Ryan S Trim; Samuel Kuperman; John Kramer; Victor Hesselbrock; Kathleen K Bucholz; John I Nurnberger; Michie Hesselbrock; Gretchen Saunders Journal: Drug Alcohol Rev Date: 2012-06-18