INTRODUCTION: Understanding factors that render some individuals more vulnerable to smoking relapse during the early stages of a quit attempt is critical to tailoring treatment efforts. Development of laboratory models of relapse can provide a framework for identifying underlying mechanisms that may contribute to vulnerability. Here, we explored predictors of abstinence in a novel incentive-based model of relapse. METHODS: Fifty-six nontreatment seeking daily smokers completed several nicotine dependence measures prior to participating in a 1-week abstinence incentive test. During the abstinence procedure, participants earned monetary reinforcement for each biochemically verified day of abstinence according to a descending schedule of reinforcement. RESULTS: Compliance with the procedure was excellent. All but 3 participants were able to initiate abstinence; nearly 70% lapsed as incentives were reduced. Scores on the Fagerström Test for Nicotine Dependence (FTND), number of cigarettes smoked per day, and self-reported craving on the first day of abstinence each independently predicted time to lapse. The single item of time to first cigarette in the morning on the FTND significantly predicted time to lapse, even when controlling for other significant predictors just listed. The Nicotine Dependence Syndrome Scale (NDSS) and Wisconsin Inventory of Smoking Dependence Motives did not predict lapse, but the NDSS did predict reinitiation of abstinence among those experiencing an initial lapse. CONCLUSIONS: These findings partially replicate those of previous full-scale clinical trials and support the feasibility and validity of an incentive-based model of relapse. The time-limited and laboratory-based nature of this model has the potential to further investigations of underlying mechanisms contributing to relapse.
INTRODUCTION: Understanding factors that render some individuals more vulnerable to smoking relapse during the early stages of a quit attempt is critical to tailoring treatment efforts. Development of laboratory models of relapse can provide a framework for identifying underlying mechanisms that may contribute to vulnerability. Here, we explored predictors of abstinence in a novel incentive-based model of relapse. METHODS: Fifty-six nontreatment seeking daily smokers completed several nicotine dependence measures prior to participating in a 1-week abstinence incentive test. During the abstinence procedure, participants earned monetary reinforcement for each biochemically verified day of abstinence according to a descending schedule of reinforcement. RESULTS: Compliance with the procedure was excellent. All but 3 participants were able to initiate abstinence; nearly 70% lapsed as incentives were reduced. Scores on the Fagerström Test for Nicotine Dependence (FTND), number of cigarettes smoked per day, and self-reported craving on the first day of abstinence each independently predicted time to lapse. The single item of time to first cigarette in the morning on the FTND significantly predicted time to lapse, even when controlling for other significant predictors just listed. The Nicotine Dependence Syndrome Scale (NDSS) and Wisconsin Inventory of Smoking Dependence Motives did not predict lapse, but the NDSS did predict reinitiation of abstinence among those experiencing an initial lapse. CONCLUSIONS: These findings partially replicate those of previous full-scale clinical trials and support the feasibility and validity of an incentive-based model of relapse. The time-limited and laboratory-based nature of this model has the potential to further investigations of underlying mechanisms contributing to relapse.
Authors: Saul Shiffman; Deborah M Scharf; William G Shadel; Chad J Gwaltney; Qianyu Dang; Stephanie M Paton; Duncan B Clark Journal: J Consult Clin Psychol Date: 2006-04
Authors: Lynne Dawkins; Jane H Powell; Robert West; John Powell; Alan Pickering Journal: Psychopharmacology (Berl) Date: 2006-10-18 Impact factor: 4.530
Authors: James Loughead; E Paul Wileyto; Kosha Ruparel; Mary Falcone; Ryan Hopson; Ruben Gur; Caryn Lerman Journal: Neuropsychopharmacology Date: 2014-12-03 Impact factor: 7.853
Authors: Amanda R Mathew; Bryan W Heckman; Brett Froeliger; Michael E Saladin; Richard A Brown; Brian Hitsman; Matthew J Carpenter Journal: Exp Clin Psychopharmacol Date: 2018-12-27 Impact factor: 3.157
Authors: Tracy T Smith; Joseph S Koopmeiners; Katelyn M Tessier; Esa M Davis; Cynthia A Conklin; Rachel L Denlinger-Apte; Tonya Lane; Sharon E Murphy; Jennifer W Tidey; Dorothy K Hatsukami; Eric C Donny Journal: Am J Prev Med Date: 2019-10 Impact factor: 5.043
Authors: Cynthia A Conklin; Craig S Parzynski; Ronald P Salkeld; Kenneth A Perkins; Carolyn A Fonte Journal: Exp Clin Psychopharmacol Date: 2012-08-13 Impact factor: 3.157