Christine E Sheffer1, Darren R Christensen2, Reid Landes3, Larry P Carter4, Lisa Jackson5, Warren K Bickel6. 1. Department of Community Health and Social Medicine, Sophie Davis School of Biomedical Education, 160 Convent Ave, Harris Hall Suite 400, City College of New York, New York, NY 10031, USA; Department of Health Behavior and Health Education, Fay W. Boozman College of Public Health, USA; Department of Psychiatry, Center for Addiction Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. Electronic address: csheffer@med.cuny.edu. 2. Faculty of Health Sciences, University of Lethbridge, 4401 University Drive West, Lethbridge, AB T1K 3M4, Canada; Department of Psychiatry, Center for Addiction Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. 3. Department of Biostatistics, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. 4. Department of Psychiatry, Center for Addiction Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. 5. Department of Psychiatry, Center for Addiction Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; Center for Clinical Translational Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. 6. Department of Psychiatry, Center for Addiction Research, College of Medicine, 4301 West Markham St, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; Center for Addiction Research, Virginia Tech Carilion Research Institute, 2 Riverside Circle, Roanoke, VA 24016, USA.
Abstract
BACKGROUND: Recent evidence suggests that several dimensions of impulsivity and locus of control are likely to be significant prognostic indicators of relapse. METHOD: One-hundred and thirty-one treatment seeking smokers were enrolled in six weeks of multi-component cognitive-behavioral therapy with eight weeks of nicotine replacement therapy. ANALYSIS: Cox proportional hazard regressions were used to model days to relapse with each of the following: delay discounting of $100, delay discounting of $1000, six subscales of the Barratt Impulsiveness Scale (BIS), Rotter's Locus of Control (RLOC), Fagerstrom's Test for Nicotine Dependence (FTND), and the Perceived Stress Scale (PSS). Hazard ratios for a one standard deviation increase were estimated with 95% confidence intervals for each explanatory variable. Likelihood ratios were used to examine the level of association with days to relapse for different combinations of the explanatory variables while accounting for nicotine dependence and stress level. RESULTS: These analyses found that the $100 delay discounting rate had the strongest association with days to relapse. Further, when discounting rates were combined with the FTND and PSS, the associations remained significant. When the other measures were combined with the FTND and PSS, their associations with relapse non-significant. CONCLUSIONS: These findings indicate that delay discounting is independently associated with relapse and adds to what is already accounted for by nicotine dependence and stress level. They also signify that delay discounting is a productive new target for enhancing treatment for tobacco dependence. Consequently, adding an intervention designed to decrease discounting rates to a comprehensive treatment for tobacco dependence has the potential to decrease relapse rates.
BACKGROUND: Recent evidence suggests that several dimensions of impulsivity and locus of control are likely to be significant prognostic indicators of relapse. METHOD: One-hundred and thirty-one treatment seeking smokers were enrolled in six weeks of multi-component cognitive-behavioral therapy with eight weeks of nicotine replacement therapy. ANALYSIS: Cox proportional hazard regressions were used to model days to relapse with each of the following: delay discounting of $100, delay discounting of $1000, six subscales of the Barratt Impulsiveness Scale (BIS), Rotter's Locus of Control (RLOC), Fagerstrom's Test for Nicotine Dependence (FTND), and the Perceived Stress Scale (PSS). Hazard ratios for a one standard deviation increase were estimated with 95% confidence intervals for each explanatory variable. Likelihood ratios were used to examine the level of association with days to relapse for different combinations of the explanatory variables while accounting for nicotine dependence and stress level. RESULTS: These analyses found that the $100 delay discounting rate had the strongest association with days to relapse. Further, when discounting rates were combined with the FTND and PSS, the associations remained significant. When the other measures were combined with the FTND and PSS, their associations with relapse non-significant. CONCLUSIONS: These findings indicate that delay discounting is independently associated with relapse and adds to what is already accounted for by nicotine dependence and stress level. They also signify that delay discounting is a productive new target for enhancing treatment for tobacco dependence. Consequently, adding an intervention designed to decrease discounting rates to a comprehensive treatment for tobacco dependence has the potential to decrease relapse rates.
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