Literature DB >> 19446407

Temporal horizon: modulation by smoking status and gender.

Bryan A Jones1, Reid D Landes, Richard Yi, Warren K Bickel.   

Abstract

Recently, delay discounting has been argued to be conceptually consistent with the notion of temporal horizon [Bickel, W.K., Yi, R., Kowal, B.P., Gatchalian, K.M., 2008. Cigarette smokers discount past and future rewards symmetrically and more than controls: is discounting a measure of impulsivity? Drug Alcohol Depend. 96, 256-262]. Temporal horizon refers to the temporal distance over which behavioral events or objects can influence behavior. Here we examine the results on two putative measures of temporal horizon, future time perspective (FTP) and delay discounting, collected over three separate studies (n=227), to determine the influence of smoking and gender on temporal horizon. By comparing the results on these temporal horizon measures we address our population of interest: women who smoke. One of the measures of FTP indicates that smoking women have a shorter temporal horizon than their nonsmoking counterparts. Additionally, the story completion measures of FTP are positively correlated with delay discounting. In contrast, results of delay discounting measures showed no difference between smoking women and nonsmoking women, while results of delay discounting measures indicated smoking men have a shorter temporal horizon than non-smoking men. Additionally, the results of the FTP story completion measure indicated that lower third income earners had a shortened temporal horizon compared to upper third income earners. A possible explanation for these results is explored, and the implications of the modulation of temporal horizon by gender and smoking are discussed.

Entities:  

Mesh:

Year:  2009        PMID: 19446407      PMCID: PMC2732767          DOI: 10.1016/j.drugalcdep.2009.04.001

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  33 in total

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Authors:  J L Evenden
Journal:  Psychopharmacology (Berl)       Date:  1999-10       Impact factor: 4.530

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3.  Working class matters: socioeconomic disadvantage, race/ethnicity, gender, and smoking in NHIS 2000.

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4.  Future time perspective in schizophrenia.

Authors:  M WALLACE
Journal:  J Abnorm Psychol       Date:  1956-03

Review 5.  A review of delay-discounting research with humans: relations to drug use and gambling.

Authors:  Brady Reynolds
Journal:  Behav Pharmacol       Date:  2006-12       Impact factor: 2.293

6.  Moderate drug use and delay discounting: a comparison of heavy, light, and never smokers.

Authors:  Matthew W Johnson; Warren K Bickel; Forest Baker
Journal:  Exp Clin Psychopharmacol       Date:  2007-04       Impact factor: 3.157

7.  Shortened time horizons and insensitivity to future consequences in heroin addicts.

Authors:  N M Petry; W K Bickel; M Arnett
Journal:  Addiction       Date:  1998-05       Impact factor: 6.526

8.  Gender differences in factors that influence time spent planning for retirement.

Authors:  Joy M Jacobs-Lawson; Douglas A Hershey; Kirstan A Neukam
Journal:  J Women Aging       Date:  2004

9.  Do pretty women inspire men to discount the future?

Authors:  Margo Wilson; Martin Daly
Journal:  Proc Biol Sci       Date:  2004-05-07       Impact factor: 5.349

10.  Gender differences in the comorbidity of smoking behavior and major depression.

Authors:  Mathilde M Husky; Carolyn M Mazure; Prashni Paliwal; Sherry A McKee
Journal:  Drug Alcohol Depend       Date:  2007-09-11       Impact factor: 4.492

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  25 in total

1.  Predictors of delay discounting among smokers: education level and a Utility Measure of Cigarette Reinforcement Efficacy are better predictors than demographics, smoking characteristics, executive functioning, impulsivity, or time perception.

Authors:  A George Wilson; Christopher T Franck; E Terry Mueller; Reid D Landes; Benjamin P Kowal; Richard Yi; Warren K Bickel
Journal:  Addict Behav       Date:  2015-01-22       Impact factor: 3.913

2.  Individual differences in discount rate are associated with demand for self-administered cocaine, but not sucrose.

Authors:  Mikhail N Koffarnus; James H Woods
Journal:  Addict Biol       Date:  2011-08-04       Impact factor: 4.280

3.  Examining educational attainment, prepregnancy smoking rate, and delay discounting as predictors of spontaneous quitting among pregnant smokers.

Authors:  Thomas J White; Ryan Redner; Joan M Skelly; Stephen T Higgins
Journal:  Exp Clin Psychopharmacol       Date:  2014-07-28       Impact factor: 3.157

4.  Differences in delay discounting between smokers and nonsmokers remain when both rewards are delayed.

Authors:  Suzanne H Mitchell; Vanessa B Wilson
Journal:  Psychopharmacology (Berl)       Date:  2011-10-08       Impact factor: 4.530

5.  Delay discounting predicts adolescent substance abuse treatment outcome.

Authors:  Catherine Stanger; Stacy R Ryan; Hongyun Fu; Reid D Landes; Bryan A Jones; Warren K Bickel; Alan J Budney
Journal:  Exp Clin Psychopharmacol       Date:  2011-12-19       Impact factor: 3.157

6.  Test-retest reliability and gender differences in the sexual discounting task among cocaine-dependent individuals.

Authors:  Matthew W Johnson; Natalie R Bruner
Journal:  Exp Clin Psychopharmacol       Date:  2013-07-08       Impact factor: 3.157

7.  Delayed reward discounting and addictive behavior: a meta-analysis.

Authors:  James MacKillop; Michael T Amlung; Lauren R Few; Lara A Ray; Lawrence H Sweet; Marcus R Munafò
Journal:  Psychopharmacology (Berl)       Date:  2011-03-04       Impact factor: 4.530

8.  Sex differences in time perception during smoking abstinence.

Authors:  Rebecca L Ashare; Joseph W Kable
Journal:  Nicotine Tob Res       Date:  2015-04       Impact factor: 4.244

9.  Educational disadvantage and cigarette smoking during pregnancy.

Authors:  Stephen T Higgins; Sarah H Heil; Gary J Badger; Joan M Skelly; Laura J Solomon; Ira M Bernstein
Journal:  Drug Alcohol Depend       Date:  2009-05-12       Impact factor: 4.492

10.  Alcohol-dependent individuals discount sex at higher rates than controls.

Authors:  David P Jarmolowicz; Warren K Bickel; Kirstin M Gatchalian
Journal:  Drug Alcohol Depend       Date:  2013-01-09       Impact factor: 4.492

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