To our knowledge, this is the first study to date to examine the longer term stability of delay discounting, the causal relationship between delay discounting and smoking, and the evidence for heterogeneity in the relationship between smoking and delay discounting. The findings indicate that delay discounting is more trait-like than state-like across adolescence to young adulthood. Related to its stability across time, delay discounting appears to promote smoking acquisition, but smoking does not significantly alter delay discounting. Finally, delay discounting appears to be elevated in those individuals who progress to a more regular pattern of smoking versus those who do not. In fact, delay discounting is a stronger predictor of smoking status than the pattern of smoking acquisition.
As delay discounting is considered to be an aspect of impulsivity and is relatively stable across adolescence and emerging adulthood, it makes sense that delay discounting would play an etiological role in smoking acquisition, rather than smoking playing an etiological role in impulsive choices measured by delay discounting. These results may help us better understand the dynamic nature between impulsive choices and smoking uptake. Adolescents higher in delay discounting may seek out activities that have more immediate rather than more delayed rewards, such as smoking and substance use. These results may also shed light on why some adolescents choose healthy rewarding behaviors (e.g., physical activity) and others choose unhealthy rewarding behaviors (e.g., smoking) (Audrain-McGovern et al., 2003
; Audrain-McGovern et al., 2006b
). If higher rates of delay discounting contribute to smoking acquisition, then delay discounting may provide a variable by which to screen for smoking vulnerability. Adolescents at higher risk of smoking due to higher delay discounting may be a subgroup to target for more intensive smoking prevention efforts that include novel behavioral components directed toward aspects of impulsivity. Intervention research suggests that impulsive decision making may be moderated by the acquisition of self-control skills. For example, a class-room based behavioral management intervention focused on reducing aggressive (e.g., fighting) and disruptive (e.g., shouting out of turn) behaviors in first and second graders reduced the risk of early onset smoking initiation (age 12), smoking initiation by age 14 years old for boys, and regular smoking in young men (19 - 21 years old) (Kellam and Anthony, 1998
; Kellam et al., 2008a
; Storr et al., 2002
). Proscribed behaviors were met with a team of classmates losing points. Teams received tangible rewards (e.g., classroom activities, stickers, erasers) for their points when no member exhibited the proscribed behaviors during the sessions. The rewards were delivered immediately at first and then delayed to the end of the school day and eventually the end of the school week. Early interventions, such as these may interrupt the development of impulsive behaviors, or reduce their occurrence by bolstering self control skill sets, including delaying gratification.
Delay discounting characterized smoking uptake, but not how individuals progressed along the uptake continuum (average delay discounting scores at baseline: -3.79 for fast adopters versus -4.15 for slow progressors versus -4.58 for nonsmokers). Although not measured in this study, delay discounting may help determine who quits smoking successfully. A recent adolescent smoking cessation study found that adolescents who were not abstinent from smoking at study end (4 weeks) discounted monetary rewards more than those adolescents who were abstinent (Krishnan-Sarin et al., 2007
). In addition, elevated impulsivity measured prior to smoking cessation treatment predicted faster time to relapse in adult smokers (Doran et al., 2004
The higher delay discounting scores of the faster smoking adopters and greater smoking rate is consistent with the cross-sectional research findings showing that individuals who begin using substances early, have greater use, and more poly-substance use tend to have high discount rates (Dom et al., 2006
; Kollins, 2003
). At age 16, fast adopters were over 50% more likely to have used marijuana in the past month compared to slow progressors, and slow progressors did not differ from nonsmokers on academic performance. Higher delay discounting scores may be a marker for early onset of smoking, heavier smoking rate, and other issues such as concurrent substance use and poorer academic performance. Interventions to disrupt one or a range of problematic behaviors associated with smoking (e.g., poor grades, alcohol use) may indirectly impact smoking acquisition, but such an intervention may be more difficult or less effective than modifying a common etiologically important antecedent early, during developmentally malleable periods (Kellam et al., 2008b
). Thus, the prevention of the direct effect of delay discounting on smoking progression and the indirect effect via behaviors related to smoking may have a significant and meaningful impact on smoking uptake.
Those individuals in the slow smoking progressors trajectory had lower delay discounting scores, slower smoking uptake, and lower overall smoking rates. Is this distinct pattern of uptake a reflection of relatively lower delay discounting or is it the loss of factors that protect against smoking over time and an increase in risk factors associated with smoking progression? Members of this trajectory had more peers who smoked and greater alcohol use at baseline compared to nonsmokers. Our previous research has shown that delay discounting can impact smoking progression indirectly through the choice of other behaviors with more immediate rewards that are associated with smoking, such as substance use (Audrain-McGovern et al., 2004b
). Delay discounting may also reflect variability in genetic liability for substance use in general, including smoking. Delay discounting may serve as an endophenotype between gene action and acquisition phenotypes (Audrain-McGovern et al., in press
). These results provide some initial evidence of the predictive validity of delay discounting, which is an important criterion for defining a potential endophenotype. Whether delay discounting meets the criteria for an endophenotype for smoking acquisition specifically and substance abuse more generally awaits further investigation.
As the first investigation of the role of delay discounting in smoking acquisition, the present study has both strengths and limitations. The strengths include multiple measures of delay discounting and smoking across five years and two developmental periods, a good retention rate, the assessment of both directional paths (i.e., the path from delay discounting to smoking and the path from smoking to delay discounting), and the assessment of the developmental heterogeneity in smoking and how it is characterized by delay discounting. Despite these strengths, limitations of the study should be noted. One limitation is that there were insufficient numbers of adolescents in other racial groups to conduct meaningful analyses stratified by race. Another potential limitation of this study is the consent rate. Although the difference in those parents who originally provided consent and those who did not was relatively small and few (Audrain et al., 2002
) caution is warranted in generalizing the results, despite the sample being regionally and locally representative with respect to demographics and smoking behavior (Audrain-McGovern et al., 2004a
). One could also argue that the use of the delay discounting questionnaire rather than a lab task is a limitation, as the questionnaire may be less sensitive. The questionnaire has been shown to correlate highly (r = .82) with lab based measures of delayed discounting (Epstein et al., 2003
). In addition, the variables, including the smoking data are based on self report. Research supports the validity of adolescent self report of smoking behavior as well as other sensitive behaviors in nontreatment contexts where confidentiality is emphasized (Botvin and Botvin, 1992
; Velicer et al., 1992
; Wills and Cleary, 1997
). Finally, the latent growth curve model is based on only three time points (the minimum number needed) given that delay discounting was measured at three time points. Although more than three time points may have offered greater power and stability of the parameter estimates (Muthen and Muthen, 2008
), our model fit the data well, but the results will need to be replicated.
Contrary to previous research in community samples, the present study did not find a significant relationship between ADHD symptoms and smoking (Galera et al., 2005
; Kollins et al., 2005
). We can only speculate that the presence of novelty-seeking and delay discounting in the model dampened the individual effects of inattention and hyperactivity/impulsivity on smoking progression or the discrimination between smoking and nonsmoking trajectories. Likewise, our statistical models considered the effects of ADHD symptom subtypes on changes in smoking across time, rather than an end state smoking outcome. Our previous research has shown that ADHD symptoms have significant effects on the developmental trajectory of nicotine dependence (Rodriguez et al., 2008
Despite the limitations noted above, the present study provides initial evidence of the etiological role of delay discounting in smoking acquisition, irrespective of the onset time point or the rate and magnitude of acquisition. It is important to note that the impact of delay discounting on smoking acquisition was somewhat modest (OR = 1.11) while controlling for other influences on smoking behavior, such as novelty-seeking, ADHD symptoms, and other substance use. These findings help define the average contribution of delay discounting to smoking uptake and also indicate that delay discounting makes a unique contribution beyond important personality constructs and externalizing behaviors. It is important to note that we did not measure conduct disorder or delinquency in this cohort study, which could be considered a limitation. However, recent research suggests that 50% of adolescents with early exposure to alcohol and illicit drugs do not have a history of conduct problems, but are still at an increased risk for substance dependence in adulthood (Odgers et al., in press
). This suggests that other factors besides the traditional problem behaviors may be involved in adolescent substance use, including cigarette smoking. Future research should determine the joint contributions of impulsive decision making, impulsive behavior, and other mood variables (e.g., depression) that may impact decisions about reward and play a role in smoking uptake (Forbes et al., 2007
; Spring et al., 2003
; Windle and Windle, 2001
). The identification of variables that facilitate and buffer the impact of delay discounting on smoking uptake may also inform intervention planning by identifying who may benefit most from an intervention and what variables could be targeted to prevent smoking progression.