Intertemporal Choice Behavior in Emerging Adults and Adults: Effects of Age Interact with Alcohol Use and Family History Status

Abstract

Adults with alcohol use disorders (AUDs) show marked immediate reward selection (or “Now”) bias in intertemporal choice tasks. This Now bias persists long into abstinence, suggesting an irreversible consequence of chronic alcohol abuse or a pre-existing AUD intermediate phenotype. However, some data show substantial Now bias among emerging adults (18–25), regardless of drinking behavior, suggesting age-dependent effects on Now bias. The objectives of the present study were to determine (1) whether Now bias is greater among emerging adults relative to adults, (2) whether any such age effect on Now bias is diminished in sub-clinical heavy alcohol users, and (3) whether having a problem drinking first degree relative is independently associated with elevated Now bias. To achieve these objectives, we used an intertemporal choice task to quantify Now bias in n = 237 healthy participants (ages 18–40; 50% female), and a wide range of non-zero alcohol use, based on the Alcohol Use Disorders Identification Test (AUDIT). We found that among non-heavy drinkers, Now bias inversely correlated with age; this relationship was not present among heavy drinkers. We found no significant relationship between AUDIT score and Now bias among emerging adults, but AUDIT scores and Now bias were positively correlated among 26–40 year olds. Additionally, non-heavy drinking adults who reported a problem drinking first degree relative showed greater Now bias compared to those not reporting familial problem drinking. While not definitive, these findings lend support for elevated Now bias in adulthood as an intermediate phenotype for AUDs. Moreover, non-additive effects of age and heavy drinking on Now bias suggest perturbations in largely common neural circuits in both groups.

The association between parental history and delay discounting among individuals in recovery from addiction

“…Specifically, in a study examining delay discounting among mothers with and without nicotine dependence and their children (Reynolds et al, 2009) smoking mothers and their children had significantly higher rates of discounting compared to non-smoking mothers and their children, suggesting that delay discounting may function as a behavioral risk factor for adolescent cigarette smoking that precedes any significant nicotine use. However, in order to reach firm well-founded conclusions future work assessing the relationship between family history and discounting that aim to understand and explain reasons of inconsistency in findings from the current study and some previous ones of significant association (Dougherty et al, 2014; Smith et al, 2015; VanderBroek et al, 2016) compared to other findings of no association ( Herting et al, 2010; Sanchez-Roige et al, 2016) is needed. In addition, investigating other risk factors that might alter rates of discounting as a function of abstinence such as cessation duration, severity of addiction, and the presence of any ongoing secondary addictions and how they can affect the relationship between rates of discounting, having a family history of addiction and recovery might be beneficial.…”

“…Few studies, however, have examined the association between delay discounting and family history of addiction. Those that have reported mixed results, with some reporting a positive association (Dougherty et al, 2014; Smith et al, 2015; VanderBroek et al, 2016), some reporting a positive association among women but not men (Petry et al, 2002) and some indicating no association (Herting et al, 2010; Sanchez-Roige et al, 2016). Importantly, these studies compared groups of participants with and without a family or parental history of addiction but did not investigate or report the effect of number of parents with addiction in the family on rates of discounting.…”

Neural Systems Underlying Individual Differences in Intertemporal Decision-making

“…high ICR) is associated with alcohol and other substance use disorders. While this was a healthy, non-clinical sample, accumulating evidence suggests that excessive delay discounting may be a pre-existing intermediate phenotype for alcohol use disorders (Anokhin, Grant, Mulligan, & Heath, 2014; Dougherty et al, 2014; James MacKillop, 2013; Smith et al, 2015). Therefore, we probed whether connectivity between these brain networks was associated with aspects of subclinical alcohol use.…”

“…Participants in this sample demonstrated the full range of ICR values (i.e., 0 to 1) with a mean value of 0.62 (Q1=0.35; Q2=0.71; Q3=0.92). As a DD index, ICR has the advantage of very strong internal reliability (Smith et al, 2015; Smith et al, 2016), coupled with the fact that ICR avoids the assumptions of model-based metrics. In contrast, indices derived from temporal discounting models, such as temporal discount rates (“ k ”), are influenced by the assumptions of the particular model employed, and some participants’ data may not conform to these assumptions.…”

“…Participants performed a DD task designed for use in the MRI scanner (Boettiger, Kelley, Mitchell, D’Esposito, & Fields, 2009; Boettiger et al, 2007), and described in detail previously (Altamirano, Fields, D’Esposito, & Boettiger, 2011; Kelm & Boettiger, 2013; Smith & Boettiger, 2012; Smith, Sierra, Oppler, & Boettiger, 2014; Smith, Steel, Parrish, Kelm, & Boettiger, 2015). Participants were given task instructions, completed a short practice, and then completed six blocks of 42 trials each (~8 minutes in length).…”