Steep delay discounting and addictive behavior: a meta-analysis of continuous associations

Abstract

Aims To synthesize continuous associations between delayed reward discounting (DRD) and both addiction severity and quantity-frequency (QF); to examine moderators of these relationships; and to investigate publication bias. Methods Meta-analysis of published studies examining continuous associations between DRD and addictive behaviors. Published, peer-reviewed studies on addictive behaviors (alcohol, tobacco, cannabis, stimulants, opiates, and gambling) were identified via PubMed, MEDLINE, and PsycInfo. Studies were restricted to DRD measures of monetary gains. Random effects meta-analysis was conducted using Pearson’s r as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger’s tests, meta-regression of publication year and effect size, and imputation of missing studies. Results The primary meta-analysis revealed a small magnitude effect size that was highly significant (r = 0.14, p < 10−14). Significantly larger effect sizes were observed for studies examining severity compared with QF (p = 0.01), but not between the type of addictive behavior (p = 0.30) or DRD assessment (p = 0.90). Indices of publication bias suggested a modest impact of unpublished findings. Conclusions Delayed reward discounting is robustly associated with continuous measures of addiction severity and quantity-frequency. This relation is generally robust across type of addictive behavior and delayed reward discounting assessment modality.

Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry

“…Phenotypic correlations between DD and both ADHD and drug abuse were already well established 4,20 ; we showed, for the first time, that they are also genetically correlated. Furthermore, we identified less intuitive genetic correlations between DD and both schizophrenia and MDD.…”

“…--Delay discounting (DD) is a fundamental component of impulse control 1 and is exaggerated in patients with diseases including attention-deficit/hyperactivity disorder (ADHD) 3 , substance use disorders 4 and obesity 5 . DD is included in the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC) initiative 6 , which focuses on psychiatric disorders as extremes of normal tendencies, based on a biological understanding of behavior.…”

Age and impulsive behavior in drug addiction: A review of past research and future directions

“…Alcohol dependence has been related to higher delay discounting rates in young-to-middle adulthood (Petry, 2001; Vuchinich & Simpson, 1998); although Kirby & Petry (2004) revealed no significant difference in delay discounting between alcohol users and controls. A significant association of delay discounting with different tobacco outcomes has been substantiated in the literature, including tobacco use frequency and quantity (Amlung et al, 2017; Ohmura, Takahashi, & Kitamura, 2005; with some exceptions, e.g., Sweitzer et al, 2008), and nicotine dependence (Amlung & MacKillop, 2014; Mackillop & Tidey, 2011; Sweitzer et al, 2008). Opioid use was also related to delay discounting, with heroin users demonstrating significantly higher delay discounting rates than non-users (Kirby et al, 1999; Madden et al, 1997; MacKillop et al, 2011).…”

“…When given a choice between an immediate smaller reward and a later larger reward, drug users tend to prefer an immediate smaller reward more over a later larger reward than non-drug users (e.g., Kirby et al, 1999; Bickel et al, 1999; Petry, 2001; Kirby & Petry, 2004; MacKillop et al, 2011). Longitudinal studies have identified delay discounting as a significant predictor for the development of addictive behaviors (Anokhin et al, 2011; Fernie et al, 2013; Khurana et al, 2013) and treatment response (Amlung et al, 2017). This demonstrates the importance of delay discounting in the trajectory of addiction.…”

Differential relations between delay discounting and distress tolerance as a function of opportunity cost and alcohol use.

“…These results may be due to the fact that effect sizes for associations between discounting and severity of drug use are smaller than those typically found in comparisons of clinical populations to -non (Amlung, Vedelago, Acker, Balodis, & MacKillop, 2017); and thus the size of our relatively sub-clinical sample may not have been large enough to detect these particular associations. Finally, because problematic drug use is highly comorbid with other psychiatric conditions (Grant et al, 2015), our sample probably differed in other ways that impacted discounting (e.g., higher education).…”