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

Addiction. 2017 Jan;112(1):51-62. doi: 10.1111/add.13535. Epub 2016 Sep 1.


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 Indices of publication bias suggested a modest impact of unpublished findings.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 associated robustly 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.

Keywords: Addiction; behavioral economics; delayed reward discounting; meta-analysis; publication bias; quantity-frequency; severity.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Behavior, Addictive / physiopathology*
  • Behavior, Addictive / psychology*
  • Delay Discounting / physiology*
  • Humans
  • Publication Bias
  • Reward*
  • Severity of Illness Index