The relationship between delay discounting and Internet addiction: A systematic review and meta-analysis

Yu-Shian Cheng; Huei-Chen Ko; Cheuk-Kwan Sun; Pin-Yang Yeh

doi:10.1016/j.addbeh.2020.106751

The relationship between delay discounting and Internet addiction: A systematic review and meta-analysis

Addict Behav. 2021 Mar:114:106751. doi: 10.1016/j.addbeh.2020.106751. Epub 2020 Dec 2.

Authors

Yu-Shian Cheng¹, Huei-Chen Ko², Cheuk-Kwan Sun³, Pin-Yang Yeh⁴

Affiliations

¹ Department of Psychiatry, Tsyr-Huey Mental Hospital, Kaohsiung Jen-Ai's Home, Taiwan.
² Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan; Center for Prevention and Treatment of Internet Addiction, Asia University, Taichung, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
³ Department of Emergency Medicine, E-Da Hospital, Kaohsiung, Taiwan; School of Medicine for International Students, I-Shou University, Kaohsiung, Taiwan.
⁴ Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan. Electronic address: PsyYPY@asia.edu.tw.

PMID: 33310692
DOI: 10.1016/j.addbeh.2020.106751

Abstract

Aims: To estimate the difference in delay discounting (DD) between subjects with Internet addiction (IA) and those without as well as to identify significant variables involved in DD.

Methods: Using the keywords related to IA (e.g., "excessive Internet use", "Internet dependence") AND "delayed reward discounting" OR "delay discounting" OR "temporal discounting" OR "delayed gratification" OR time discounting OR intertemporal choice OR impulsive choice, the PubMed, Embase, and PsycINFO databases were searched from inception to June 2020 for English articles with comparison between subjects with IA and those without. Effect sizes were calculated by group means from the k value or area under the curve (AUC). The random-effects models were used.

Results: Fourteen studies in total were eligible for the current meta-analysis that involved 696 subjects with IA (mean age = 22.71) and 2,394 subjects without (mean age = 21.91). Subjects with IA had a steeper DD rate (g = 1.10, 95% CI: 0.57-1.64; p ≤ 0.01) compared with that in those without. Regarding DD data, the difference between k value and AUC was significant (p < 0.01; AUC > k). Additionally, the estimation of DD by the paper-and-pencil task was larger than that by the computerized task (p < 0.01). Significant difference in the DD rate was also noted between subjects with Internet gaming disorder (IGD) and those with unspecified IA (p = 0.00; IGD > IA). The percentage of men and task variables were significantly associated with the DD rate (all p < 0.01), suggesting impaired DD in subjects with IA.

Conclusions: Our results suggested the feasibility of utilizing the DD rate as a therapeutic index for cognitive control in IA. Nevertheless, judicious use is recommended taking into consideration the significant difference between k value and AUC.

Keywords: Decision-making; Delay discounting; Delayed gratification; Internet addiction; Problematic internet use.

Publication types

Meta-Analysis
Review
Systematic Review

MeSH terms

Adult
Delay Discounting*
Humans
Impulsive Behavior
Internet Addiction Disorder
Reward
Young Adult