Literature DB >> 33914568

Reinforcer pathology of internet-related behaviors among college students: Data from six countries.

Samuel F Acuff1, Angelina Pilatti2, Megan Collins3, Leanne Hides3, Nutankumar S Thingujam1, Wen Jia Chai4, Wai Meng Yap1, Ruichong Shuai3, Lee Hogarth3, Adrian J Bravo5, James G Murphy1.   

Abstract

Research has demonstrated that repeated engagement in low-effort behaviors that are associated with immediate reward, such as Internet use, can result in a pathological reinforcement process in which the behavior is increasingly selected over other activities due, in part, to a low availability of alternative activities and to a strong preference for immediate rather than delayed rewards (delay discounting). However, this reinforcer pathology model has not been generalized to other Internet-related behaviors, such as online gaming or smartphone use. Given the widespread availability of these technologies, it is also important to examine whether reinforcer pathology of Internet-related behaviors is culturally universal or culture-specific. The current study examines relations between behavioral economic constructs (Internet demand, delay discounting, and alternative reinforcement) and Internet-related addictive behaviors (harmful Internet use, smartphone use, online gaming, and Internet sexual behavior) in a cross-sectional sample of college students (N = 1,406) from six different countries (Argentina, Australia, India, Malaysia, the United Kingdom, and the United States). Using structural equation modeling, Internet demand was associated with harmful Internet use, smartphone use, and online gaming; delay discounting was associated with harmful smartphone use; and alternative reinforcement was associated with harmful Internet and smartphone use. The models were partially invariant across countries. However, mean levels of behavioral economic variables differed across countries, country-level gross domestic product, person-level income, and sex at birth. Results support behavioral economic theory and highlight the importance of considering both individual and country-level sociocultural contextual factors in models for understanding harmful engagement with Internet-related behaviors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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Year:  2021        PMID: 33914568      PMCID: PMC8553798          DOI: 10.1037/pha0000459

Source DB:  PubMed          Journal:  Exp Clin Psychopharmacol        ISSN: 1064-1297            Impact factor:   3.492


  54 in total

1.  Modeling drug consumption in the clinic using simulation procedures: demand for heroin and cigarettes in opioid-dependent outpatients.

Authors:  E A Jacobs; W K Bickel
Journal:  Exp Clin Psychopharmacol       Date:  1999-11       Impact factor: 3.157

2.  Building blocks of self-control: increased tolerance for delay with bundled rewards.

Authors:  George Ainslie; John R Monterosso
Journal:  J Exp Anal Behav       Date:  2003-01       Impact factor: 2.468

3.  Temporal stability of a cigarette purchase task.

Authors:  Lauren R Few; John Acker; Cara Murphy; James MacKillop
Journal:  Nicotine Tob Res       Date:  2011-12-09       Impact factor: 4.244

4.  Delay Discounting of Video Game Players: Comparison of Time Duration Among Gamers.

Authors:  Frank D Buono; Matthew E Sprong; Daniel P Lloyd; Christopher J Cutter; Destiny M B Printz; Ryan M Sullivan; Brent A Moore
Journal:  Cyberpsychol Behav Soc Netw       Date:  2017-01-24

Review 5.  Contributions from behavioral theories of choice to an analysis of alcohol abuse.

Authors:  R E Vuchinich; J A Tucker
Journal:  J Abnorm Psychol       Date:  1988-05

6.  Sensitivity of hypothetical purchase task indices when studying substance use: A systematic literature review.

Authors:  Ivori Zvorsky; Tyler D Nighbor; Allison N Kurti; Michael DeSarno; Gideon Naudé; Derek D Reed; Stephen T Higgins
Journal:  Prev Med       Date:  2019-08-07       Impact factor: 4.018

7.  Using Demand Curves to Quantify the Reinforcing Value of Social and Solitary Drinking.

Authors:  Samuel F Acuff; Kathryn E Soltis; James G Murphy
Journal:  Alcohol Clin Exp Res       Date:  2020-06-23       Impact factor: 3.455

8.  High-resolution behavioral economic analysis of cigarette demand to inform tax policy.

Authors:  James MacKillop; Lauren R Few; James G Murphy; Lauren M Wier; John Acker; Cara Murphy; Monika Stojek; Maureen Carrigan; Frank Chaloupka
Journal:  Addiction       Date:  2012-07-30       Impact factor: 6.526

9.  A modified exponential behavioral economic demand model to better describe consumption data.

Authors:  Mikhail N Koffarnus; Christopher T Franck; Jeffrey S Stein; Warren K Bickel
Journal:  Exp Clin Psychopharmacol       Date:  2015-08-17       Impact factor: 3.157

10.  Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design.

Authors:  Daria J Kuss; Lydia Harkin; Eiman Kanjo; Joel Billieux
Journal:  Int J Environ Res Public Health       Date:  2018-01-16       Impact factor: 3.390

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  1 in total

Review 1.  Delay Discounting in Established and Proposed Behavioral Addictions: A Systematic Review and Meta-Analysis.

Authors:  Sarah Weinsztok; Sarah Brassard; Iris Balodis; Laura E Martin; Michael Amlung
Journal:  Front Behav Neurosci       Date:  2021-11-26       Impact factor: 3.558

  1 in total

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