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Journal Article

Citation

Wei S, Liu Q, Harrington M, Sun J, Yu H, Han J, Hao M, Wu H, Liu X. Am. J. Drug Alcohol Abuse 2019; ePub(ePub): 1-10.

Affiliation

Department of Psychology , University of Chinese Academy of Sciences , Beijing , China.

Copyright

(Copyright © 2019, Informa - Taylor and Francis Group)

DOI

10.1080/00952990.2019.1608554

PMID

31120769

Abstract

Background: Many experimental studies and theoretical models have tried to explain the multifaceted formation of drug addiction. In most addiction models, social factors are an important component; however, few empirical studies have investigated the social influences on the safe or risky choices of drug-addicted individuals during the abstinence stage. Objectives: To investigate the behavioral patterns of female methamphetamine abstainers under social influence. Methods: Thirty-seven female methamphetamine abstainers (average abstinence time: 8.61 ± 4.75 months) and 40 matched controls performed a gambling task in the presence of peers' choices. We applied both model-free and computational model-based analysis to examine how the decision patterns differed with social influence between the two groups. Results: 1) the choice data from the two groups showed a social influence effect such that participants made more risky choices when others made risky choices; 2) overall, the female methamphetamine abstainers made more risky choices in the social influence task; and 3) in the computational model parameters, the female methamphetamine abstainers exhibited more nonconforming attitudes (with negative other-conferred utility) with respect to peer influence, whereas controls showed higher conformity to peers. Conclusion: Our findings provide the first objective evidence that female methamphetamine abstainers show peer nonconformity. This nonconformist tendency may be a potential behavioral marker to track drug addiction and help to elucidate the mechanisms of decisions made by female methamphetamine abstainers.


Language: en

Keywords

Methamphetamine; addiction; computational modeling; decision making; social conformity; social influence

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