JOURNAL ARTICLE
Understanding decision-making in autistic children and adolescents: Insights from deliberative processes and behavioral economic paradigms.
Published In: Autism: The International Journal of Research & Practice, 2025, v. 29, n. 6. P. 1597 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Ghosn, Farah; Perea, Manuel; Lizarán, Marta; Labusch, Melanie; Moreno-Giménez, Alba; Sahuquillo-Leal, Rosa; Almansa, Belén; Buesa, Julia; Campos, Laura; Pérez, Juan A.; García-Blanco, Ana 3 of 3
Abstract
This article investigates decision-making differences between autistic and non-autistic children and adolescents aged 8–18 using the Ultimatum Game (UG) and Dictator Game (DG), focusing on explicit choices and implicit response times (RTs) alongside executive function (EF) assessments. Findings indicate that autistic participants were less likely to propose selfish (ultra-fair) offers in the DG, a behavior correlated with better organizational EF skills, and exhibited slower RTs when endorsing selfish offers in both games, suggesting a more deliberative decision-making process. Both groups showed similar aversion to unfair offers in the UG, reflecting sensitivity to fairness, but autistic individuals appeared to engage more in sociomoral reasoning when deciding on offers benefiting themselves. These results highlight the nuanced cognitive processes underlying social decision-making in autism and suggest that slower, reflective reasoning may contribute to less selfish and more fairness-oriented behaviors.
Additional Information
- Source:Autism: The International Journal of Research & Practice. 2025/06, Vol. 29, Issue 6, p1597
- Document Type:Article
- Subject Area:Economics
- Publication Date:2025
- ISSN:1362-3613
- DOI:10.1177/13623613251323493
- Accession Number:185255974
- Copyright Statement:Copyright of Autism: The International Journal of Research & Practice is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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