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dc.contributor.authorChenyu Lv
dc.contributor.authorZhi Liu
dc.contributor.authorOfir Turel
dc.contributor.authorQinghua He
dc.date.accessioned2025-12-13T14:09:57Z
dc.date.accessioned2026-05-18T04:59:35Z
dc.date.available2026-05-18T04:59:35Z
dc.date.issued2025-12-13T14:09:57Z
dc.identifier.urihttps://doi.org/10.1057/s41599-025-04843-7
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/22089
dc.description.abstractAbstract Delay discounting significantly influences individuals’ economic decisions, daily habits, and overall physical and mental well-being. The question of whether there are systematic gender-based differences in delay discounting remains controversial. We use a meta-analysis of 109 studies (N = 66,972) to address this question. Our findings underscore a statistically significant tendency for males to exhibit higher discounting rates for future rewards compared to females. Subgroup analyses reveal that these gender disparities are most pronounced among adults, as opposed to children, adolescents, and the elderly. Furthermore, notable gender differences are primarily observed among Asian participants, whereas studies from other regions do not consistently demonstrate significant variations. Importantly, our analysis does not suggest the presence of publication bias. In summary, our meta-analysis confirms that males display a higher propensity to discount future rewards compared to females, contingent on age and geographical region. These insights offer valuable implications for understanding individual differences in economic decision making and shaping interventions tailored to address specific populations’ needs.
dc.publisherSpringer Nature
dc.subject.lccHistory of scholarship and learning. The humanities; Social Sciences
dc.titleUnderstanding gender differences in delay discounting: a systematic review and meta-analysis
dc.typeArticle
dc.description.doi10.1057/s41599-025-04843-7
dc.title.journalHumanities & Social Sciences Communications
dc.identifier.oaioai:doaj.org/journal:f6aab66887b249279e76e5047925ef73


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