Is it true that negative emotions cause more utilitarian judgements? from the influence of emotion and cognition

心理学 认知 认知心理学 消极情绪 社会心理学 神经科学
作者
Haibo Yang,Chunmei Tang,D Wang
出处
期刊:Cognition & Emotion [Taylor & Francis]
卷期号:37 (7): 1248-1260 被引量:2
标识
DOI:10.1080/02699931.2023.2258572
摘要

ABSTRACTThe affect-as-information (AAI) model proposes that emotions influence the accessibility and value of information (Avramova & Inbar, 2013). Furthermore, according to the dual-process model of moral judgement, emotions and cognition influence moral judgement (Greene, 2007; Greene et al., 2001, 2008); however, there is no direct evidence of a causal chain to support this model's proposition. By using a 3 (emotions: positive vs. neutral vs. negative) × 2 (primed rule: save lives vs. do not kill) between-participants design, we examined two hypotheses in two experiments: supraliminal (Experiment 1) and subliminal (Experiment 2) priming. Our results partially supported the AAI model and confirmed that emotions and cognition independently influence moral judgement. Specifically, the positive emotions group made more utilitarian decisions after being primed with the "save lives" rule and more deontological decisions after being primed with the do not kill rule. However, priming did not affect moral judgement in the negative emotion condition. Further, irrespective of whether priming was done, the negative emotion group mostly made utilitarian decisions. Accordingly, we propose a dynamic dual-process model of moral judgement, that can help clarify how emotion and cognition influence moral judgement.KEYWORDS: Emotionmoral rulesmoral judgementaffect-as-information modeldual-process model of moral judgement Data availability statementThe materials and data files (SPSS) are publicly available on the Open Science Framework (https://osf.io/dp2gc/?view_only=5f0ac588c613451c8326238fc1e9db85).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Natural Science Foundation of Fujian Province, China: [grant No.2021J011010].

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