The Associations between Discrete Emotions and Political Learning: A Cross-Disciplinary Systematic Review and Meta-Analysis

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Bibliographic Details
Title: The Associations between Discrete Emotions and Political Learning: A Cross-Disciplinary Systematic Review and Meta-Analysis
Language: English
Authors: Elisabeth Graf (ORCID 0000-0002-9856-6189), Johanna L. Donath (ORCID 0000-0002-6692-5300), Elouise Botes (ORCID 0000-0003-4952-8386), Martin Voracek (ORCID 0000-0001-6109-6155), Thomas Goetz (ORCID 0000-0002-8908-2166)
Source: Educational Psychology Review. 2024 36(3).
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 34
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Psychological Patterns, Emotional Development, Political Influences, Political Socialization, Emotional Response, Anxiety, Positive Attitudes, Association (Psychology)
DOI: 10.1007/s10648-024-09893-y
ISSN: 1040-726X
1573-336X
Abstract: In recent decades, researchers' interest in the role of emotions in individual political learning has grown. However, it is still unclear whether and how discrete emotions are associated with political learning. Through a cross-disciplinary systematic review and multilevel meta-analysis, we reviewed which discrete emotions have been analyzed in the context of political learning so far and meta-analytically synthesized how these emotions relate to political learning. We addressed this question by synthesizing associations between discrete emotions and various aspects of learning about political matters, such as political attention, information seeking, discussions, knowledge, and knowledge gain. The final dataset included 66 publications with 486 effect sizes, involving more than 100,000 participants. Most of the effect sizes were based on negative-activating emotions (65%; mainly anxiety, 32%, and anger, 19%) and positive-activating emotions (32%; mainly enthusiasm, 15%), while studies on positive-deactivating emotions (e.g., contentment) and negative-deactivating emotions (e.g., sadness) are largely lacking. We uncovered small positive associations (r = 0.05 to 0.13) for activating emotions, of both negative (especially anger) and positive valence (e.g., enthusiasm, only in cross-sectional designs), but no associations for negative-deactivating emotions. We discuss theoretical implications and recommend future research to include previously unconsidered emotions in order to extend existing findings.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1430319
Database: ERIC
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