Elected by the face? Facial impressions of honesty and competence made under suboptimal conditions predict voting intentions
Rapid judgments based on political candidates' facial features often predict electoral outcomes. Building on this, we explored how facial impressions of honesty and competence—formed under suboptimal processing conditions—predict voting intentions for actual political candidates. In this study, 484 participants (Colombians: 199; Peruvians: 285; male: 30.2%) were exposed to candidate faces from Colombia and Peru under time constraints (33 ms or 100 ms). Participants rated these faces on honesty and competence and subsequently indicated their likelihood of voting for each candidate. Our findings demonstrate that while rapid facial impressions predict voting preferences overall, this effect is strongly amplified when candidates are recognized from one's own country, whereas for foreign candidates, the relationship remains minimal or disappears. Crucially, because voting intentions were evaluated during subsequent unconstrained viewing, these rapid impressions interact with full-viewing processing rather than acting in complete isolation. By utilizing real candidate photographs, this study confirms that rapid facial impressions align with electoral preferences in naturalistic settings, operating through an integrated process where familiar faces instantly retrieve pre-existing political attitudes.
Authors
- William Jiménez‐Leal (ORCID: https://orcid.org/0000-0002-8824-5269)
- Jaume Rosselló (ORCID: https://orcid.org/0000-0003-4010-7868)
- Sergio Barbosa (ORCID: https://orcid.org/0000-0003-1989-158X)
- Javier Villacampa (ORCID: https://orcid.org/0000-0001-9971-9004)
- Antonio Olivera‐La Rosa (ORCID: https://orcid.org/0000-0001-7637-8518)
- Guido B. Corradi (ORCID: https://orcid.org/0000-0001-9163-6829)
- Gonzalo Luna-Cortés (ORCID: https://orcid.org/0000-0002-6386-7483)
- Sissy Delgado-Pacheco
Publication Details
- Published
- 2026-10-30
- DOI
- https://doi.org/10.31234/osf.io/v8utw_v3
- Primary Topic
- Face Recognition and Perception
- Type
- preprint