Gender differences in subjective ratings of affective pictures: Methodological and conceptual implications for research on emotional health

Evidence of gender differences in norms in relation to affective picture databases is controversial when considering emotion from a dimensional perspective, and it is scarce from a categorical perspective. The present study explored the existence of gender differences in norms for the affective pictures included in the MATTER dataset and provided results of such differences in relation to dimensional and categorical ratings for each individual picture, as well as separate classifications of the pictures into discrete emotional categories, for both men and women. This could aid the selection of stimuli in studies that include participants of both genders. Moreover, gender differences in the ratings of each discrete emotional category of pictures were analyzed. The results suggested the presence of a negativity bias in women, who had higher disgust and fear ratings for fear and disgust pictures than men, and also rated erotic pictures as more disgusting than men. There was a positivity bias in men, who rated erotic, fear and disgust pictures as more mirthful, and disgust pictures as more erotic, than did women. Men also rated all categories of pictures as more interesting than did women. These gender differences are consistent with an evolution-based hypothesis, although sociocultural influences cannot be discounted and should be investigated in the future.

Authors

Institutions

Publication Details

Journal
Acta Psychologica
Published
2025-10-20
DOI
https://doi.org/10.1016/j.actpsy.2025.105774
Primary Topic
Emotional Intelligence and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gender differences in subjective ratings of affective pictures: Methodological and conceptual implications for research on emotional health

Elisabeth Ruiz‐Padial
Acta Psychologica
Emotional Intelligence and Performance
article

Gender differences in subjective ratings of affective pictures: Methodological and conceptual implications for research on emotional health

Elisabeth Ruiz‐Padial
article en

Abstract

Evidence of gender differences in norms in relation to affective picture databases is controversial when considering emotion from a dimensional perspective, and it is scarce from a categorical perspective. The present study explored the existence of gender differences in norms for the affective pictures included in the MATTER dataset and provided results of such differences in relation to dimensional and categorical ratings for each individual picture, as well as separate classifications of the pictures into discrete emotional categories, for both men and women. This could aid the selection of stimuli in studies that include participants of both genders. Moreover, gender differences in the ratings of each discrete emotional category of pictures were analyzed. The results suggested the presence of a negativity bias in women, who had higher disgust and fear ratings for fear and disgust pictures than men, and also rated erotic pictures as more disgusting than men. There was a positivity bias in men, who rated erotic, fear and disgust pictures as more mirthful, and disgust pictures as more erotic, than did women. Men also rated all categories of pictures as more interesting than did women. These gender differences are consistent with an evolution-based hypothesis, although sociocultural influences cannot be discounted and should be investigated in the future.

Acta PsychologicaVol. 261
Universidad de Jaén (ES)
Openalex Percentile: Top 65%
Emotional Intelligence and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.