Divergence between facial expressions and self-reported emotions: Sex differences in responses to video-based emotional stimuli

Emotional responses involve multiple components, including subjective experience and behavioral expression, which do not always align. Moreover, sex differences in emotional processing appear to vary across emotion types and response modalities. This study investigated sex differences and concordance between self-reported emotional experience and facial expressions elicited by naturalistic emotional video stimuli in a Korean adult sample. One hundred forty-eight healthy adults viewed video clips inducing joy, anxiety, sadness, and neutral states; spontaneous facial expressions were recorded and analyzed using the iMotions automated facial expression analysis software. After watching the stimuli, participants rated their subjective emotional experiences on discrete emotion scales (joy, sadness, disgust, fear/anxiety) and affective dimension scales (valence and arousal). Facial expression measures were summarized as positive and negative expressions. Age effects were statistically controlled for both facial expression and self-rating measures, and non-parametric analyses were conducted on the age-adjusted values because most variables deviated from normality. The video stimuli reliably elicited their intended target emotions in both self-reported ratings and facial expression patterns. Females exhibited stronger positive facial expressions than males during joyful stimuli despite comparable self-reported joy ratings. For anxiety stimuli, females showed higher fear/anxiety ratings and stronger negative facial expressions, whereas for sadness stimuli, females reported higher sadness ratings without corresponding differences in facial expressions. Females also reported higher arousal than males for negative stimuli. Concordance between facial expressions and self-reported ratings varied by emotion and sex, with robust associations for joy across both sexes, weaker or absent associations for sadness, and sex-specific associations for anxiety. These findings demonstrate that sex differences in emotional responding are emotion-specific and component-specific, highlighting partial dissociations between subjective experience and expressive behavior. This study provides culturally specific validation of dynamic video-based emotion paradigms and supports continuous facial expression analysis as an objective complement to self-report measures in Korean populations.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-06-29
DOI
https://doi.org/10.1371/journal.pone.0352759
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Divergence between facial expressions and self-reported emotions: Sex differences in responses to video-based emotional stimuli

Sungsil Ko, Hyungjun Kim, Jiyoun Choi, Sunyoung Choi et al.
PLoS ONE
Emotion and Mood Recognition
article

Divergence between facial expressions and self-reported emotions: Sex differences in responses to video-based emotional stimuli

Sungsil Ko, Hyungjun Kim, Jiyoun Choi, Sunyoung Choi, Changjin Jung, Jieun Kim
article en

Abstract

Emotional responses involve multiple components, including subjective experience and behavioral expression, which do not always align. Moreover, sex differences in emotional processing appear to vary across emotion types and response modalities. This study investigated sex differences and concordance between self-reported emotional experience and facial expressions elicited by naturalistic emotional video stimuli in a Korean adult sample. One hundred forty-eight healthy adults viewed video clips inducing joy, anxiety, sadness, and neutral states; spontaneous facial expressions were recorded and analyzed using the iMotions automated facial expression analysis software. After watching the stimuli, participants rated their subjective emotional experiences on discrete emotion scales (joy, sadness, disgust, fear/anxiety) and affective dimension scales (valence and arousal). Facial expression measures were summarized as positive and negative expressions. Age effects were statistically controlled for both facial expression and self-rating measures, and non-parametric analyses were conducted on the age-adjusted values because most variables deviated from normality. The video stimuli reliably elicited their intended target emotions in both self-reported ratings and facial expression patterns. Females exhibited stronger positive facial expressions than males during joyful stimuli despite comparable self-reported joy ratings. For anxiety stimuli, females showed higher fear/anxiety ratings and stronger negative facial expressions, whereas for sadness stimuli, females reported higher sadness ratings without corresponding differences in facial expressions. Females also reported higher arousal than males for negative stimuli. Concordance between facial expressions and self-reported ratings varied by emotion and sex, with robust associations for joy across both sexes, weaker or absent associations for sadness, and sex-specific associations for anxiety. These findings demonstrate that sex differences in emotional responding are emotion-specific and component-specific, highlighting partial dissociations between subjective experience and expressive behavior. This study provides culturally specific validation of dynamic video-based emotion paradigms and supports continuous facial expression analysis as an objective complement to self-report measures in Korean populations.

PLoS ONEVol. 21(6)
Sookmyung Women's University (KR), Korea Institute of Oriental Medicine (KR)
Sookmyung Women's University, Korea Institute of Oriental Medicine, National Research Council of Science and Technology, Ministry of Science and ICT, South Korea
Gender equality
Openalex Percentile: Top 6%
Emotion and Mood Recognition
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.