Gender and Accuracy in Decoding Affect Cues: A Meta-Analysis.

Area of Science:

• Psychology
• Social Sciences
• Cognitive Science

Background:

• Gender differences in emotion recognition have been studied for over a century.
• Previous reviews indicate females generally outperform males in decoding affect cues from face, body, and voice.
• This research provides an updated meta-analysis incorporating a larger dataset and broader scope.

Purpose of the Study:

• To update the understanding of gender differences in emotion recognition accuracy.
• To investigate the consistency of this gender difference across various moderators.
• To identify factors that may influence or eliminate the observed gender gap.

Main Methods:

• A comprehensive meta-analysis was conducted, synthesizing 1188 effect sizes from 1011 studies.
• The total sample size included 837,637 participants.
• Moderators examined included sample health status, international location, cue modalities, and other test characteristics.

Main Results:

• A small but statistically significant gender difference favoring females in emotion recognition was confirmed (r = 0.12, d = 0.24).
• This difference was highly consistent across numerous moderators, with minor variations.
• Evidence for publication bias was minimal.
• Only sample health status emerged as a moderator where significant gender differences were not observed.

Conclusions:

• The findings confirm a persistent, albeit small, gender difference in emotion recognition, with females demonstrating higher accuracy.
• The consistency of this effect across diverse conditions underscores its robustness.
• Health status represents a key factor that may mitigate or eliminate gender disparities in affect cue understanding.