Predicting honest behavior based on Eysenck personality traits and gender: an explainable machine learning study using SHAP analysis

Predicting honest behavior based on Eysenck personality traits and gender: an explainable machine learning study using SHAP analysis

IntroductionThis study bridges a critical gap in aviation safety research by examining how Eysenck personality traits (Neuroticism, Psychoticism, Extraversion) and gender predict dishonest behavior in high-risk aviation contexts. While prior studies have focused on the Big Five and HEXACO models in...

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Bibliographic Details
Main Authors: Yu Meng, Zili Peng, Zhitong Zhang, Qiaolin Chen, Hanxi Huang, Yihan Chen, Mengqian Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Psychology
Subjects:
honest behavior
Eysenck personality
gender differences
machine learning
SHAP analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1525606/full
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