The Neuroticism Extraversion Openness - Five Factor Inventory is extensively utilized in psychological research to quantitatively evaluate personality traits. However, psychological biases may influence test takers to intentionally fabricate responses to present themselves more favorably. This manipulation can compromise the reliability of the questionnaire results. To address this issue, we hypothesized that classifying responses as either honest or fabricated based on the influence of psychological bias could enhance the reliability of the assessment. In this study, electroencephalography data recorded during the response process was used to define information transfer in brain activity while responding by Granger causality, which was used as a feature for a support vector machine to perform a binary classification of responses as honest or fabricated. A validation experiment was conducted with 23 participants under two conditions. In one condition, participants were instructed to manipulate their responses to make them appear more favorable. In the other condition, they were asked to respond honestly. Based on the difference between the two conditions, responses were labeled according to the presence or absence of psychological bias. To evaluate the classification accuracy, we applied leave-one-subject cross-validation and evaluated the generalization performance of the model. The results showed that the accuracy was 0.797, the positive predictive value was 0.853, the negative predictive value was 0.713, the recall was 0.840, the specificity was 0.709, and the F1-score was 0.835.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

A Method for Classifying Fabricated Responses Due to Psychological Biases Using Brain Activity Networks Based on Granger Causality in EEG Responses to the NEO-FFI

  • Yuto Ashikawa,
  • Yosuke Kurihara

摘要

The Neuroticism Extraversion Openness - Five Factor Inventory is extensively utilized in psychological research to quantitatively evaluate personality traits. However, psychological biases may influence test takers to intentionally fabricate responses to present themselves more favorably. This manipulation can compromise the reliability of the questionnaire results. To address this issue, we hypothesized that classifying responses as either honest or fabricated based on the influence of psychological bias could enhance the reliability of the assessment. In this study, electroencephalography data recorded during the response process was used to define information transfer in brain activity while responding by Granger causality, which was used as a feature for a support vector machine to perform a binary classification of responses as honest or fabricated. A validation experiment was conducted with 23 participants under two conditions. In one condition, participants were instructed to manipulate their responses to make them appear more favorable. In the other condition, they were asked to respond honestly. Based on the difference between the two conditions, responses were labeled according to the presence or absence of psychological bias. To evaluate the classification accuracy, we applied leave-one-subject cross-validation and evaluated the generalization performance of the model. The results showed that the accuracy was 0.797, the positive predictive value was 0.853, the negative predictive value was 0.713, the recall was 0.840, the specificity was 0.709, and the F1-score was 0.835.