Classification of Participants Based on Increase–Decrease Rate Model of Reaction Time to Personality Trait Words
by
Kouhei Matsuda 1,*
and Emi Sato 2
Kouhei Matsuda 1,* and Emi Sato 2
1
Department of Human Welfare, Tohoku Bunkyo College, Yamagata 990-2316, Japan
2
Department of Business Administration, Tokyo Fuji University, Tokyo 169-0075, Japan
*
Author to whom correspondence should be addressed.
Behav. Sci. 2019, 9(12), 155; https://doi.org/10.3390/bs9120155
Received: 29 October 2019 / Revised: 6 December 2019 / Accepted: 9 December 2019 / Published: 14 December 2019
(This article belongs to the Special Issue XVI European Congress of Psychology)
In this experiment, we tried to measure personality by reaction time (RT) to stimuli of personality trait words. There were interindividual and intraindividual differences in the factors that caused the reaction time to fluctuate. The intraindividual differences for personality trait words were caused by changes due to circumstances for the same participant. The increased stimulus reaction time (sRT) model for simple reaction time was used as an index to indicate personality traits. As a result, participants could be classified into two major hierarchical clusters. The participants in Cluster 1 showed innovative dominance. The participants in Cluster 2 were obedient and conservative. The independent variable was measured by the physiological index using sRT for classify the participants. Participants in Cluster 2 had a reduced stress response to the experiment and showed a tendency to be compliant. Moreover, immediately after the RT measurement session with a laptop computer started, participants in Cluster 1 showed decreased HEG and increased amylase values and had a somewhat negative attitude. The physiological dependent variable were measured by using salivary amylase and hemoencephalography (HEG). And, the psychological dependent variable was the Big Five personality inventory. All of them ware using to verify the participant’s classification. Participants in Cluster 2 had significantly higher conscientiousness than those in Cluster 1. Therefore, we suggest that it is possible to classify personality traits from RT by using sRT based on intraindividual differences.
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Keywords:
personality; reaction time; trait words; variation rate; cluster analysis
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MDPI and ACS Style
Matsuda, K.; Sato, E. Classification of Participants Based on Increase–Decrease Rate Model of Reaction Time to Personality Trait Words. Behav. Sci. 2019, 9, 155.
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