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Exploratory Machine Learning Modeling of Adaptive and Maladaptive Personality Traits from Passively Sensed Behavior.


ABSTRACT: Continuous passive sensing of daily behavior from mobile devices has the potential to identify behavioral patterns associated with different aspects of human characteristics. This paper presents novel analytic approaches to extract and understand these behavioral patterns and their impact on predicting adaptive and maladaptive personality traits. Our machine learning analysis extends previous research by showing that both adaptive and maladaptive traits are associated with passively sensed behavior providing initial evidence for the utility of this type of data to study personality and its pathology. The analysis also suggests directions for future confirmatory studies into the underlying behavior patterns that link adaptive and maladaptive variants consistent with contemporary models of personality pathology.

SUBMITTER: Yan R 

PROVIDER: S-EPMC8951872 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Exploratory Machine Learning Modeling of Adaptive and Maladaptive Personality Traits from Passively Sensed Behavior.

Yan Runze R   Ringwald Whitney R WR   Hernandez Julio Vega JV   Kehl Madeline M   Bae Sang Won SW   Dey Anind K AK   Low Carissa C   Wright Aidan G C AGC   Doryab Afsaneh A  

Future generations computer systems : FGCS 20220224


Continuous passive sensing of daily behavior from mobile devices has the potential to identify behavioral patterns associated with different aspects of human characteristics. This paper presents novel analytic approaches to extract and understand these behavioral patterns and their impact on predicting adaptive and maladaptive personality traits. Our machine learning analysis extends previous research by showing that both adaptive and maladaptive traits are associated with passively sensed behav  ...[more]

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