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ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Computational Psychiatry
Volume 15 - 2024 |
doi: 10.3389/fpsyt.2024.1436121
This article is part of the Research Topic Machine Learning and Statistical Models: Unraveling Patterns and Enhancing Understanding of Mental Disorders View all 5 articles
Data-Driven vs. Psychological Personality Temperaments: Theoretical and Clinical Utility of Personality Measures in Psychiatry
Provisionally accepted- 1 Palestinian Neuroscience Initiative, Al-Quds University, Jerusalem, Jerusalem, Palestine
- 2 Institute of Neuroscience and Medicine, Julich Research Center, Helmholtz Association of German Research Centres (HZ), Jülich, North Rhine-Westphalia, Germany
- 3 Faculty of Medicine, RWTH Aachen University, Aachen, North Rhine-Westphalia, Germany
- 4 Center for Molecular and Behavioral Neuroscience, School of Arts & Sciences, Rutgers University, Newark, Newark, New Jersey, United States
Decades of research on personality identified dissociable psychological temperaments. Cloninger's temperament and character theory used a psychobiological approach to differentiate three major dimensions of personality: harm avoidance, novelty seeking, and reward dependence. Previous studies, heretofore, did not examine the correspondence between Cloninger's psychological temperaments and statistically independent data-driven components and how that could enhance the clinical utility of personality temperaments. In this study, we validated an Arabic version of the tri-dimensional personality questionnaire (TPQ) to construct data-driven personality temperaments using independent component analysis (ICA). Using SVM, we contrasted the clinical utility of data-driven personality vs. Cloninger's psychological temperaments in differentiating medication-naïve patients with major depressive disorder (N=244) and healthy subjects (N=1109). Data-driven personality components based on ICA showed very little overlap with Cloninger's original temperaments. Both Cloninger's temperaments and data-driven components revealed low internal consistency (for subscales) but high test-retest reliability. Cloninger's temperaments, however, showed a poor goodness-of-fit for the structure of the TPQ. Data-driven components significantly outperformed psychological TPQ temperaments with higher accuracy and recall but not precision. To our knowledge, this is the first study to examine the clinical utility of data-driven vs. psychological personality metrics using a sizeable sample of patients and healthy individuals. Our results could have wide implications for reexamining psychometric data to extract data-driven latent structures that can improve replicability, clinical utility, and cross-disciplinary inference.
Keywords: Abdulrahman S. Sawalma Writing (first draft preparation), Software, data analysis, visualizations Mahmud A. Sehwail Writing (editing/reviewing), clinical supervision, recruitment Jürgen Dammers Writing (editing/reviewing), supervision, Analysis design
Received: 21 May 2024; Accepted: 07 Oct 2024.
Copyright: © 2024 Sawalma, Sehwail, Dammers and Herzallah. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Mohammad M. Herzallah, Palestinian Neuroscience Initiative, Al-Quds University, Jerusalem, 5100, Jerusalem, Palestine
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