INTEGRO-DIFFERENTIAL PRINCIPLE IN PERSONALITY DEVELOPMENT: THE POSSIBILITY OF MATHEMATICAL DESCRIPTION WITHIN THE STRUCTURAL THEORY FRAMEWORK
Abstract
The research is devoted to the mathematical description possibility of the personality development dynamics within the factor models framework. The dynamic Ornstein-Uhlenbeck equation is used, which describes a stochastic stationary process tending to an equilibrium state. This equation has already been used by psychologists to describe the dynamics of development within the framework of personality “Big Five” model. In this paper, this approach is used for qualitative interpretation and visual demonstration of the integration and differentiation principles in personality development based on the transformation of R. Cattell’s factor model. A simple analytical solution of the equation for averaged psychological indicators is compared with the results of the author’s longitudinal study of the dynamics of changes in the personal traits interrelations for schoolchildren in the transition period between primary school and adolescence. When comparing theoretical and experimental results, it is shown that the model makes it possible to assess the patterns of mental development in a transitional (crisis) period, to interpret the mechanism of development, the manifestation of heterochrony and the integro-differentiation principle.
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Rachel L.C. Mitchell, Veena Kumari Hans Eysenck’s interface between the brain and personality: Modern evidence on the cognitive neuroscience of personality. Personality and Individual Differences, 2016, vol. 103, pp. 74-81.
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Shchebetenko S., Kalugin A.Y., Mishkevich A.M., Soto C.J., John O.P. Measurement invariance and sex and age differences of the big five inventory-2. Evidence From the Russian Version. Assessment, 2020, vol. 27(3), pp. 472-486. https://doi.org/10.1177/1073191119860901
Slavutskaya E., Slavutskii L. Dynamics of personality development in pre-adolescence: longitudinal study. Social and Cultural Transformations in the Context of Modern Globalism. European Proceedings of Social and Behavioural Sciences. Future Academy, 2020, vol. 76, pp. 2944-2951. https://doi.org/10.15405/epsbs.2019.12.04.396
Slavutskaya E., Slavutskii L., Zakharova A., Nikolaev E. Integrated use of data mining techniques for personality structure analysis. Technology, Innovation and Creativity in Digital Society. PCSF 2021. Lecture Notes in Networks and Systems. V. 345. Springer, Cham. https://doi.org/10.1007/978-3-030-89708-6_44
Sosnowska J, Kuppens P, De Fruyt F, Hofmans J. New directions in the conceptualization and assessment of personality - a dynamic systems approach. European Journal of Personality, 2020, vol. 34(6), pp. 988-998. https://doi.org/10.1002/per.2233
Soto C.J., John O. P. Short and extra-short forms of the Big Five Inventory 2: The BFI-2-S and BFI-2-XS. Journal of Research in Personality, 2017, vol. 68, pp. 69-81.
Uhlenbeck G.E., Ornstein L.S. On the theory of Brownian Motion. Phys. Rev., 1930, vol. 36(5), pp. 823–841. https://doi.org/10.1103/PhysRev.36.823
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