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Efficient self-regulation of human functional states as a predictor of work success under long-term innovation stress
Published online by Cambridge University Press: 01 September 2022
Abstract
Research data indicate the necessity of efficient human functional states’ (HFS) self-regulations for successful work execution, and not only for those professionals, who work under extreme work conditions; efficient HFS self-regulation is discussed as one of the key professional competences in socionomic jobs as well (Friedman, 2003; Landy & Conte, 2021). Moreover, ability of efficient HFS self-regulation could be viewed as a differentiative competence for separation of professionals with normal and high work achievements (Spencer L. & Spencer S., 1993).
The empirical study was targeted to investigate HFS self-regulation efficiency as a predictor of work success under long-term innovation stress.
The longitudinal research was conducted in college teachers (n=50) during the period of organizational innovations. The empirical data were obtained by the diagnostic set of methods for self-assessment of attitudes towards innovations as a factor of long-term work strain, coping strategies and self-regulation means, chronic fatigue and burnout as the main consequences of long-term stress manifestations (Hobfoll, Dunahoo, Ben-Porath & Monnier, 1994; Leonova, 2012).
The significant diversity in the level of HFS self-regulation efficiency in teachers with different work success has been found (p<0,05). Teachers with the highest level of work results have a well-developed system of self-regulation means, which allows them to cope with innovation stress.
The empirical data revealed patterns of effective self-regulation means, which are adequate to situational requirement, professional norms and rules of organizational behavior. Obtained results formed the basis for the elaboration of training course for HFS self-regulation skills development.
No significant relationships.
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- Information
- European Psychiatry , Volume 65 , Special Issue S1: Abstracts of the 30th European Congress of Psychiatry , June 2022 , pp. S690
- Creative Commons
- This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Copyright
- © The Author(s), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association
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