adaptive and maladaptive perfectionism, and professional burnout among medical laboratory scientists
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2018
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Abstract
Background
The goal of this paper is to verify the correlations between adaptive and maladaptive perfectionism and the selected
demographic and job characteristics vs. professional burnout among medical laboratory scientists in Poland.
Material and Methods
The study group consisted of 166 laboratory scientists. The Polish Adaptive and Maladaptive Perfectionism Questionnaire
(Szczucka) was used for testing perfectionism. The Oldenburg Burnout Inventory was used for examining burnout syndrome.
Results
Adaptive perfectionism was positively and maladaptive perfectionism was negatively correlated with both aspects of
professional burnout: the disengagement from work and exhaustion. What is more, maladaptive perfectionism was correlated
negatively with age and work experience. People in relationships have a higher level of disengagement and a higher level of exhaustion
than single ones. The results of hierarchical regression analyses have revealed, after having controlled selected demographic
and job factors, that a significant predictor of disengagement is the high level of adaptive perfectionism and low level of maladaptive
perfectionism. In addition, a significant predictor of high level of exhaustion is the low level of maladaptive perfectionism.
Conclusions
Professional burnout among medical laboratory scientists is of a specific nature. The “healthier” perfectionism they
reveal, the higher level of burnout they present. In this profession, lower risk of burnout is represented by those who are characterized
by the lack of confidence in the quality of their actions and a negative reaction to their own imperfections associated with
imposed social obligation to be perfect. The individuals pursuing their internal high standards experience burnout faster. Med
Pr 2018;69(3):253–260
| Reference Key |
robakowska2018medycynaadaptive
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| Authors | ;Marlena Robakowska;Anna Tyrańska-Fobke;Maciej Walkiewicz;Małgorzata Tartas |
| Journal | journal of bioinformatics and computational biology |
| Year | 2018 |
| DOI |
10.13075/mp.5893.00644
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| URL | |
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