Literature DB >> 31612593

The Role of Trait and State Perfectionism in Psychological Detachment From Daily Job Demands.

Dorota Reis1, Elisabeth Prestele2.   

Abstract

Psychological detachment has been proposed to be a mediator of the relations between an individual's responses to stressful work-related experiences and mid- and long-term health. However, the number of studies that have specifically examined the role that personal characteristics play in these associations is considerably small. One personal characteristic that might specifically interfere with psychological detachment is perfectionism, which has been considered an important vulnerability factor for the development of psychological disorders. Hence, the goal of this registered report was to extend research on psychological detachment by introducing trait and state perfectionism as moderators of the aforementioned relations. We conducted an experience sampling study with three measurement occasions per day over the course of 3 working weeks (N = 158 employees; Mage = 41.6; 67% women). Multilevel path models showed that perfectionistic concerns consistently determined strain responses at between- and within-levels of analyses even after the effects of job demands (i.e., unfinished tasks and role ambiguity) and detachment were accounted for. However, we found no evidence for the proposed moderation effects. The theoretical implications for the understanding of the processes proposed in the stressor-detachment model are discussed.
© 2019 The Authors. Stress and Health published by John Wiley & Sons Ltd.

Entities:  

Keywords:  job stress; multilevel moderated mediation model; perfectionism; psychological detachment; registered report

Year:  2020        PMID: 31612593     DOI: 10.1002/smi.2901

Source DB:  PubMed          Journal:  Stress Health        ISSN: 1532-3005            Impact factor:   3.519


  2 in total

1.  Implementation of Computer-Aided Piano Music Automatic Notation Algorithm in Psychological Detoxification.

Authors:  Xinmei Zhang
Journal:  Occup Ther Int       Date:  2022-06-30       Impact factor: 1.565

2.  Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants' Well-being: Ecological Momentary Assessment.

Authors:  Alexander Hart; Dorota Reis; Elisabeth Prestele; Nicholas C Jacobson
Journal:  J Med Internet Res       Date:  2022-04-28       Impact factor: 7.076

  2 in total

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