OBJECTIVES: This study of a large and heterogeneous sample of 5210 daytime employees was designed to shed more light on the work effort-recovery mechanism by examining the cross-sectional relations between subjective sleep quality and (i) psychosocial work characteristics, (ii) work-related rumination, (iii) fatigue after work, and (iv) affective well-being at work and work pleasure. METHODS: We used the Dutch Questionnaire on the Experience and Evaluation of Work and created three sleep quality groups (low, low-to-intermediate, and high quality). Group differences were studied through analysis of variance (ANOVA). To examine the relations among the study variables in more detail, we also conducted four sets of stepwise regression analyses. In all the analyses, we corrected for age, level of education, and gender. RESULTS: A series of (M)ANOVA provided strong evidence for a relation between sleep quality and adverse work characteristics and work-related rumination. Furthermore, poor sleepers reported higher levels of fatigue after work, and poor sleep quality was related to both lower affective well-being during work and work pleasure. Regression analyses revealed that sleep quality was the strongest statistical predictor of after-work fatigue and affective well-being at work, and high levels of work rumination constituted the strongest statistical predictor of sleep complaints. CONCLUSIONS: As this study showed strong relations between sleep quality, occupational stress, fatigue, perseverative cognitions, and work motivation, it supports effort-recovery theory. Interventions should aim to prevent a disbalance between effort and recovery.
OBJECTIVES: This study of a large and heterogeneous sample of 5210 daytime employees was designed to shed more light on the work effort-recovery mechanism by examining the cross-sectional relations between subjective sleep quality and (i) psychosocial work characteristics, (ii) work-related rumination, (iii) fatigue after work, and (iv) affective well-being at work and work pleasure. METHODS: We used the Dutch Questionnaire on the Experience and Evaluation of Work and created three sleep quality groups (low, low-to-intermediate, and high quality). Group differences were studied through analysis of variance (ANOVA). To examine the relations among the study variables in more detail, we also conducted four sets of stepwise regression analyses. In all the analyses, we corrected for age, level of education, and gender. RESULTS: A series of (M)ANOVA provided strong evidence for a relation between sleep quality and adverse work characteristics and work-related rumination. Furthermore, poor sleepers reported higher levels of fatigue after work, and poor sleep quality was related to both lower affective well-being during work and work pleasure. Regression analyses revealed that sleep quality was the strongest statistical predictor of after-work fatigue and affective well-being at work, and high levels of work rumination constituted the strongest statistical predictor of sleep complaints. CONCLUSIONS: As this study showed strong relations between sleep quality, occupational stress, fatigue, perseverative cognitions, and work motivation, it supports effort-recovery theory. Interventions should aim to prevent a disbalance between effort and recovery.
Authors: Zbigniew Obmiński; Jan Supiński; Łukasz Rydzik; Wojciech J Cynarski; Mariusz Ozimek; Zbigniew Borysiuk; Wiesław Błach; Tadeusz Ambroży Journal: Biology (Basel) Date: 2022-05-27