The Effects of Weekly Levels of Supervisor Support and Workload on Next Week Levels of Well‐Being, Satisfaction, and Performance as Mediated by Weekend Work Recovery
Bibliographic record
Abstract
This diary study sought to examine the direct and indirect effects of individuals' perceptions of supervisor support and workload during a work week (week 1) on their well-being, satisfaction, and performance at work during the following work week (week 2) as mediated through the quality of their weekend work recovery experiences (psychological detachment, relaxation, mastery, and control) and sleep quantity. Moreover, we also investigated the possible interaction between supervisor support and workload in the prediction of weekend recovery experiences and sleep quantity. A sample of 90 second-year nursing students taking part in a professional internship completed self-report questionnaires after each of their five working days during week 1 (i.e., supervisor support and workload), then at the end of the day for 2 days during the weekend (i.e., recovery experiences and sleep quantity), and finally after each of their five working days during week 2 (i.e., workplace well-being, performance, and satisfaction). Our results revealed indirect effects of supervisor support on workplace well-being and job satisfaction, as mediated by weekend recovery experiences. Workload was also associated with higher levels of sleep quantity during the weekend and had a direct negative association with the levels of satisfaction and well-being experienced during the following week. Furthermore, workload was associated with better weekend recovery experiences for participants exposed to low levels of supervisor support in week 1. Alternatively, the positive effects of supervisor support on weekend recovery experiences were attenuated as workload levels increased. Theoretical and practical implications of the present study are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".