Patterns and predictors of change in energy and mood around a vacation from the workplace: Distinguishing the effects of supplemental work activity and work‐related perseverative cognition
Bibliographic record
Abstract
Abstract This study contributes to the vacation literature by exploring predictors of change in school teachers' negative affective states around a 2‐week (Christmas) vacation. Drawing from a combination of self‐regulatory and effort‐recovery theoretical principles, we hypothesized that supplemental work activity during the vacation might have some positive consequences for mood state, while simultaneously impairing the ability to recover from work‐related exhaustion. Ninety teachers completed measures across eight consecutive weeks, spanning the period before, during and after vacation (710 observations in total). Teachers' weekly levels of emotional exhaustion, anxious mood and depressed mood decreased significantly from before to during the vacation. Following the vacation, anxious mood showed the most rapid rate of increase, returning to its prevacation level within 2 weeks of work resumption. Exhaustion and depressed mood re‐emerged more gradually across 4 consecutive weeks following the vacation. Supplemental work activity during the vacation was associated with weaker recovery from exhaustion, but did not exhibit a detrimental relationship with change in anxious or depressed mood. Of note, supplemental working during the vacation was associated with a less pronounced re‐emergence of anxious mood after the vacation. Work‐related perseverative cognition (worry and rumination) during the vacation impeded energy restoration and mood repair and was related to faster fade out of beneficial vacation effects. These findings demonstrate the utility of examining discrete energy and mood states in respite research, reveal the mixed functions of engaging in supplemental work activity during vacations and highlight the harmful impact of perseverative cognition on the recovery from work process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".