Daily Links Between Leisure Activities, Stress, and Well-Being During the Transition to University
Bibliographic record
Abstract
Leisure activities engagement could promote freshmen’s well-being by providing social support and improving positive mood. Little is known about the day-to-day variability in leisure activities and stress and their links to daily well-being. Using a month-long daily diary design among 273 Canadian freshmen (Mage = 18, 73% female, 32% White), this study investigated the relations between daily leisure activities, stress, and well-being. Multilevel modeling revealed that daily leisure activities showed concurrent positive effects on daily well-being, whereas daily stress had negative effects. There were substantial inter-individual differences in these links, which were partly explained by coping orientations and person-average levels of stress. Engaging in more diverse leisure activities was related to better well-being. The findings demonstrate the immediate beneficial effects of leisure activities on well-being in everyday life, and provide interventions with amendable targets to promote freshmen’s positive socioemotional development during their transition to university.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".