Relationships Between First-Year Student Resilience and Academic Stress
Bibliographic record
Abstract
Academic stress is a prevalent issue among university students, with significant implications for mental health and academic performance. This exploratory study examined whether academic stress could be predicted from resilience sub-factors based on a three-factor model of resilience. An initial sample of 70 first-year university students completed self-report measures assessing mastery, relatedness, emotional reactivity, and academic stress. After accounting for missing data, 68 participants were female (65%; n = 44) and 35% (n = 24) were male. The mean age of the participants was 18.52 years, with a standard deviation of 1.26. Multiple regression analysis revealed that the sub-factors of mastery, relatedness, and reactivity were significant predictors of academic stress. Specifically, self-efficacy and perceived support were negatively associated with academic stress, and emotional sensitivity was positively associated with academic stress. The results have important implications for interventions aimed at reducing academic stress that focus on these resilience sub-factors could offer an effective approach for improving outcomes in transitioning students. Interventions such as cognitive training and mindfulness-based programs may strengthen students’ executive function difficulties, thereby improving their ability to cope with academic stress and foster resilience.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".