The mediating role of self-compassion in positive education for student mental health during COVID-19
Bibliographic record
Abstract
In this quasi-experimental design, we tested the hypothesis that a quality of life (QOL) positive education course delivered online during COVID-19 would promote undergraduate students' mental health by improving self-compassion. A total of 104 students (69 enrolled in the QOL course and 35 in control courses) completed a questionnaire assessing mental health and self-compassion before and after completion of their courses. Two-way mixed ANCOVAs were used to analyse the effects of the positive education course on mental health and self-compassion over time. Compared to control students, QOL students' mental health and self-compassion significantly increased from baseline to endpoint. A simple mediation analysis confirmed the mediating role of self-compassion between the positive education course and enhanced mental health. This study adds to the emerging literature vis-à-vis positive education and its effects on student mental health through self-compassion.
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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 | 0.002 | 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 | 0.001 | 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".