In sport and now in medical school: examining students’ well-being and motivations for learning
Bibliographic record
Abstract
OBJECTIVES: To investigate relationships between students' past level of involvement in physical activity/sport and their motivations for learning (achievement goals) and well-being in medical school. In doing so, we provide evidence to medical programs to inform admission processes and curriculum planning. METHODS: A cross-sectional study was conducted. Out of 640 medical students, 267 completed an online questionnaire with measures of: achievement goals, academic burnout, physical activity/sport involvement, and demographics. Data were analyzed using descriptive and inferential statistics (frequency, mean, standard deviation, chi-square test, Cronbach alpha, Spearman correlation). RESULTS: Students who had pursued physical activity/sport at higher levels of involvement had lower academic burnout scores and endorsed maladaptive achievement goals to a less degree. Specifically, the level of students' involvement in physical activity/sport was negatively correlated with academic burnout (r=-0.15, p=0.014) and with achievement goals of performance approach (r=-0.15, p=0.014), performance avoidance (r=-0.21, p=0.001), and mastery avoidance (r=-0.24, p<0.001). CONCLUSIONS: Pursuit of dedicated personal activities such as sport appears to be associated with the desired quality of motivation and well-being of medical students. A school culture that fosters resilience of newly admitted students through extracurricular activities and raises students' awareness of maladaptive and adaptive achievement goals is likely to be beneficial in addressing academic burnout and improving the mental health of medical students.
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 | 0.005 | 0.013 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".