European student wellness, stress, coping, support and perceptions about remote dental training during COVID‐19
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to compare wellness, stress, ability to cope, social support and perceptions about remote training amongst European dental students during COVID-19. METHODS: 1795 undergraduate dental students from six countries and eight dental schools participated. The anonymous survey collected data about different aspects in each of the following domains: wellness, stress, ability to cope, social support and perceptions about remote training. Complex multi-item scales were used for all domains. RESULTS: There were differences amongst countries in all the domains. Overall, student stress scores were lower than either their coping or support scores. The highest wellness score (mean ±sd) was observed in Romania: 62.5% ± 11.2% whilst the highest mean stress scores were observed in Albania: 46.3% ± 11.7% and Lithuania: 42.2% ± 13.8%. Overall, student stress and coping ability scores were lower and their support scores higher. About 10% of students did not have any support. In the linear multivariable regression analysis, significant predictors of wellness were being female (β = 0.073), not being in a graduating year (β = 0.059), having less stress (β = 0.222), ability to cope (β = 0.223) and having support (β = 0.179). The student positive perceptions about remote training were predicted by less stress (β = 0.080), coping (β = 0.182) and support (β = 0.057). CONCLUSIONS: Students varied in wellness, stress, coping, social support and perceptions of remote training. Also, there were significant differences amongst students from different countries. Coping was the best predictor of both student wellness and their positive perceptions about remote training.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".