Impacts of Stress Coping Approaches on Covid-19 Anxiety: A Sample of Turkish Medical School Students
Bibliographic record
Abstract
We aimed to assess Covid-19 anxiety among Turkish medical school students. More specifically, we examined the association between the participants’ age, gender, grades, stress coping approaches and Covid-19 anxiety using a quantitative design. The participants were 875 (493 female and 480 male students) medical school students between 19 and 26 years old. The participants completed Ways of Coping Inventory and Coronavirus Anxiety Scale. It was observed that university students in the schools of medicine used stress coping approaches such as searching for social support and self-confident. ANOVA analyses revealed that female medical school students had higher mean scores for the search for social support, optimistic, submissive, and helpless approaches, while male medical school students had higher scores for self-confident approach. Post hoc analysis indicated that the first-grade medical school students used self-confident stress coping approach more often than the higher-grade medical school students. We established that 21 years and older medical school students used submissive stress coping approach more often than younger students. Hierarchical regression revealed that gender female, submissive and helpless approaches explained 11% of the variance in Coronavirus anxiety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".