Stress Levels and Examination Performance of Medical Students
Bibliographic record
Abstract
Introduction The effects of stress are known to be multi faceted. Hans Selye, the father of the science of stress, studied effects of stress on the human body. Though stress is being studied in detail since long, somehow stress is still a mystery. Performance of a person in examination depends on many factors. In present study, we attempted to find stress levels and their effect on examination performance of first year medical students. Material and Methods In present study, we asked fifty first year medical students to rate their perceived level of stress in percentage score from 0-100; 100 being the highest, along with other relevant data. We correlated this stress level and other factors with their marks in “intermediate exams”, i.e. exams conducted in + 60 days of recording stress score. Results It was found that stress levels higher than 40, suggestive of distress; lead to decrease in examination performance, as evidenced by decrease in marks in all examinations conducted in this period viz. three written theory examinations and two practical examinations.
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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 | 0.019 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".