Medical students' quarter-life crisis
Bibliographic record
Abstract
Objectives: This was the first study that explored factors associated with medical students' quarter-life crisis, the anxiety young might experience at the end of their studies and in the beginning of their career. Methods: 351 medical students (74.6% female, M: 23.79 years, SD: 1.53 years) filled the online questionnaire, that contained Quarter-life Crisis Questionnaire, International Personality Item Pool version of Big Five markers, and questions about different aspects of medical school. Independent t-test, Mann-Whitney U test and linear regression analysis was performed. Results: Women reported higher quarter-life crisis. Pre-medical school experiences: Higher quarter-life crisis displayed among those students who did not apply to medical university right after high school. Attitudes on medical school: students who would have not applied to medical school again; would have not encouraged their children to apply to medical school; were uncertain to finish the university showed higher quarter life crisis. Factors of academic achievement: students who failed at least one term for academic reason; did not feel to get proper knowledge to accomplish a medical job; were not satisfied with their grades reported higher quarter life crisis. Future plans: Students who did not plan to work in a clinical field and patient care; wanted to work abroad in the future had higher quarter life crisis. Personality traits: Extraversion, conscientiousness were significant negative, neuroticism significant positive predictor of quarter life crisis. Conclusion: The explored variables might be indicators of quarter-life crisis, and can be the basis of university counseling, when medical students' quarter-life crisis and emerging adulthood is in focus.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".