Stress events and stress symptoms in Chinese secondary school students: gender and academic year characteristics of the relationship
Bibliographic record
Abstract
Objective: To explore the relationship between stress events and stress symptoms and their gender and academic year characteristics in Chinese secondary school students. Methods: 4,995 secondary school students were investigated by the Adolescent Self-rating Life Events Checklist (ASLEC) and the Calgary Symptoms of Stress Inventory (C-SOSI). Results: First, there were significant differences in all dimensions and total scores of stress events and stress symptoms between boys and girls in secondary school and between junior high school students and senior high school students. Second, the dimensions and total scores of stress events in secondary school students are positively correlated with the dimensions and total scores of stress symptoms. Third, the influence of punishment on the stress symptoms of secondary school boys is the most obvious, and the influence of punishment, adaption, relationship stress, and learning stress on the stress symptoms of secondary school girls is the most obvious. The influence of punishment on the stress symptoms of junior high school students is the most obvious, and the influence of punishment and relationship on the stress symptoms of senior high school students is the most obvious. Conclusion: Stress events and stress symptoms of Chinese secondary school students have significant differences in gender and academic year. The same stress event has different influence mechanisms on the stress symptoms of Chinese secondary school students of different genders and different academic years.
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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 | 0.001 |
| 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) | 0.003 | 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 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".