Association between Mental Health Knowledge Level and Depressive Symptoms among Chinese College Students
Bibliographic record
Abstract
This study aimed to explore the association between mental health knowledge level and the prevalence of depressive symptoms among Chinese college students. A cross-sectional study was conducted in six universities in Jinan, Shandong Province, China, and a total of 600 college students were recruited to self-complete a series of questionnaires. The Mental Health Knowledge Questionnaire (MHKQ) was used to investigate the level of mental health knowledge. Depressive symptoms were investigated with the depression subscale of the Depression Anxiety Stress Scale (DASS-21). The prevalence rate of depressive symptoms among college students was 31.2%. Compared with MHKQ scoring in the 1st quartile, college students with MHKQ scoring in the 3rd quartile and in the 4th quartile reported lower levels of depressive symptoms after adjusting for potential confounding factors. Since mental health knowledge level was related to depressive symptoms among college students, increased efforts to promote the level of mental health knowledge in Chinese college students are critical.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".