Prevalence, correlates of major depression: A mental health survey among undergraduates at a mainland <scp>C</scp>hinese university
Bibliographic record
Abstract
INTRODUCTION: This cross-sectional survey among Chinese university students aimed to estimate the prevalence and risk factors of major depressive disorder (MDD) among undergraduates, in order to provide basic information for the prevention and treatment of depression among the college-aged population. METHODS: A total of 2,046 undergraduates were interviewed face to face using the World Health Organization Composite International Diagnostic Interview Version 3.0 (WHO-CIDI, version 3.0). Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria were used to diagnose MDD. Logistic regression was used to evaluate the associations between MDD and selected correlates. RESULTS: The survey response rate was 90.1% (N = 1,843). The prevalence rates of MDD were 3.9% (lifetime), 2.4% (12 months) and 0.4% (30 days). No significant gender or age differences were found in prevalence rates. No sociodemographic characteristics were related to the lifetime prevalence of MDD. In contrast, family structure and environment factors specifically being from a single-parent family (odds ratio [OR] = 2.513, confidence interval [CI] = 1.404-2.500), parents having mental problems (OR = 1.809, CI = 1.104-2.964), and physical punishment (OR = 1.789, CI = 1.077-3.001) were associated with higher lifetime prevalence of MDD. DISCUSSION: These findings showed a relatively lower prevalence of DSM-IV/CIDI MDD in this sample of Chinese undergraduates than that reported for students in other countries. However, the prevalence rate for university students was higher than that reported for general Chinese population. Family structure and socio-environmental factors in the student's family of origin significantly correlated with the lifetime prevalence of MDD.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".