Prevalence, awareness, and treatment of depressive symptoms among the middle‐aged and elderly in China from 2008 to 2015
Bibliographic record
Abstract
INTRODUCTION: This study aimed at exploring the temporal trend of prevalence, awareness, and treatment of depressive symptoms among the middle-aged and elderly in China from 2008 to 2015, as well as depicting how many respondents suffered from persistent depression, whether they were aware of and how they coped with such persistent conditions over time. METHODS: This study used the 2008, 2011, 2012, 2013, and 2015 data of China Health and Retirement Longitudinal Study. We used descriptive statistics for data analysis. RESULTS: The prevalence of depressive symptoms among the middle-aged and elderly in China remained relatively stable at 32% to 37% from 2008 to 2015. Only less than 5% of those with depressive symptoms were aware of their conditions and less than 2% sought care over time. We also observed that persistent depression was very severe among the respondents and most of those with persistent conditions were still not aware of nor seek any care for the symptoms. CONCLUSION: Despite of the continuous efforts done by the Chinese government, depression in China is still in poor management. The Chinese government needs to first understand why and how the continuous government efforts do not turn into actual effects of depression management.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".