Risk Factors for Depression in Older Adults in Beijing
Bibliographic record
Abstract
OBJECTIVE: Depression is a common mental disorder in older adults. We examined the prevalence and risk factors for depression in older adults in the Beijing area. METHOD: We used data from a cross-sectional survey conducted in July 2006 in Beijing. As part of the national survey for older Chinese adults, 2002 older adults were interviewed. The 15-item Geriatric Depression Scale was used to assess depression. Demographics as well as other personal information were also collected. RESULTS: Among Beijing older adults, 13.01% were categorized as depressed. Prevalence rates of depression in rural and urban older adults were 26.63% and 10.79%, respectively. Poor economic status, high activities of daily living (ADL) score, poor physical health, impious offspring, and feeling old were important predictors of depression in older adults in Beijing. For the urban sample, poor economic status, poor physical health, high ADL score, and impious offspring were risk factors for depression. For the rural sample, depression was significantly associated with poor economic status and poor physical health. CONCLUSIONS: Depression is a common mood disorder among older adults in the Beijing area. Filial piety is a unique predictor for depression in older Chinese adults, compared with findings in Western cultures.
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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 | 0.000 | 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) | 0.001 | 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".