Depression among elderly Chinese-Canadian immigrants from Mainland China.
Bibliographic record
Abstract
BACKGROUND: This study examined the prevalence of depressive symptoms among elderly immigrants from Mainland China to Canada and the impact of various psychosocial factors as predictors of the number of depressive symptoms reported by the elderly Chinese immigrants. METHODS: The participants were 444 elderly immigrants who migrated from Mainland China to Canada. They were a part of a random sample of 2272 elderly Chinese living in the communities and took part in a face-to-face interview to answer questions in an orally administrated questionnaire. The depressive symptoms of the participants were measured by a Chinese version of the Geriatric Depression Scale. Data obtained from the 444 elderly Chinese immigrants was analyzed to assess the impact of various psychosocial factors on the number of depressive symptoms that they reported. RESULTS: The findings indicated that 23.2% of the elderly immigrants were assessed to have some depressive symptoms. When other predicting variables were adjusted, elderly immigrants with more chronic illnesses, less positive attitude towards ageing, poorer physical health, less adequate financial situation, lower level of ethnic identification as Chinese, more service barriers, lower level of life satisfaction, shorter length of residency in Canada and those who lived alone tended to have more depressive symptoms. CONCLUSIONS: The findings indicate that the prevalence rate of depressive symptoms among our elderly immigrant sample is higher than the one reported in a general elderly population. While further research is recommended to examine the reasons for such a difference, culturally appropriate health services, including health promotion programs, should be promoted to reduce mental health disparities.
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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 | 0.000 | 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) | 0.001 | 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 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".