Regional differences among ethnic Chinese on level of acculturation to Canadian culture and perceived barriers to mental health help seeking
Bibliographic record
Abstract
Background Ethnic Chinese are the largest immigrant population within Canada, yet they consistently under-utilize mental health services. Acculturation is considered an important factor in accessing services within the target country; however it is unclear if there are differences among ethnic Chinese in terms of accessing services and their level of acculturation. Methods A self-report questionnaire was administered to a convenience sample of ethnic Chinese at two sites in Metro-Vancouver (community & hospital) in order to examine the level of comfort and embarrassment, as well as perceived attitudinal and structural barriers in accessing mental health services. Results Higher levels of embarrassment in mental health seeking were found in subjects from the community, and from Mainland China. Higher attitudinal barriers were found in whereas greater structural barriers were found in the community sample. Subjects with more than 12 years of education or who used English in everyday life identified more with Canadian culture. Conclusion Traditional cultural values appear to be salient in accessing mental health services among ethnic Chinese. This has relevance with respect to improving access and utilization of mental health resources by ethnic Chinese in order to provide screening for common mental health disorders such as depression.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".