Chinese Immigrants’ Health Beliefs and Practices of Traditional Chinese Medicine in British Columbia of Canada
Bibliographic record
Abstract
Objective: This study is to address the health beliefs and health behavior of Chinese immigrants residing in the Greater Vancouver area of British Columbia (BC) Province in Canada. This article discussed Chinese immigrants’ traditional Chinese medicine (TCM) use, health beliefs, and health behaviors. Methods: Information used in this study is based on data collected in the Chinese-speaking community in the Greater Vancouver area of BC in 2020–2022. Quantitative and qualitative methods were applied to this study. The first stage recruited 314 participants for the quantitative study to cross-validate an instrument tool, followed by the 2nd stage of 20 stratified random sampling out of the 314 participants for TCM-related in-depth qualitative interviews. This study focuses on the second stage of TCM qualitative interviews. Results: Results indicated that TCM health beliefs have cultural and spiritual meanings tied to the Chinese-speaking participants. There are barriers for the Chinese-speaking population to access the existing healthcare services due to their TCM health beliefs and other health needs, for example, family doctors, integrated medicine for better health outcomes, and mental health services especially during the coronavirus disease 2019 (COVID-19) pandemic. Conclusion: Integrating TCM health beliefs and behaviors of Chinese-speaking immigrants into existing Canadian mainstream health services are strongly recommended.
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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 | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".