Cultural contexts during a pandemic: a qualitative description of cultural factors that shape protective behaviours in the Chinese-Canadian community
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, there have been significant variations in the level of adoption of public health recommendations across international jurisdictions and between cultural groups. Such variations have contributed to the dissimilar levels of risks associated with this world-changing viral infection and have highlighted the potential role of culture in assigning meaning and importance to personal protective behaviours. The purpose of this study is to describe the cultural factors during the COVID-19 pandemic that shaped protective health behaviours in the Chinese-Canadian community, one of the largest Chinese diasporas outside of Asia. METHODS: A qualitative descriptive design was employed. Content analysis was used to analyze the data from semi-structured virtual interviews conducted with 83 adult Chinese-Canadian participants residing in a metropolitan area in the Province of Ontario, Canada. FINDINGS: The cultural factors of collectivism, information seeking behaviour, symbolism of masks, and previous experience with severe acute respiratory syndrome (SARS) emerged as themes driving the early adoption of personal protective behaviours within the Chinese-Canadian community during the first wave of COVID-19. These protective behaviours that emerged prior to the first nation-wide lockdown in Canada included physical distancing, mask use, and self-quarantine beyond what was required at the time. CONCLUSION: These findings have implications for the development of future public health interventions and campaigns targeting personal protective behaviours in this population and other ethnic minority populations with similar characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".