Exploring the dietary choices of Chinese women living with breast cancer in Metro Vancouver
Bibliographic record
Abstract
Breast cancer is the most frequently diagnosed cancer in Canadian women, including women from immigrant groups. Many women with breast cancer believe that diet is responsible for their cancer and recurrence. Several ethnic groups have culturally distinctive views on food and its consumption, including the Chinese who constitute the largest visible minority population in Metro Vancouver. Studies have shown that Chinese breast cancer patients in other countries integrate their cultural beliefs about diet and traditional Chinese medicine to prevent cancer recurrence and promote health. However, limited studies have been performed to understand the dietary choices and information needs of Chinese breast cancer patients in British Columbia (B.C.). Currently there are few culturally specific resources despite the large immigrant population in the province. In this qualitative study, purposive sampling was used to recruit 19 first- and second-generation Chinese Canadian women aged 41-73 years in Vancouver, who have been diagnosed with breast cancer within the last five years. Interviews were recorded and transcribed verbatim. Data were analyzed using qualitative data analysis software and manual coding. Themes were developed using interpretive description methodology, an inductive approach to understanding clinical phenomena and generate implications for clinical practice. A follow-up focus group was held with participants to validate the emergent themes and enhance rigour. Five main themes were generated; (i) dietary change process, (ii) goals of dietary change, (iii) dietary beliefs and uncertainties, (iv) barriers and facilitators to dietary change and (v) information and resource needs. Participants implemented dietary changes to various degrees and the majority reduced consumption of meat. Many expressed fear and uncertainties over the effects of some foods after diagnosis. Barriers and facilitators to dietary change were family preference, convenience, taste and cost. The main sources of diet related information were family, friends, Internet, media, supportive cancer care centre, and doctors of traditional Chinese medicine. Participants revealed the need for consistent, credible and culturally sensitive information on the health effects of certain foods. The preferred means of delivery include a website and/or seminars conducted in Chinese by healthcare professionals who are familiar with Chinese dietary preferences.
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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 | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".