Understanding Elderly Chinese Cancer Patients in a Multicultural Clinical Setting: Embracing Mortality and Addressing Misperceptions of Vulnerability
Bibliographic record
Abstract
Chinese patients face higher risks of gastrointestinal (GI) cancers and greater cancer-related deaths than Canadian-born patients. The older population encounters barriers to quality healthcare, impacting their well-being and survival. Previous studies highlighted Chinese immigrant perceptions of not requiring healthcare support. During the COVID-19 pandemic, their underutilization of healthcare services garnered attention. The present study explores the experiences of older Chinese cancer patients to improve culturally sensitive cancer care. A total of twenty interviews carried out in Cantonese and Mandarin were conducted with Chinese immigrants, aged 60 or above, diagnosed with Stage 3 or 4 GI cancer. These interviews were transcribed verbatim, translated, and subjected to qualitative descriptive analysis. Among older Chinese immigrant patients, a phenomenon termed "Premature Acceptance: Normalizing Death and Dying" was observed. This involved four key themes: 1. acceptance and letting go, 2. family first, 3. self-sufficiency, and 4. barriers to supportive care. Participants displayed an early acceptance of their own mortality, prioritizing family prosperity over their own quality of life. Older Chinese patients normalize the reality of facing death amidst cancer. They adopt a pragmatic outlook, acknowledging life-saving treatments while willingly sacrificing their own support needs to ease family burdens. Efforts to enhance health literacy require culturally sensitive programs tailored to address language barriers and differing values among this population. A strengths-based approach emphasizing family support and practical aspects of care may help build resilience and improve symptom management, thereby enhancing their engagement with healthcare services.
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 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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".