What a Hug Does: A Qualitative Study of Chinese Immigrant Families’ Experiences with Inpatient Palliative Care Specialists
Bibliographic record
Abstract
Background: Compared with non-Chinese adults in high-income countries, ethnically Chinese patients are more likely to encounter palliative care (PC) closer to death and in hospital settings. Yet, Chinese families' experiences and perception of inpatient PC remain unknown. Objective: Identify barriers and facilitators to culturally respectful PC for Chinese immigrant inpatients and their caregivers. Design: Prospective, exploratory qualitative design involving phenomenological interviews. Setting/Subjects: = 10) in Mandarin and/or English. The interviews were recorded, transcribed, translated, and thematically analyzed using Tan's Health Communication framework. Results: Patients were older-aged (mean = 73.5 ± 16.2 years), 53.3% female, 60% college-educated, 66.7% nonreligious, and 93.3% diagnosed with cancer and had low acculturation (mean = 1.8 ± 0.9/5.0). Caregivers were middle-aged (mean = 50.6 ± 15.5 years), 78.6% children, 57.1% female, 85.7% college-educated, and 71.4% nonreligious and had moderate acculturation (mean = 2.5 ± 1.2/5.0). We identified four themes from post-consultation interviews: abandonment and alienation mark past experiences with serious illness care; emphasizing expertise and symptom relief may help overcome initial ambivalence toward PC; PC brokers competing priorities within the family unit; and PC alleviates time-related distress by addressing illness understanding. Conclusion: Chinese patients and caregivers may prefer a PC approach that is sensitive to historical mistrust, leverages expertise in symptom management to inspire confidence, and accommodates the information and care preferences of the family unit. Further research is needed to examine the impact of these PC strategies on clinical outcomes for Chinese families.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".