Communication and language challenges experienced by Chinese and South Asian immigrant parents of children with cancer in Canada: Implications for health services delivery
Bibliographic record
Abstract
BACKGROUND: Language is an important aspect of health literacy and plays a vital role in families' ability to access and use health information and resources. Our study explored the role of communication and language in the healthcare experiences of immigrant parents of children with cancer living in Canada. PROCEDURE: We used a grounded theory approach. Chinese and South Asian parents of children 6 months post-diagnosis were recruited from six Canadian pediatric oncology centers. Semi-structured interviews were conducted in Cantonese, Mandarin, Hindi, Punjabi, Urdu, or English. Questions relevant to communication included: how parents navigated the healthcare system; nature of interpreter services and translated materials; and suggestions about how to improve services. Analysis involved line-by-line, focused and theoretical coding, and constant comparison. RESULTS: Thirty-one (62%) parents reported no difficulty communicating with healthcare providers in English, while 13 (26%) parents struggled with English, and six (12%) parents could not communicate in English. Communication challenges influenced parents' role in caring for their child and made it difficult to learn complex medical terminology. Interpreting services were sometimes inadequate or not accessible. Parents occasionally missed out on services and resources, reported limited availability of linguistically and culturally appropriate information, and experienced a lack of social integration in the healthcare process. CONCLUSION: Language ability played an essential role in parents' healthcare experiences for pragmatic and social purposes. Language challenges can heighten systemic and socio-cultural barriers to accessing health information and resources. The provision of enhanced culturally and linguistically sensitive services may support immigrant families in their caregiving role.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".