Culturally Safe Care Barriers and Facilitators in Organ Transplantation and Donation According to First Nations and Health Professionals in Quebec, Canada
Bibliographic record
Abstract
Introduction: First Nations are most at risk of developing end-stage kidney disease. Kidney transplantation is the best treatment option for these patients; however, First Nations donors are underrepresented. The aim of this study was to describe and understand barriers and facilitators of culturally safe organ transplantation and donation from the perspective of First Nations and Health Professionals in the Province of Quebec, Canada. Methods/Approach: This was a qualitative descriptive study using the decolonizing Two-Eyed Seeing approach. The sample consisted of First Nations people and health professionals living in Quebec, Canada, who have had an experience of organ transplantation or donation. Semi-structured interviews were conducted between May and September 2021 with 11 people, including 5 healthcare professionals and 6 First Nations people. Findings: This study enrolled 11 participants. Several individual and contextual factors influencing culturally safe organ transplantation and donation among First Nations people were identified: language barrier, impacts of relocation, lack of knowledge about transplantation, mistrust of the healthcare system, family support and accompaniment, and transplant testimonials. Discussion: This study identified several avenues for reinforcing culturally safe transplantation and donation among First Nations, including the presence of a companion in medical consultations, focusing on access to culturally safe accommodation and sharing transplant testimonials. Further work in partnership with First Nations is needed to improve access to culturally safe organ transplantation
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".