Organ Donation and Transplantation: A Survey of Critical Care Health Professionals in Nontransplant Hospitals
Bibliographic record
Abstract
Context Exploration of the role of critical care professionals in improving organ donation within Canada has been limited to tertiary care centers while donor potential in smaller nontransplant hospitals remains unknown. Objective To gain an understanding of the knowledge, attitudes, and perceived barriers that healthcare professionals in 5 nontransplant hospitals in Alberta have toward organ donation and transplantation, and to identify factors that influenced participation in the donation process. Design A descriptive survey of critical care professionals. Setting Five nontransplant hospitals in Alberta, Canada. Results Of the 135 respondents, 98 were critical care nurses, 32 were physicians, and 5 were hospital administrators. Respondents were least knowledgeable about transplant statistics and religious beliefs regarding donation, although overall, attitudes reflected positive support for organ donation. Respondents exhibited reluctance in approaching a potential donor family, and believed inadequate resources were allocated for organ donation. Conclusions Educational programs are needed to increase knowledge of organ donation and transplantation as well as the development of an in-house coordinator program in nontransplant hospitals for critical care personnel.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".