A Multidisciplinary Survey to Assess Facilitators and Barriers to Successful Organ Donation in the Intensive Care Unit
Bibliographic record
Abstract
INTRODUCTION: Rates of successful organ donation vary between otherwise comparable intensive care units (ICUs). The ICU staff have a unique perspective into the facilitators and barriers underlying this variation in successful deceased organ donation. RESEARCH QUESTION: What do ICU staff perceive to be the most meaningful facilitators and barriers to deceased organ donation? DESIGN: We designed and conducted a survey of all disciplines working in the ICU to ascertain the perceived facilitators and barriers to donation in an academic tertiary care hospital. Survey reliability was assessed using Cronbach α. Factor analysis was used to assess construct validity and identify potentially redundant survey items. RESULTS: We had responses from 108 ICU staff, including nurses (n = 75), respiratory therapists (n = 14), physicians (n = 12), chaplains (n = 2), as well as social work, pharmacy, physiotherapy, and occupational therapy (n = 1 each). Perceived facilitators included availability of organ donation organization coordinators, explicit institutional support for donation, ICU staff culture toward donation, standardized order sets for donation, presence of ICU staff with donation experience, and bedside nurse presence at discussions about donation. Perceived barriers included ICU staff ruling out potentially suitable donors before consulting a donor coordinator, physician communication skills, low priority for organ donation among operating room staff, limited family understanding of patient prognosis and organ donation, and limited emotional readiness of families to discuss donation. DISCUSSION: Several staff-perceived facilitators and barriers to deceased organ donation were identified in the ICU. Future research could identify strategies to promote these facilitators and overcome barriers.
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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 | 0.004 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".