Expertise practice of clinical transplant coordinators in Japan
Bibliographic record
Abstract
Objective: This study aimed to describe the expertise practice of nurse clinical transplant coordinators (CTCs) in organ transplantation medical care.Methods: To present the expertise practices of CTCs, we conducted a qualitative descriptive study using semistructured interviews. We performed an analysis according to analytical methods from the (Modified) Grounded Theory Approach (M-GTA) proposed by Kinoshita.Results: The expertise practice of CTCs was associated with 14 categories: [conscious communication toward compromise], [observation to understand actual intention], [conversation content that quickly notices the other’s reaction and changes], [engaging so that patients and families do not have regrets after a transplantation], [provide support for the self-determination process and advocate the decision], [autonomous judgment and timely response while assessing patient conditions], [coordination in response to changes in conditions], [assertive communication with physicians], [care that is aware of team medicine], [mediate to build trust between patients/families and medical staff], [long-term care as a permanent primary], [promoting self-monitoring by grasping the timing of guidance], [stepping forward to solve problems], and [evaluate their own ability appropriately and have humble attitude].Conclusions: CTC in Japan demonstrates expertise practice with decision support during transplant selection, coordination during the transplant process, and long-term continuing care. In addition, this study highlighted that CTCs in Japan had been conducting autonomous practice as a nurse and providing comprehensive care including patients, family members, and living donors. Our results clarified the experienced CTC’s expertise practices in all organ transplants and can be used to improve and assess the quality of care given by Japanese CTCs in the transplant process.
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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 | 0.003 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".