Behavioral economics—A framework for donor organ decision‐making in pediatric heart transplantation
Bibliographic record
Abstract
The high discard rate of pediatric donor hearts presents a major challenge for children awaiting heart transplantation. Recent literature identifies several factors that contribute to the disparities in pediatric donor heart usage, including regulatory oversight, the absence of guidelines on pediatric donor heart acceptance, and variation among transplant programs. However, a likely additional contributor to this issue are the behavioral factors influencing transplant team decisions in donor offer scenarios, a topic that has not yet been studied in detail. Behavioral economics and decision psychology provide an excellent foundation for investigating decision-making in the pediatric transplant setting, offering key insights into the behavior of transplant professionals. We conducted a systematic review of published literature in pediatric heart transplant related to behavioral economics and the psychology of decision-making. In this review, we draw on paradigms from these two domains in order to examine how existing aspects of the transplant environment, including regulatory oversight, programmatic variation, and allocation systems, may precipitate potential biases surrounding donor offer decisions. Recognizing how human decision behavior influences donor acceptance is a first step toward improving utilization of potentially viable pediatric donor hearts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".