Does a perception of increased blood safety mean increased blood transfusion? An assessment of the risk compensation theory in Canada
Bibliographic record
Abstract
BACKGROUND: The risk compensation theory is a widely used concept in transport economics to analyze driver risk behaviour. This article explores the feasibility of applying the theory in blood transfusion to raise important questions regarding the increased blood safety measures and their possible effects on blood usage (e.g., the appropriateness in transfusion). Further, it presents the findings of a pilot survey of physicians in Canada. DISCUSSION: While studies have attempted to define transfusion appropriateness, this article argues that if the risk compensation theory holds true for transfusion practice, physicians may actually be transfusing more. This may increase the possibility of contracting other unknown risks, such as the variant Creutzfeldt-Jakob Disease (vCJD), as well as increasing the risk of non-infectious transfusion risks, such as transfusion reactions. SUMMARY: A much larger study involving psychosocial assessment of physician decision making process to fully assess physician behaviour within the context of risk compensation theory and transfusion practice in Canada is needed to further explore this area.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".