Donor understanding and attitudes about current and potential deferral criteria for high‐risk sexual behavior
Bibliographic record
Abstract
BACKGROUND: Few donor criteria are as contentious as the deferral of men who have had sex with men (MSM). We performed an anonymous donor survey to determine attitudes toward current screening and the feasibility and acceptability of adoption of alternate donor criteria for MSM. STUDY DESIGN AND METHODS: Donors who had successfully donated to Canadian Blood Services were randomly mailed an anonymous questionnaire several weeks after donation; there were 40,000 donors sampled, evenly split between first-time and repeat donors. RESULTS: The response rate was 45.5%. The vast majority of donors found the current screening questions and clinic environment acceptable. Attention to clinic educational materials was poor. A total of 53% felt that the MSM criteria should be changed; many were supportive of criteria based on specific behaviors rather than a period of abstinence. Gender-neutral questions such as number of sexual partners would result in deferral of large numbers of donors. CONCLUSION: Many donors would support a change in MSM deferral policy. Implementation of strategies based on donor attention to additional material would be challenging. Universal use of simple gender-neutral questions would result in very high donor loss and are therefore not an acceptable option. The acceptability and feasibility of various screening approaches should be explored further with both donors and advocacy groups.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".