Comparison of donor and general population demographics over time: a BEST Collaborative group study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: We compared donor and general population demographics over time to provide insight into current donation patterns and the future adequacy of the blood supply. STUDY DESIGN AND METHODS: Seventeen blood center members of the Biomedical Excellence for Safer Transfusion (BEST) Collaborative from 12 countries provided the number of donors and people in the general population by demographic category for 2001 and 2011, changes in age criteria, and percentage of first-time donors. We calculated the median age of donors and the general population and determined the percentage of each group in age and sex cohorts. RESULTS: Age criteria vary, with upper limits recently liberalized in several countries. In 2011, the percentage of first-time donors ranged from 10% to 41%. The median age of the donor and general population increased from 2001 to 2011 in most countries, as did the percentage of the general population over 60. The youngest donor cohort is overrepresented to a variable degree; this tendency increased over time. Although still underrepresented, older donors contributed more in 2011. A large middle-aged cohort is aging at a rate exceeding the progression of time, while 25- to 45-year-olds are relatively underrepresented. CONCLUSIONS: All participating countries are experiencing aging of their general population. Donor demographics differ substantially between countries; this can be only partly explained by population demographics and age criteria. Many countries have an aging middle-aged donor and population cohort and are increasingly relying on their youngest donors to contribute disproportionately to the blood supply.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it