The relative efficacy of three interventions to favour return to give blood.
Bibliographic record
Abstract
BACKGROUND: The aim of the study was to test the relative efficacy of action planning and reward distribution to promote retention of whole blood donors. MATERIALS AND METHODS: A sample of 7,399 donors was randomised to one of three interventions: "action planning" (n=2,585); "reward" (n=2,397); and "thank you" (n=2,417). Participants in the action planning condition were invited to write the date of their next donation on a post-it note before taking it home at the end of the donation process. Participants in the "reward" condition were given an anti-theft credit card sleeve at the end of the donation process. The "thank you" intervention is the usual condition at the end of the process; it was considered the control condition. The dependent variable was the proportion of donors who registered to give blood at six months. RESULTS: Overall, 4,444 (60.06%) donors registered to give blood at six months. There were no differences between the three interventions in the proportions of donors who registered to give blood (d.f. 2, chi-square=3.72, p<0.15). However, gender modified the effect of the intervention (d.f. 2, chi-square=6.57, p<0.0375); more women registered in the "thank you" condition than in the other two. DISCUSSION: The results suggest that action planning and the distribution of a reward have no motivational effect on the return to give blood. Nonetheless, women appear to respond more negatively to these interventions at the end of the donation 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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".