Determinants of repeated blood donation among new and experienced blood donors
Bibliographic record
Abstract
BACKGROUND: The maintenance of a safe level of blood supply is provided by a small number of volunteers, and their retention is difficult. The aim of this study was to identify factors predicting repeated blood donation among experienced and new donors. STUDY DESIGN AND METHODS: A random sample of 2,231 donors (2,070 experienced and 161 new) completed a questionnaire assessing psychosocial factors as defined by the most prominent social cognitive theories. Six months later, an objective measure of frequency of registrations to give blood was obtained from the database of the local official agency for blood donation. RESULTS: Logistic regression analysis indicated that for experienced donors, the predictors were intention, perceived control, anticipated regret, moral norm, age, and frequency of blood donation in the past. For new donors, intention and age were the only determinants of behavior. Important differences in the determinants of intention were also noted between experienced and new donors. CONCLUSION: In summary, the results of this study support the idea that distinct promotion strategies should be adopted to increase repeated blood donation among experienced versus new donors.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".