Determinants of return behavior: a comparison of current and lapsed donors
Bibliographic record
Abstract
BACKGROUND: There is a need to identify factors explaining why some people stop donating blood. STUDY DESIGN AND METHODS: A random mail survey of first-time (FT) and repeat (RPT) current (donating within 6 months before survey) and lapsed (donating >2 years prior) donors was conducted. The self-administered questionnaire included questions on personal, social, and behavioral characteristics. RESULTS: Among 1280 current and 1672 lapsed donors with valid addresses, the participation rate was 66.8 and 39.2 percent, respectively. In FT donors, the odds of lapsing increased with education (odds ratio [OR], 2.18; 95% confidence interval [CI], 1.34-3.55 for college or higher vs. Grade 12 or less education). Lapsed FT donors were more often asked to donate (OR, 1.89; 95% CI, 1.32-2.70) and had less interest in incentives (p < 0.001) than current FT donors. In RPT donors, lapsed status was associated with being younger (p < 0.001) and female (OR, 1.19; 95% CI, 1.00-1.42). Lapsed status was inversely associated with satisfaction with the last donation experience in both FT (p = 0.043) and RPT (p < 0.001) donors. Lapsed and current donors did not differ in perceived need for blood, personal transfusion experience, or mean reported altruistic behavior score. CONCLUSION: A positive donation experience appears to be a major determinant of donor return behavior. Lapsed donors do not appear, on average, to engage in fewer altruistic behaviors than currently active donors. Retention marketing strategies that appeal solely to altruistic values need to be further evaluated for their effectiveness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".