Increasing nondonors’ intention to give blood: addressing common barriers
Bibliographic record
Abstract
BACKGROUND: Recruiting new donors is a challenging experience for most blood collection agencies. A modest proportion of the population is eligible to give blood and few of these individuals volunteer. The goal of this study was to examine the effects of brief behavioral interventions on nondonors' intention to give blood, by addressing some commonly reported obstacles. STUDY DESIGN AND METHODS: A total of 244 young adults who were eligible to give blood but had never done so participated in the study. They were assigned randomly to an applied tension (AT) instruction condition, a relaxation instruction condition, a Web browsing condition, or a no-treatment control condition. After the 20-minute experimental intervention, half watched three short injection and blood draw videos and the others sat quietly. Intention to give blood and different cognitive constructs associated with blood donation were measured using a Theory of Planned Behavior questionnaire. RESULTS: Participants in all three active conditions had significantly greater increases in intention to donate blood compared to controls, although those who learned AT had greater increases than Web browsing. Bootstrapping tests of mediation indicated particular importance of increased perceived behavioral control in AT and relaxation treatment effects. Follow-up analyses revealed a significant association between degree of within-session increase in intention and subsequent blood clinic attendance. CONCLUSION: These results suggest that simple interventions can be effective in increasing nondonors' intention to donate blood and, perhaps, actual attendance. The mediational analyses suggest that interventions can selectively target different barriers associated with blood donation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 teacher head, 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".