Evaluation of attitudes and barriers toward blood donation in volunteer blood donors in Mashhad city (Northeast of Iran)
Bibliographic record
Abstract
Background: Blood transfusion services are responsible for providing blood products. Knowing the parameters that affect people’s decision to donate blood will help respond to this demand. This study was designed to assess the attitudes and barriers toward blood donation among volunteer donors in Mashhad (Northeast of Iran) during 2014-2015. Methods: This cross-sectional study was performed in Iranian Blood Transfusion Organization centers in Mashhad. A total of 640 volunteer blood donors, including first-time and frequent donors, attended this study. The questionnaire was designed based on similar studies, and the reliability and validity were controlled. A questionnaire consisting of multiple-choice questions was provided to the participants. SPSS software was used for data analysis. The Student’s t-test was used, and P<0.05 was considered significant. Results: Among the 640 participants, 80% completed and returned the questionnaire. Of the participants, 474 (92.5%) were male and 38 (7.4%) were female. A total of 114 donors were first-time donors, and the others had donated blood before. The most important motivations for blood donation included altruism: 249 (91.88%) among frequent donors and 76 (85.40%) among first-time donors. Other factors such as social influences also played a role. Lack of time (73.80%) was the most important barrier to blood donation among the first-time donors. Conclusion: The results showed that the most important motive and barrier for blood donation were altruism and lack of time, respectively. In other words, paying attention to the motivations and barriers of blood donation can play an important role in attracting and retaining blood 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".