Knowledge, attitudes, and practices toward blood donation in the Gaza Strip, Palestine
Bibliographic record
Abstract
Aims: Both developing and developed countries are facing difficulties in finding regular donors. In areas that are exposed to frequent conflicts and wars, such as the Gaza Strip, there is a need for a continuous blood supply. This study aims to determine the level of knowledge, attitudes, and practices toward blood donation in the Gaza Strip, Palestine. Methods: A cross-sectional study was conducted in 2022, in which 1506 participants were randomly selected from different governorates in the Gaza Strip. A structured and valid questionnaire was employed to assess the level of knowledge, attitudes, and practices toward blood donation. All statistical analyses were performed using SPSS version 28. The chi-square test was used to measure the significance of associations. Results: A total of 1506 individuals living in the Gaza Strip participated. The total mean score of the overall knowledge and positive attitudes toward blood donation was 55.1% and 67.1%, respectively. Furthermore, 1236 (82.1%) of the study participants never donated blood. Of them, 260 (21.0%) demonstrated that they do not have information on when, where, and how to donate; 228 (18.4%) thought that they were not fit to donate; 187 (15.1%) demonstrated that they did not have time to donate; 143 (11.6%) feared health problems, and 132 (10.7%) feared anemia. On the contrary, 99 (36.7%) donated blood when a friend or relative needed blood, and 171 (63.3%) were voluntary donations. Statistically, a significant association was found between knowledge, attitudes, practices, and sociodemographic variables ( p < 0.05 for all). Discussion: The study findings indicated poor donation habits despite positive attitudes toward blood donation in the Gaza Strip, Palestine. This research emphasizes the need to recognize and correct the knowledge gap that results in unfavorable behaviors against blood donation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".