Factors influencing blood donations and the rational use of blood.
Bibliographic record
Abstract
A multicentric quasi-experimental study was conducted in Delhi, from March 2007 to September 2007, on i) the factors which stimulate the donors to donate blood, ii) major barriers and myths associated with blood donation and iii) clinicians perception of the rational use of blood. The study design included a face-to-face survey, with a pre-tested questionnaire paper in two leading blood banks of Delhi and by relevant interviewers from the community and medical fraternity. The sample size was 240-blood donors from two different blood banks and the control group included 100 potential donors from community and 50 clinicians from various hospitals. The data generated was analyzed using excel sheet and Epi-Info software. The study revealed the factors which influence the blood donation included replacement credit and family/peer pressure. Regarding myths and barriers, among potential donors, about a quarter of them felt that it is time consuming, and 20% felt it could lead to sexual impairment or is not rewarding. A total of 10% were not aware about the blood donation while 15% said that donation time was inconvenient. Of the 50 clinicians, a quarter of them were not aware of the rational use of blood.
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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 | 0.005 | 0.014 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".