Differences in social representation of blood donation between donors and non-donors: an empirical study.
Bibliographic record
Abstract
BACKGROUND: Both donors and non-donors have a positive image of blood donation, so donors and non-donors do not differ regarding their views on donation but do differ in converting their opinion into an active deed of donation. Several studies have identified altruism and empathy as the main factors underlying blood donation. However, a mixture of various motivational factors mould the complex behaviour of donation. This paper presents an exploratory study on differences of social representations of blood donation between blood donors and non-donors, in order to understand the reasons that bring someone to take the decision to become a blood donor. MATERIALS AND METHODS: Participants filled in the Adapted Self-Report Altruism Scale, Toronto Empathy Questionnaire and answered a test of verbal association. Descriptive and correlation analyses were carried out on quantitative data, while a prototypic analysis was used for qualitative data. RESULTS: The study was carried out on a convenience sample of 786 individuals, 583 donors (mean age: 35.40 years, SD: 13.01 years; 39.3% female) and 203 non-donors (mean age: 35.10 years, SD: 13.30 years; 67.5% female). Social representations of donors seem to be more complex and articulated than those of non-donors. The terms that appear to be central were more specific in donors (life, needle, blood, help, altruism were the words most associated by non-donors; life, aid, altruism, solidarity, health, love, gift, generosity, voluntary, control, needed, useful, needle were the words most associated by donors). Furthermore, non-donors associated a larger number of terms referring to negative aspects of blood donation. DISCUSSION: Aspects related to training and the accuracy of any information on blood donation seem to be important in the decision to become a donor and stabilise the behaviour of donation over time, thus ensuring the highest levels of quality and safety in blood establishments.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".