Determinants of the intention to participate in a programme of plasma donation for fractionation among men who have sex with men
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Several approaches are currently under study to contribute to efforts to allow men who have sex with men (MSM) to donate blood. One of these approaches involves implementing a programme of plasma donation for fractionation, with a quarantine period. The goal of this article is to identify the determinants of intention to participate in the plasma donation programme among MSM in Montreal, Canada. MATERIALS AND METHODS: Based on the theory of planned behaviour, a questionnaire was developed to measure MSM's intention to donate plasma and identify influencing factors. A multiple linear regression analysis was conducted to identify the determinants of intention to donate plasma. RESULTS: Respondents' (N = 933) intention to donate plasma in the next six months was moderate. The multiple linear regression model explained 55% (P < 0·001) of the variation of intention. Intention was predicted by attitudes (β = 0·34, P < 0·001), perceived behavioural control (β = 0·28, P < 0·001), aged under 35 years (β = 0·26, P < 0·001), history of blood donation (β = 0·24, P < 0·001), subjective norm (β = 0·21, P < 0·001), income above $40,000 (β = 0·20, P < 0·001), moral norm (β = 0·18, P < 0·001) and higher level of involvement in various issues LGBTQ+ communities are fighting for (β = 0·09, P < 0·001). CONCLUSION: Our analyses show that intention to donate plasma within the proposed programme is associated with personal, social and structural factors, but more strongly predicted by factors related to the theory of planned behaviour. Our results also highlight the importance of involving MSM; community acceptability of the plasma donation programme would probably be higher if MSM felt respected and party to the decisions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".