Gay and bisexual men’s views on reforming blood donation policy in Canada: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Researchers and activists have long called for changes to blood donation policies to end what is frequently framed as unjustified bans or deferral periods for men who have sex with men (MSM). Since 2016, in Canada, a man had to be abstinent from all sexual contact (anal or oral sex) with other men for at least 12 months in order to be an eligible blood donor. As of June 3, 2019, this deferral period was reduced to 3 months. METHODS: To better understand the acceptance of existing deferral policies and possible future policy, we conducted 47 in-depth interviews with a demographically diverse sample of gay, bisexual, queer, and other men who have sex with men (GBM) in Canada's three largest cities: Vancouver, (n = 17), Toronto (n = 15), and Montreal (n = 15). Interviews were coded in NVivo 11 following an inductive thematic analysis. We focus on men's preferred policy directions and their opinions about a policy change proposed by Canada's blood operators: a 3-month deferral for all sexual activity between men. We interviewed GBM approximately one-year before this new deferral policy was approved by Health Canada. RESULTS: Most participants were opposed to any deferral period in relation to MSM-specific sexual activity. A fair and safe policy was one that was the "same for everyone" and included screening for several risk factors during the blood donation process with no categorical exclusion of all sexually active MSM. Participants believed that multiple "gender blind" and HIV testing-related strategies could be integrated into the blood donation process. These preferences for a move away from MSM-specific exclusions aligned with their opinions concerning the possible change to a 3-month MSM deferral, for which participants shared three overarching perspectives: (1) step in the right direction; (2) ambivalence and uncertainty; and (3) not an improvement. CONCLUSION: A predominant assertion was that a change from a 12-month to a 3-month deferral period would not resolve the fundamental issues of fairness and equity affecting blood screening practices for GBM in Canada. Many participants believed that blood donation policy should be based on more up-to-date scientific evidence concerning risk factor assessment and HIV testing.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.033 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".