Sexual risk behavior questions: Understanding and mitigating donor discomfort
Bibliographic record
Abstract
BACKGROUND: Blood operators are working to improve donor screening and eligibility for gay, bisexual and other men who have sex with men (gbMSM), and trans and nonbinary donors. Many consider screening all donors for specific sexual risk behaviors to be a more equitable approach that maintains the safety of the blood supply. Feasibility considerations with this change include ensuring donor understanding of additional sexual behavior questions and minimizing donor loss due to discomfort. STUDY DESIGN AND METHODS: Qualitative one-on-one interviews were conducted with Canadian whole blood and plasma donors (N = 40). A thematic analysis was conducted to assess participants' understandings of the questions, examine their comfort/discomfort, and identify strategies to mitigate donor discomfort. RESULTS: All participants understood what the sexual behavior questions were asking and thought the questions were appropriate. Themes related to comfort/discomfort include: their expectations of donor screening, social norms that they bring to donation, whether their answer felt like personal disclosure, knowing the reasons for the question, trusting confidentiality, confidence in knowing their sexual partner's behavior, and potential for the question to be discriminatory. Strategies to mitigate discomfort include: providing an explanation for the questions, forewarning donors of these questions, reducing ambiguity, and using a self-administered questionnaire. CONCLUSION: While many blood operators and regulators view the move to sexual behavior-based screening for all donors as a significant paradigmatic shift, donors may not perceive additional sexual behavior questions as a significant change to their donation experience. Further research is needed to evaluate the effectiveness of strategies to mitigate donor discomfort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".