Sickle cell disease and the need for blood: Barriers to donation for African, Caribbean, and Black young adults in Canada
Bibliographic record
Abstract
BACKGROUND: Many blood operators around the world face the challenge of increasing the number of donors of African ancestry to meet the transfusion needs of people living with sickle cell disease. This article reports results of the barriers to blood donation for young adults (aged 19-35) in Canada who identify as African, Caribbean, or Black. STUDY DESIGN AND METHODS: A community-based qualitative study was conducted by researchers from community organizations, blood operator, and universities. In-depth focus groups and interviews (n = 23) were conducted from Dec 2021 to Apr 2022 and thematic analysis was completed. RESULTS: Applying a socio-ecological model, multiple levels of interacting barriers to blood donation were identified. These included macro-level barriers (e.g., systemic racism, mistrust of the healthcare system, sociocultural beliefs and views about blood and sickle cell disease), mezzo-level barriers (e.g., deferral criteria, minimum hemoglobin levels, donor questionnaire, access, parental concerns), and microlevel barriers (e.g., limited knowledge of blood needs for people with sickle cell disease, lacking information about blood donation process, fear of needles, personal health concerns). DISCUSSION: This study is the first to focus on barriers to donation for African, Caribbean, and Black young adults across Canada. Parental concerns, informed by parents' experiences of inequitable healthcare and mistrust, emerged as a novel finding in our study population. Results suggest that higher order (macro-level) barriers influence and may reinforce lower order (mezzo- and microlevel) barriers. As such, interventions aimed at addressing barriers to donation should keep in view all levels with particular attention paid to higher order barriers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".