Development and evaluation of stem cell collection procedure diagrams to support the education and recruitment of committed stem cell donors
Bibliographic record
Abstract
BACKGROUND: Diagrams which allow potential unrelated stem cell donors to visualize the stem cell collection process were hypothesized to support the recruitment and education of committed stem cell donors. STUDY DESIGN AND METHODS: A series of bone marrow and peripheral blood stem cell collection procedure diagrams were developed, featuring young adult male donors of varied ethnic backgrounds. Post-implementation, surveys were conducted to evaluate stakeholder perspective on the diagrams' utility. A quality improvement project was conducted at five stem cell drives from 2017 to 2018 at which recruiters did or did not show the diagrams to potential donors. Following the drives, registrants were invited to complete a survey exploring their experience, knowledge and attitude towards donation. RESULTS: The diagrams were implemented in Canada in 07/2016. Of 293 participating registrants (24·7% non-Caucasian males) recruited at five drives between 2017 and 2018, 76% (n = 197) were shown the diagrams. Participants who were shown the diagrams were significantly more likely to report that the recruiters appeared very knowledgeable (89% vs. 76%, P = 0·019) and to report improved self-reported knowledge of stem cell donation (P = 0·010) compared to participants not shown the diagram. Data are also shown demonstrating that stakeholders in donor recruitment used and valued the diagrams and that use of the diagrams was associated with improved donor recruitment outcomes in Canada. CONCLUSION: This report is the first evaluation of stem cell collection diagrams in the literature. The diagrams are relevant to donor registries, recruitment organizations and transplant centres worldwide, and their use may support efforts to educate and recruit committed, ethnically diverse donors.
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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 | 0.044 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".