What influences decisions to donate plasma? A rapid review of the literature
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Plasma has become an essential ingredient for various medical treatments. Many blood collection agencies rely on voluntary non-remunerated donation when collecting plasma, but at present many do not collect sufficient plasma to meet domestic demands. This rapid review sought to explore the factors that have been found to influence people's decisions to donate plasma to inform future research. METHODS: Searches were conducted in PubMed, PsycINFO, Social Sciences Citation Index and CINAHL for peer-reviewed journal articles that discussed plasma donation and the factors associated with donor behaviour. Pertinent information from included articles was extracted and arranged in themes. RESULTS: In total, 33 articles were included in this review. Three main themes were identified by the authors. The first focused on site-level factors related to blood collection agencies' engagement with plasma donors and their influence on plasma donation experiences. The second theme considered how individual characteristics and experiences influence willingness to donate plasma. The third theme examined social and cultural-level factors, such as how social networks and community shape perceptions and experiences with donation. CONCLUSION: Our findings suggest that the current understanding of plasma donation is focused mainly on converting whole blood donors and also centres on individual-level factors to donation. Further research must examine what factors attract non-whole blood donors to become plasma donors, focusing on broader social-level influences. This review will inform policies and interventions for blood collection agencies to increase plasma donors.
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 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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".