Psychometric properties of the Blood Donation Reactions Inventory: a subjective measure of presyncopal reactions to blood donation
Bibliographic record
Abstract
BACKGROUND: Presyncopal reactions are among the most common systemic reactions experienced by blood donors, occur most frequently in novice donors, and can serve as a deterrent to future donation regardless of donation experience. This report describes the validation of a presyncopal reactions scale that can be used to standardize assessment of the donor's subjective experience. STUDY DESIGN AND METHODS: A psychometric analysis of the Blood Donation Reactions Inventory (BDRI), a measure of presyncopal reactions, was conducted using data obtained from two independent samples of volunteer blood donors. Based on these analyses, a new, brief version of the BDRI is proposed, and psychometric data regarding the reliability and construct validity of this instrument are presented. RESULTS: Results of confirmatory factor analyses indicate that a 4-item version of the BDRI can be used to assess subjective perception of mild, prefaint symptoms. Additional analyses indicate that the BDRI has good internal consistency and demonstrates concurrent validity relative to other indices of donor reactions (e.g., donor chair reclines and loss of consciousness). Construct validity is supported by factor analyses, expected score differences in different donor groups, and convergent validation against measures of donor satisfaction and likelihood of repeat donation. CONCLUSION: The BDRI provides an assessment of subjective ratings of presyncopal symptoms that is brief, easily understood by donors, and quick to administer and score. The BDRI yields important information about the donor's experience that can be used to predict satisfaction and likelihood of repeat donation.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".