Assessing the cognition, attitudes and intentions of volunteers regarding unrelated peripheral blood stem cell donation: The UPBSC-DQ instrument in Chinese
Bibliographic record
Abstract
Objectives This study aimed to develop and validate the Unrelated Peripheral Blood Stem Cell Donation Questionnaire (UPBSC-DQ) (an instrument in Chinese) to assess the degree of cognition, attitude and intention of enrolled volunteers towards UPBSC donation. Methods The development process of the UPBSC-DQ was performed in a stepwise approach that included extensive literature retrieval, expert revision, and pretesting with 442 students. We conducted an online cross-sectional survey using the final version of the UPBSC-DQ among 336 participants. The reliability of the questionnaire was assessed by Cronbach's α and corrected item-total correlation (CITC), and the validity was evaluated by a correlation coefficient matrix, confirmatory factor analysis (CFA), and t -test. Results The UPBSC-DQ consists of four domains: basic information, cognitive, attitude, and intention. The Cronbach's α values were 0.88 and 0.86 for the attitude and intention scales, respectively, indicating strong internal consistency and good reliability. Correlation analysis and CFA showed good structure and content validity. Interitem correlations indicated that each item had only a weak correlation with the other scales. Conclusions The UPBSC-DQ is a reliable and valid assessment questionnaire for individuals' attitudes and intentions towards UPBSC donation. The questionnaire showed good to high reliability, content and construct validity.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".