Developing Student Evidence‐Based Practice Questionnaire (S‐EBPQ) for undergraduate nursing students: Reliability and validity of a Chinese adaptation
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: The assessment of evaluating undergraduate nursing students' evidence-based practice engagement is an important issue, yet few tools have been developed specifically in Mainland China. The purpose of this study was to adapt the Student Evidence-based Practice Questionnaire (S-EBPQ) to Mainland China's cultural context and to evaluate the psychometric properties of the newly adapted Chinese S-EBPQ. METHODS: Cross-cultural adaptation, including translation of the original S-EBPQ into Mandarin Chinese language, was performed according to published guidelines. A pilot study was conducted in Mainland China with 25 Chinese undergraduate nursing students. A subsequent validation study was conducted with 400 undergraduate nursing students from Mainland China. Construct validity was assessed by exploratory factor analysis (n = 190) and confirmatory factor analysis (n = 210). Reliability was determined using internal consistency and test-retest reliability. RESULTS: The split-half coefficient for the overall Chinese S-EBPQ was 0.858. A content validity index of 0.986 was achieved. Principal component analysis resulted in a 4-factor structure explaining 68.285% of the total variance. The comparative fit index was 0.927, and the root mean squared error of approximation was 0.072 from the confirmatory factor analysis. Known-group validity was supported by the significant differences according to various characteristics of participants. Internal consistency was high for the Chinese S-EBPQ reaching a Cronbach α value of 0.934. Test-retest reliability was 0.821. CONCLUSION: The newly cross-culturally adapted S-EBPQ possesses adequate validity, test-retest reliability, and internal consistency and therefore may be utilized in nursing education to assess EBP of undergraduate nursing students in Mainland China.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".