Self-reported and objectively assessed knowledge of evidence-based practice terminology among healthcare students: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Self-reported scales and objective measurement tools are used to evaluate self-perceived and objective knowledge of evidence-based practice (EBP). Agreement between self-perceived and objective knowledge of EBP terminology has not been widely investigated among healthcare students. AIM: The aim of this study was to examine agreement between self-reported and objectively assessed knowledge of EBP terminology among healthcare students. A secondary objective was to explore this agreement between students with different levels of EBP exposure. METHODS: Students in various healthcare disciplines and at different academic levels from Norway (n = 336) and Canada (n = 154) were invited to answer the Terminology domain items of the Evidence-Based Practice Profile (EBP2) questionnaire (self-reported), an additional item of 'evidence based practice' and six random open-ended questions (objective). The open-ended questions were scored on a five-level scoring rubric. Interrater agreement between self-reported and objective items was investigated with weighted kappa (Kw). Intraclass correlation coefficient (ICC) was used to estimate overall agreement. RESULTS: Mean self-reported scores varied across items from 1.99 ('forest plot') to 4.33 ('evidence-based practice'). Mean assessed open-ended answers varied from 1.23 ('publication bias') to 2.74 ('evidence-based practice'). For all items, mean self-reported knowledge was higher than that assessed from open-ended answers (p<0.001). Interrater agreement between self-reported and assessed open-ended items varied (Kw = 0.04-0.69). The overall agreement for the EBP2 Terminology domain was poor (ICC = 0.29). The self-reported EBP2 Terminology domain discriminated between levels of EBP exposure. CONCLUSION: An overall low agreement was found between healthcare students' self-reported and objectively assessed knowledge of EBP terminology. As a measurement tool, the EBP2 Terminology scale may be useful to differentiate between levels of EBP exposure. When using the scale as a discriminatory tool, for the purpose of academic promotion or clinical certification, users should be aware that self-ratings would be higher than objectively assessed knowledge.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".