Finnish graduating nursing students’ research utilization competence
Bibliographic record
Abstract
In nursing, research utilization (RU) is a core competence for evidence-based practice (EBP). During the past fifteen years, a great deal of effort has been expended worldwide in nursing higher education to promote EBP. This study explores graduating nursing students’ RU competence in Finland using a descriptive cross-sectional, long-term survey design with two cohorts of nursing students in 2003 (n = 529) and 2012 (n = 259). Data were collected with a Competence in Research Utilization instrument, and analyzed statistically. In both cohorts, students’ attitudes towards RU were positive, but their knowledge and skills were low to moderate. Students’ RU competence was higher in 2003 compared to 2012. There is a need to develop nursing education strategically, and by seeking suitable pedagogical methods and curriculum contents to support the learning of RU. In higher education, educational cooperation and longitudinal learning outcome evaluations are recommended.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".