Psychometric properties of the research competencies assessment instrument for nurses (RCAIN) in Greece
Bibliographic record
Abstract
Background and Purpose: Evidence-based practice can improve quality of care and patient and system outcomes. Healthcare professionals need certain research competencies to achieve evidence-based practice. We aimed to evaluate the psychometric properties of the self-reported 19-item Research Competencies Assessment Instrument for Nurses (RCAIN) with Greek. Methods This cross-sectional study included in total, 520 respondents (within 33 health organizations) who completed the 5-point Likert-type RCAIN as well as the 8-item " Research Utilization by Nurses " that was used to assess construct validity. Expert scholars translated both survey questionnaires into the Greek language. A baseline one-factor model was compared against three-factor model (i.e., knowledge, skills, and application of knowledge and skills) that were developed based on the hypothetical design of the instrument. Results Participants were females (86.4%) 50 years old or younger (91%). The RCAIN had a Cronbach's alpha coefficient of 0.937 and intraclass correlation coefficient of 0.440 (95% CI 0.403 to 0.480, p < .001). Confirmatory factor analysis revealed a 3-factor solution (i.e., knowledge, skills, application of knowledge & skills). Fit indices for the three-factor model were statistically superior when compared with the baseline model. Reliability and validity of each subscale were acceptable. Further assessment of construct validity using hypothesis testing indicated that there is a statistically significant difference in research utilization by knowledgeable or not participants. Specifically, the effect size between knowledge synthesis and instrumental research use was eta squared = 0.020, meaning that approximately 2.0% of the variance in instrumental research use scores can be explained by knowledge in methods of knowledge synthesis. The predictive validity, based on correlations between the two instruments, showed that increasing levels of instrumental research use were associated with an increasingly positive and statistically significant pattern of correlations. Conclusions The RCAIN survey is a psychometrically sound tool for nurses. Providers, educators, and health administrators may use it for professional development and improvement of individual research competencies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".