Evaluation of Best Practice Guidelines Implementation in an Undergraduate Nursing Curriculum
Bibliographic record
Abstract
This mixed methods study sought to understand the implementation of Registered Nurses Association of Ontario’s (RNAO) Best Practice Guidelines (BPGs) in the undergraduate nursing program in the State of Qatar. The RNAO has disseminated over 50 BPGs on clinical topics and on healthy work environment topics (Melnyk, 2015). All BPGs whether clinical or related to a healthy work environment, are developed to improve patient care and provide easy access to evidence-based research to students, instructors, and practicing nurses (Edwards et al., 2005). For this research, Yrjö Engeström’s (1987) Cultural Historic Activity Theory (CHAT) was selected due to its explanation of the interactions among various participants and factors within the activity system (or environment) towards the achievement of a common goal (Greig et al., 2012). The implementation and evaluation of the RNAO BPGs in the undergraduate nursing program in Qatar required an understanding of interactions and relationships among the various participants. CHAT enabled the researcher to examine these complex relationships. The participants’ experiences with the teaching and learning of RNAO BPGs were explored using a mixed methods approach. Quantitative methods included questionnaires, while qualitative methods consisted of interviews and document analyses. Both methods enabled the triangulation of the findings to gain an in-depth understanding of the RNAO BPGs implementation process. The findings showed that the integration of RNAO BPGs into the undergraduate nursing program successfully strengthened the curriculum through the intentional incorporation of evidence-based guidelines, though there were areas for improvement. Students and instructors were aware of the BPGs but needed more education to incorporate them efficiently and effectively. Moreover, the use of BPGs in courses as evidence-based tools was evident but lacked depth. The guidelines were perceived as lengthy, somewhat outdated, and not inclusive of all topics. However, there was also a lack of awareness among students and instructors regarding the status of updates to the guidelines. There was a perception of bias, with a focus on RNAO guidelines over other evidence-based guidelines and resources. Additionally, there were reports of actual and perceived cultural barriers due to the Western-based examples in some of the guidelines. On the other hand, the review of the guidelines revealed that it was explicitly mentioned to “use the guidelines if culturally appropriate”. The statements by students and some of the experiences shared by the instructors about cultural appropriateness could be interpreted as a sense of being “othered” and the need for the guidelines to be “read” as culturally appropriate. Due to time constraints, an evaluation of the impact of the BPGs on students’ application of guidelines in clinical practice could not be conducted. It is proposed to include an evidence- based practice (EBP) course and a scaffolded approach to integrate EBP teaching, learning, and assessment strategies. This approach is recommended to improve the integration, monitoring, and application of EBP in clinical practice courses using outcome indicators. While the findings are limited to students who participated in the research study, the recommendations will help the participating academic institution refine its strategies as it continues to monitor the implementation process. The findings may also benefit other academic institutions aiming to incorporate RNAO BPGs into their nursing curricula.
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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 | 0.089 | 0.148 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".