Implementation strategies to improve evidence-based practice for post-stroke dysphagia identification and management: A before-and-after study
Bibliographic record
Abstract
Objectives: Even though guidelines are available to guide dysphagia identification and management practice, there is still a gap between evidence and practice, which requires improvement. The purpose of this study was to determine the effect of using tailored, multifaceted strategies to improve evidence-based post-stroke dysphagia identification and management practice in a community hospital. Methods: Guided by the Knowledge to Action framework, the tailored, multifaceted strategies were developed and implemented for 5 months in a community hospital using a before-and-after study design. These strategies consisted of training intervention, policy intervention, and audit and feedback intervention. Nurses' level of knowledge and adherence, were collected in March 2019 and again in January 2020. Patients' quality of life and satisfaction were evaluated during the pre-intervention period (between February 2019 and April 2019) and the post-intervention period (between November 2019 and January 2020). Results: A total of 55 patients with post-stroke dysphagia (28 in the pre-intervention period and 27 in the post-intervention period) and 17 registered nurses were recruited. Following implementation, there were statistically significant improvements in patients' outcomes (quality of life and satisfaction) and nurses' outcomes (level of knowledge and adherence). Conclusions: This study assists in closing the research-practice gap by using tailored, multifaceted strategies to increase the use of evidence-based nursing care for dysphagia identification and management practices.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".