Nurses’ self-efficacy and knowledge: A pre- and post- study on reeducation for patient self-management of Type 2 diabetes mellitus
Bibliographic record
Abstract
Introduction: Type 2 Diabetes Mellitus (T2DM) is a chronic health condition with the potential for poor health outcomes that can be limited by good patient education and self-management approaches. Nurse-led diabetes self-management education (DSME) can reduce hospitalizations, support optimal blood glucose levels, and lower hemoglobin A1C. The goal of this study was to establish and maintain expertise for long term care (LTC) facility nurses in DSME. The project's purpose was to determine whether DSME increases LTC nurse knowledge about T2DM management, and whether it increases self-efficacy of LTC nurses to deliver DSME discharge training.Methods: This project utilized a quasi-experimental prospective comparative pre and posttest design to examine the effect of DSME training for licensed practical and registered nurses practicing in Chicagoland LTC facilities. Knowledge was measured utilizing a pre-and-posttest survey before and after the educational intervention and analyzed with the Wilcoxen signed-rank test. The online survey included a questionnaire to assess nurses' knowledge about T2DM and DSME and self-efficacy for delivering DSME. Descriptive statistics analyzed demographic data and questionnaire responses. Data analysis was performed IBM's Statistical Package for the Social Sciences.Results: Ten participants completed the survey. Post-test scores increased following the education session with a p-value (.03689) for the variable “knowledge in treating low blood sugar,” suggesting the DSME educational training increased LTC nurse knowledge. The average-pre-post-confidence level scores were significant (p = .01198), indicating that education on T2DM and DSME increases nurse knowledge about T2DM management and increases their self-efficacy for delivering T2DM education.Conclusions: This study demonstrated a link between T2DM management knowledge and DSME education programs for LTC nurses. The study's findings emphasize the need for ongoing education to increase nurse knowledge, self-efficacy and confidence for providing T2DMcare to improve patient outcomes.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".