Applying mindfulness to influence the patient and care team experience
Bibliographic record
Abstract
Objective: In today’s work environment, specifically in health care, mindfulness is a personal and professional strategy to improve performance and productivity. To influence the patient and care team hospital experience through the concepts of mindfulness and perception.Methods: This was a prospective observational project completed by medical/surgical nurses using an online survey pre- and post an educational program and an aggregate score of the 5 nurse-sensitive questions on the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, a survey based in the United States that is mailed to patients post discharge to home to measure patient satisfaction with their hospitalization. The HCAHPS survey is a patient satisfaction survey required by the Centers for Medicare and Medicaid Services (CMS) for all hospitals in the United States. The purpose of the HCAHPS survey is to provide a standardized survey instrument and data collection methodology for measuring patients’ perspectives on their hospital care and hospital experience.Results: The aggregate nurse-sensitive HCAHPS scores increased from 85.5 to 89.8 over one month. For mindfulness, after the educational program, among the ten nurse survey questions the percentage went up as much as 0.57%.Conclusions: An educational program related to the benefits of mindfulness can positively effect nurses’ engagement in the workplace and positively increase HCAHPS scores. Continuing education on mindfulness should carry over month to month. In this research project, participants provided feedback to the researcher of feeling empowered to bring in new ideas, present different ways to grow, and tackle challenges.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".