A Value-Added Benefit of Nurse Practitioners in Long-Term Care Settings: Increased Nursing Staff’s Ability to Care for Residents
Bibliographic record
Abstract
The number of people living longer is increasing, and those with physical or cognitive impairments may need admission into long-term care settings. In long-term care there is a need to increase nursing staff's capacity to meet the care needs of residents, develop a team approach to providing care and provide opportunities for staff to improve their knowledge and skills. One approach to meet these needs has been to employ a nurse practitioner (NP). The purpose of this paper is to examine nursing staff's perceptions of how working with an NP affected their ability to provide care, function as a team and increase their knowledge and skill. Data used in this paper were obtained from nursing staff and managers who participated in focus groups that were part of case studies conducted in the second phase of a larger sequential, two-phase mixed-methods study. NPs used multiple approaches to increase staff knowledge and skills and improve quality of care. These findings describe the benefits of employing NPs in long-term care settings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".