Advanced Practice Nursing and the Expansion of the Role of Nurses in Primary Health Care in the Americas
Bibliographic record
Abstract
Nurses have an educational background particularly suited to the growing challenges of the 21st century, characterized by an accelerated demographic transition, accompanied by a scenario of triple disease burden: 1) the unsurpassed agenda for infectious diseases; 2) the increase in deaths attributable to external causes; and 3) the predominance of chronic noncommunicable diseases. Advanced Practice Nurses (APN) already have regulations well-established in many countries such as Australia, Belgium, Canada, the USA, Finland, France, Ireland, Japan, Poland, the United Kingdom, and the Czech Republic, among others. This paper aimed to point out and to reflect on Advanced Practice Nursing and the expansion of the role of nurses in Primary Health Care (PHC) in the Americas. In the same year the Nursing Now Campaign was launched, Pan American Health Organization (PAHO) and World Health Organization (WHO) prepared the document Expanding the Role of Nurses in PHC which calls on governments and nurses from countries in the Americas to implement APN training for PHC and Nurses from Central and South America who already have specialization programs, residency, academic master's and doctoral degrees. Expansion is intended to provide greater coverage and assistance to users of the health system, take advantage of nurses' intellectual capacity, and retain good professionals in the profession. This is a crucial moment for nursing worldwide. However, it is imperative to ensure the voice and impact of nursing continues to reverberate long after the end of 2021. In this paper, a debate on the strengths and challenges for the expansion of the APN role in PHC in the Americas is discribed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".