The use of the Nursing Activities Score in clinical settings: an integrative review
Bibliographic record
Abstract
Objective analyze how studies have approached the results obtained from the application of the Nursing Activities Score (NAS) based on Donabedian's model of healthcare organization and delivery. Method CINAHL and PubMed databases were searched for papers published between 2003 and March 2015. Results 36 articles that met the inclusion criteria were reviewed and double-coded by three independent coders and analyzed based on the three elements of Donabedian's health care quality framework: structure, process and outcome. The most frequently addressed, but not always tested, variables were those that fell into the structure category. Conclusion variables that fell into the process category were used less frequently. Beside NAS, the most frequently used variables in the outcome category were mortality and length of stay. However, no study used a quality framework for healthcare or NAS to evaluate costs, and it is recommended that further research should explore this approach.
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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 | 0.019 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.028 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".