Retrospective study of the implementation of the nursing process in a health area
Bibliographic record
Abstract
OBJECTIVES: To analyze when the nursing process began to be used in the public and private healthcare centers of Gipuzkoa (Basque Country), and when both NANDA-I nursing diagnoses and the NIC-NOC terminologies were incorporated into this process. METHOD: A retrospective study was conducted, based on the analysis of nursing records that were used in the 158 studied centers. RESULTS: The specific data provided showed that in Gipuzkoa, the nursing process began to be used in the 1990s. As for NANDA-I nursing diagnoses, they have been used since 1996, and the NIC-NOC terminologies has been used since 2004. CONCLUSION: It was concluded that public centers are the ones which, generally speaking, first began with the nursing methodology, and that in comparison to the United States and Canada, the nursing process started to be used about 20 years later, NANDA-I nursing diagnoses around 15 years later, and the NIC-NOC terminologies, around six years later.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".