L’autonomie décisionnelle d’infirmières de soins intensifs lors du sevrage de la ventilation mécanique : une analyse de concept
Bibliographic record
Abstract
Nurses have a leading role in weaning patients from mechanical ventilation (WMV) given their constant presence and their continuous monitoring. To promote proper WMV, nurses must exercise autonomy and be involved in decision-making. However, in certain care contexts, there is little involvement of nurses. The purpose of this text is to establish the characteristics of the concept of autonomous decision-making applied to nursing during WMV. An analysis of this concept was carried out according to the evolutionary method of Rodgers. The identification of the attributes, antecedents, and consequences made it possible to note ambiguity in the definition of this concept. Nurses use autonomous decision-making for the execution of assigned tasks and when they make decisions according to a pre-prescribed decision-making algorithm. Significant foundations for the decision-making autonomy of critical care nurses during WMV emerged from this analysis : scope of practice, in-depth knowledge of the patient, and commitment to the success of WMV. Participation in interdependent decision-making allows nurses to bring the patient’s perspective into decisions. Avenues of reflection have also emerged, including decisions based on evidence to provide new avenues for autonomous decision-making.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".