Helping novice nurses make effective clinical decisions: the situated clinical decision-making framework.
Bibliographic record
Abstract
The nature of novice nurses' clinical decision-making has been well documented as linear, based on limited knowledge and experience in the profession, and frequently focused on single tasks or problems. Theorists suggest that, with sufficient experience in the clinical setting, novice nurses will move from reliance on abstract principles to the application of concrete experience and to view a clinical situation within its context and as a whole. In the current health care environment, novice nurses frequently work with few clinical supports and mentors while facing complex patient situations that demand skilled decision-making. The Situated Clinical Decision-Making Framework is presented for use by educators and novice nurses to support development of clinical decision-making. It provides novice nurses with a tool that a) assists them in making decisions; b) can be used to guide retrospective reflection on decision-making processes and outcomes; c) socializes them to an understanding of the nature of decision-making in nursing; and d) fosters the development of their knowledge, skill, and confidence as nurses. This article provides an overview of the framework, including its theoretical foundations and a schematic representation of its components. A case exemplar illustrates one application of the framework in assisting novice nurses in developing their decision-making skills. Future directions regarding the use and study of this framework in nursing education are considered.
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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 | 0.007 | 0.140 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".