Novice nurses’ attention to task-relevant stimuli during practice
Bibliographic record
Abstract
Objective: Nurses engaged in practice make split-second decisions based on stimuli perceived in the clinical environment. There has been limited research in nursing on stimuli perception and limited research aimed specifically at directly measuring nurses’ gaze and the subsequent quality of their decisions.Methods: This study used an observational descriptive design to examine nurses’ gaze behaviors as they cared for a simulated patient in three different clinical scenarios. Participants were fitted with eye-tracking goggles that facilitated the recording on video of the focal point of their gaze. The recorded videos were coded to quantify the participants’ areas of focus. For each scenario, visual focus data were compared between participants who successfully resolved the scenarios and those who did not. Results: The results revealed statistically significant differences in areas of focus between successful and unsuccessful participants. While successful participants focused on the patient, unsuccessful participants focused on task-irrelevant environmental cues.Conclusions: The results demonstrate a need for nurse educators to focus their students on the patient, while guiding them to avoid becoming mired in task irrelevant foci and actions.
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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 | 0.001 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".