An exploratory investigation of the measurement of cognitive load on shift: Application of cognitive load theory in emergency medicine
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Emergency physicians often experience a high cognitive load (CL) due to the inherent nature of working in acute care settings. CL has traditionally been measured in educational studies but has not been well studied in the clinical environment. METHODS: Emergency medicine attending physicians and residents working in an academic urgent care center completed psychometric questionnaires while on shift to measure overall CL, intrinsic cognitive load (ICL), extraneous cognitive load (ECL), and acute stress. Data regarding the patient load, patient acuity, and the number of patients in the waiting room were also collected. Correlational analysis and simple linear regression were used to evaluate predictors of CL on shift. RESULTS: < 0.001). No differences in mean overall CL, ICL, ECL, and acute stress were observed between attending physicians and residents. Bivariate analysis demonstrated associations between ICL, ECL, acute stress, and overall CL in attending physicians. In residents, acute stress was the only variable associated with overall CL and the number of high-acuity patients was associated with ICL. CONCLUSIONS: Factors influencing reported CL during clinical work are different between attending emergency physicians and residents. Further study to appreciate the impact of these differences is required and may help educators elucidate strategies to better manage CL, thereby improving clinical performance and potentially improving patient care.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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 it