Sacral herpes zoster presenting as sciatica
Bibliographic record
Abstract
Background Despite ample evidence that hand hygiene (HH) can reduce nosocomial infections, physician compliance remains low. The authors hypothesised that attending physician role modelling and peer pressure among internal medicine teams would impact HH adherence. Methods Nine teams were covertly observed. Team member entry and exit order, and adherence to HH were recorded secretly. The mean HH percentage across encounters was estimated by compliance of the first person entering and exiting an encounter, and by the attending physician9s HH compliance. Results 718 HH opportunities prior to contact and 744 opportunities after contact were observed. If the first person entering a patient encounter performed HH, the mean compliance of other team members was 64%, but was only 45% if the first person failed to perform HH (p=0.002). When the attending physician performed HH upon entering the patient encounter, the mean HH compliance was 66%, but only 42% if the attending physician did not perform HH (p<0.001). Similar results were seen on exiting the room. The effects of the first person were not driven solely by the attending physician9s HH behaviour because the attending physician was first or second to enter 57% of the encounters and exit 44% of the encounters. Conclusions If the first person entering a patient room performs HH, then others were more likely to perform HH too, implying that peer pressure impacts team member HH compliance. The attending physician9s behaviour also influenced team members regardless of whether the attending physician was the first to enter or exit an encounter, implying that role modelling impacts the HH behaviour of learners. These findings should be used when designing HH improvement programmes targeting physicians.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".