Exploring Physician Hand Hygiene Practices and Perceptions in 2 Community-Based Canadian Hospitals
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to explore the self-reported hand hygiene practices and the predictors of hand hygiene among physicians in a midsize Canadian city. METHODS: A descriptive cross-sectional survey using self-report questionnaire administered to a complete list of 354 local physicians. Perception of proper compliance was defined in a participant if he/she indicated performance of hand hygiene before and after every patient contact at least 80% of the time. RESULTS: One hundred fifty-four physicians completed the questionnaire, yielding a 44.9% response rate. Only 45.3% of our sample reported performing preprocedure and postprocedure hand hygiene at least 80% of the time. Stepwise logistic regression results suggested that the variables "presence of hand hygiene auditing" (odds ratio [OR], 3.2; 95% confidence interval [CI], 1.47-6.91), "being too busy" (OR, 0.43; 95% CI, 0.20-0.90), "forgetfulness" (OR, 0.27; 95%, CI, 0.13-0.56), and "the perception that hand hygiene products are damaging to the skin" (OR, 0.31;95% CI, 0.11-0.88) were the only independent predictors of physician hand hygiene compliance. CONCLUSIONS: Hand hygiene compliance among physicians remains an issue. The findings emphasize the need of health-care institutions to prioritize hand hygiene by ensuring proper promotion and enforcement of current policies to all practicing HCPs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".