A comparative analysis of two cross-sectional surveys of healthcare workers' hand hygiene knowledge, intentions, access and product preferences between two university hospitals, one in Norway and one in Canada
Bibliographic record
Abstract
Objective: Vancouver General Hospital (VGH) and The University Hospital of Northern Norway in Tromsø (UNN-Tromsø) were compared for self-reported differences in level of knowledge and intentions to comply with the hand hygiene guidelines. Hand hygiene products were also assessed for preference of use, access, gentleness and promotion of hand hygiene compliance.\nMethods: A cross-sectional quality assurance staff survey was made available at UNN- Tromsø and at VGH in both print and in electronic format. \nResults: A total of 1230 of the 10,000 full time health care workers (HCWs) (12%) responded to the survey. UNN-Tromsø HCWs were less satisfied with the gentleness of soap and water than were VGH HCWs. UNN-Tromsø HCWs reported greater access to both soap and water and hand rub than was reported by HCWs at VGH. Promoting compliance was influenced by access for both VGH and UNN- Tromsø whereas, gentleness promoted compliance only for Tromsø-UNN HCWs. The HCWs at VGH had higher mean scores on intention to comply with hand hygiene guidelines. \nConclusion: Environmental factors such as gentleness to the hand and easy accessibility of hand cleansers were associated with compliance to the hand hygiene guidelines. Further, knowledge of hand hygiene guidelines was positively associated with compliance.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".