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Record W1632329379

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

2008· dissertation· en· W1632329379 on OpenAlexaboutno aff
Anne Kristine Mediå

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2008
Typedissertation
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHygieneCompliance (psychology)Health careFamily medicinePsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.102
GPT teacher head0.391
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2008
Admission routes1
Has abstractyes

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