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Record W2402144413 · doi:10.1177/1744987115606959

Self-perceived hand hygiene practices among undergraduate nursing students

2015· article· en· W2402144413 on OpenAlexaffabout
Anne Foote, Maher M. El‐Masri

Bibliographic record

VenueJournal of research in nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsUniversity of WindsorSt. Clair College
Fundersnot available
KeywordsHygieneMedicineOdds ratioLogistic regressionConfidence intervalNursingDescriptive statisticsFamily medicineCompliance (psychology)PsychologyInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

Abstract Limited research has investigated the hand hygiene practices of undergraduate nursing students. A descriptive self-report survey explored the predictors of self-perceived hand hygiene compliance using a convenience sample of 306 undergraduate nursing students enrolled at a southwestern Ontario university. Compliance was defined as the performance of hand hygiene at least 90% of the time in the moments both before and after direct patient contact. The self-reported compliance rate among study participants was 74.8%. Logistic regression analysis revealed that the independent predictors of hand hygiene compliance included concern about reprimand or discipline (odds ratio (OR) 4.324; 95% confidence interval (CI) 1.465–12.758); motivation to protect patients from infection (OR 2.418; 95% CI 1.001–5.838); number of clinical placements (OR 0.815; 95% CI 0.702–0.947) and role modelling by the clinical instructor (OR 2.227; 95% CI 1.009–4.915). Other independent predictors were the perceived barriers of busyness (OR 0.231; 95% CI 0.126–0.423), forgetfulness (OR 0.356; 95% CI 0.186–0.678) and perceptions of alcohol rub-related skin damage (OR 0.163; 95% CI 0.070–0.380). The findings of this study provide research-based evidence that could be used by educators to understand better hand hygiene practices among undergraduate nursing students.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.168
GPT teacher head0.542
Teacher spread0.374 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2015
Admission routes2
Has abstractyes

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