Knowledge and Skills in Infection Prevention and Control Measures Amongst Visitors to Long-Term Care Homes: A Mixed methods Study
Bibliographic record
Abstract
Caroline Gibbons,1 Pamela Durepos,2 Natasha Taylor,3 Lisa Keeping-Burke,3 Matt W Rogers,4 Karen E Furlong,3 Rose M McCloskey3 1School of Nursing, Université de Moncton, Moncton, NB, Canada; 2Faculty of Nursing, University of New Brunswick, Fredericton, NB, Canada; 3Department of Nursing & Health Sciences, University of New Brunswick, Saint John, NB, Canada; 4Faculty of Education, University of New Brunswick, Fredericton, NB, CanadaCorrespondence: Caroline Gibbons, School of Nursing, 18 Antonine-Maillet Ave, Université de Moncton, Moncton, NB, E1A 3E9, Canada, Email caroline.gibbons@umoncton.caPurpose: This mixed methods study aimed to assess the knowledge and skills related to infection prevention and control amongst visitors to long-term care homes following the removal of visiting restrictions during the Covid-19 pandemic.Methods: Forty visitors to residents in long-term care homes were recruited. Participants’ knowledge of the Covid-19, infection prevention and control practices, and self-reported use of protective behaviours were assessed through questionnaires. Handwashing skills, donning and doffing of personal protective equipment and decision-making surrounding hand hygiene moments were assessed through laboratory simulation using observation checklists.Results: Participants’ level of knowledge and perceived use of protective behaviours were high. However, no one accurately performed the handwashing steps, few (5.0%) performed all hand hygiene moments recommended, 35.0% donned personal protective equipment and only 12.5% doffed correctly. This is concerning because 90.0% of participants reported receiving infection prevention and control training.Conclusion: These findings suggest educational interventions, resources and policies are needed to strengthen infection prevention and control training for visitors’ to long-term care.Keywords: long-term care, handwashing utilization, personal protective equipment utilization, simulation
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".