Education and training for infection prevention and control provided by long-term care homes to family caregivers: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this review is to map the infection prevention and control education and training that long-term care homes use with families during a pandemic or infectious outbreak. INTRODUCTION: During the COVID-19 pandemic, restrictions were imposed on visits to long-term care homes to decrease the risk of virus transmission. These restrictions had negative consequences for both residents and families. A scoping review of infection prevention and control education and training used with families will inform family visitation practices and policies during future infectious outbreaks. INCLUSION CRITERIA: This review will examine literature describing infection prevention and control education and training provided to families in long-term care homes. Research and narrative papers, including experimental; quasi-experimental; descriptive observational quantitative and qualitative studies; and reviews, text, policy, and opinion papers, will be considered for inclusion. METHODS: A 3-step approach will be followed, in line with the JBI methodology for scoping reviews. Published literature will be searched for in databases, including CINAHL, Embase, ERIC, MEDLINE, and AgeLine. Published and unpublished papers will be considered from 1990 to the present, in English or French. The World Health Organization, Centers for Disease Control, and the Public Health Agency of Canada websites will be searched for unpublished and gray literature. Two authors will independently review and assess studies for inclusion and extract the data. The findings will be charted in a narrative summary and tables.
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 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 | 0.127 | 0.082 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.070 | 0.015 |
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".