Nguyen et al. (2024). Relocation of hospitalized older people to long-term care homes.pdf
Bibliographic record
Abstract
Background. Many older people who experience a loss of functional independence, following a hospitalization must move to a long-term care home. These transitions are often unexpected and can have significant consequences. Several studies have explored different aspects of these transitions, but no knowledge synthesis addressing this phenomenon has been identified.Aim. Our aim is to map available knowledge about the relocation of older people from the hospital to a long-term care home, following a decline in health and loss of functional independence.Methods. Following the Joanna Briggs Institute (JBI) Manual, a scoping review will be conducted of the relocation of older people, aged 65 and over, from the hospital to a long-term care home. It will also include the perspectives of stakeholders involved in this process. We will search seven databases and gray literature, as well as conduct a retrospective search. Documents published since 2004 and from all countries will be included. The search will be limited to English and French texts. After a calibration exercise, records will be selected by two independent researchers in duplicate, first by title and abstract, and then by full text. Data extraction and quality assessment will be conducted according to the JBI Manual. Analysis of evidence will consist in content analysis and descriptive statistics. Results will be presented by means of charts, graphs, and narrative descriptions.Discussion. Our findings will help to identify areas of research that should be developed in order to gain insight into the process of integrating a long-term care home from a hospital.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.151 | 0.019 |
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".