New Knowledge And Research Needs For End-of-life Care Among Elderly Persons In Long-term Care Settings
Bibliographic record
Abstract
Given the aging of the population, an increase in the number of persons in need of long-term care and end-of-life care can be expected in the coming years. The scientific literature underlines the lack of end-of-life care for elderly people in long-term care centres. The aim of this study is to explore needs in terms of new knowledge and research on end-of-life care for elderly persons in long-term care settings, from the perspective not only of the scientific and international community, but also of Quebec professionals concerned by the issue. An online survey using the LimeSurvey tool was conducted in 2015 among health professionals involved in end-of-life care for elderly persons in long-term care settings in Quebec. 208 professionals rated the priority of new knowledge and research needs related to 1) health professionals; 2) delivery and quality of care; 3) residents and their loved ones; and 4) organization and management of care. The results show that the statements collected in scientific literature resonate with health professionals. The most important need is to identify the symptoms of distress in residents in the final stages of their lives, as well as their causes and treatments. This study also shows professionals' concerns about attitudes, beliefs, and values of practitioners and the related impacts on end-of-life care in long-term care settings. This study shows that there is a significant need for new knowledge and research. It revealed that there are few studies on end-of-life care for elderly persons in long-term care settings and that there is much more to be discovered in this field.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".