Overcoming the challenges of conducting research with people who have advanced heart failure and palliative care needs
Bibliographic record
Abstract
Research on the palliative care needs of heart failure patients is scant and requires development to provide a sound evidence base for improved care; but there are distinct practical and ethical challenges in conducting research with this population. This paper presents an integrative review of the literature that aims to describe these challenges and discuss potential strategies by which they may be addressed. It is recognised that heart failure is a volatile condition making identification of the end of the life phase difficult. This leads to an array of other issues; firstly clinical teams tend to use this as a rationale for their failure to discuss palliative care issues with patients and families, making identification of the population difficult and research related communication challenging. Symptom volatility also creates methodological problems for researchers in deciding patients' eligibility, securing user involvement and contributes to sample attrition in research. There are also substantial ethical challenges for researchers in terms of gaining access and ensuring patient autonomy in this population. Acknowledgement of these issues and discussion of strategies by which they can be addressed has the potential to augment clinical research, develop practice and ultimately produce the much needed improvements in patient care required for those with advanced heart failure.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".