The impacts of partnering with cancer patients in palliative care research: a systematic review and meta-synthesis
Bibliographic record
Abstract
Background: Palliative care (PC) is an added layer of support provided concurrently with cancer care and serves to improve wellbeing and sustain quality of life. Understanding what is meaningful and a priority to patients, their families, and caregivers with lived experience of cancer and PC is critical in supporting their needs and improving their care provision. However, the impacts of engaging cancer patients within the context of PC research remain unknown. Objective: To examine the impacts of engaging individuals with lived experience of cancer and PC as partners in PC research. Methods: An a priori systematic review protocol was registered with PROSPERO (CRD42021286744). Four databases (APA PsycINFO, CINAHL, EMBASE, and MEDLINE) were searched and only published, peer-reviewed primary English studies aligned with the following criteria were included: (1) patients, their families, and/or caregivers with lived experience of cancer and PC; (2) engaged as partners in PC research; and (3) reported the impacts of engaging cancer PC patient partners in PC research. We appraised the quality of eligible studies using the Critical Appraisal Skills Program (CASP) and GRIPP2 reporting checklists. Results: Three studies that included patient partners with lived experience of cancer and PC engaged at all or several of the research stages were identified. Our thematic meta-synthesis revealed impacts (benefits and opportunities) on patient partners (emotional, psychological, cognitive, and social), the research system (practical and ethical) and health care system (service improvements, bureaucratic attitudes, and inaction). Our findings highlight the paucity of evidence investigating the impacts of engaging patients, their families and caregivers with lived experience of cancer and PC, as partners in PC research. Conclusions: The results of this review and meta-synthesis can inform the more effective design of cancer patient partnerships in PC research and the development of feasible and effective strategies given the cancer and PC context patient partners are coming from.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".