OP-4 Understanding the scale of exclusion for people unable to consent to research towards the end of life: a scoping review
Bibliographic record
Abstract
Introduction Impaired capacity towards the end of life is common, but involvement in clinical research is rare. Existing reporting practices often fail to include information about mechanism of consent to research, or use of consultees/proxy decision makers. Aim We aimed to determine the extent to which studies on the National Institute for Health and Care Research Clinical Research Network (NIHR CRN) Portfolio were inclusive of people with impaired mental capacity in studies relevant to palliative and end of life care. Methods A scoping review of NIHR CRN Portfolio trials register. The study collated data on: Inclusion and exclusion criteria of NIHR CRN portfolio studies in the specialties of Ageing, Palliative care, Hospice, Dementia or Care homes studies. Studies must have recruited participants between April 2018 –November 2023. Relevance of identified studies to target population (palliative and end of life care) Study recruitment rates, between studies that included people with impaired capacity to consent to participation and those that did not include this population. Results 1,752 unique studies were identified; 150 of which were relevant to palliative and end of life care. 73% (n =109/150) studies excluded people lacking capacity, 31 21% (n = 31/150) explicitly allowed for the inclusion of people lacking capacity and in 6% (n = 10/150) cases it was not clear. Only 5% (n = 5/95) of palliative care studies allowed for recruitment of people with impaired capacity. There was no correlation between studies including those who lacked capacity and failure to achieve minimum recruitment targets. Conclusions Exclusion of people with impaired capacity from research relevant to palliative care is commonplace, despite impaired capacity being highly prevalent in this population. Impact This work is part of a wider NHS England funded project which aims to understand and mitigate structural barriers to research participation.
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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 | 0.224 | 0.533 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.023 | 0.020 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".