Supporting lay carers in end of life care: current gaps and future priorities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Informal carers are central to the achievement of end of life care and death at home and to policy aims of enabling patient choice towards end of life. They provide a substantial, yet hidden contribution to our economy. This entails considerable personal cost to carers, and it is recognised that their needs should be assessed and addressed. However, we lack good research evidence on how best to do this. The present position paper gives an overview of the current state of carer research, its gaps and weaknesses, and outlines future priorities. It draws on a comprehensive review of the carer literature and a consensus meeting by experts in the field. Carers' needs and adverse effects of caregiving have been extensively researched. In contrast, we lack both empirical longitudinal research and conceptual models to establish how adverse effects may be prevented through appropriate support. A reactive, "repair" approach predominates. Evaluations of existing interventions provide limited information, due to limited rigour in design and the wide variety in types of intervention evaluated. Further research is required into the particular challenges that the dual role of carers as both clients and providers pose for intervention design, suggesting a need for future emphasis on positive aspects of caregiving and empowerment. We require more longitudinal research and user involvement to aid development of interventions and more experimental and quasi-experimental research to evaluate them, with better utilisation of the natural experiments afforded by intra- and international differences in service provision.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it