Research priorities for homecare for older people: A <scp>UK</scp> multi‐stakeholder consultation
Bibliographic record
Abstract
Homecare is generally understood to refer to services that support people to continue living in their own homes. Older people are the primary users and many countries report an increase in the number using homecare services and greater spending on such provision, driven in part by investment in 'ageing in place' policies. Despite this, and reflecting social care more generally, homecare is relatively under-researched. However, in the UK at least, there is growing interest and investment in social care research. In order that this investment is not wasted, it is essential that research addresses what stakeholders identify as research priorities. This study reports work undertaken in the UK during 2021/22 to identify research priorities for homecare for older people, and a broad scoping of existing evidence. A two-stage consultation process was used. First, topic areas for research were identified through consultations with stakeholders. Second, a survey ascertained agreement and differences between groups regarding the relative importance of topic areas as research priorities. Over 50 people participated including older people (n = 7), family members (n = 11), homecare workers (n = 16), homecare providers (n = 9) and national policy, evidence and advocacy leads (n = 13). Twenty discrete research topic areas were identified. Only one topic area (Joint working between homecare and health services) was a 'Top 5' research priority for all stakeholder groups. Timely engagement with homecare and Workforce: recruitment and retention were 'Top 5' priorities for three stakeholder groups. Scoping of existing research indicates that topic areas receiving the most research attention to date are not among those identified as being of high priority for research. To our knowledge, this is the first time research priorities for homecare have been generated. Findings will be of value to research funders, organisations using research evidence and the research community.
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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 | 0.161 | 0.131 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.016 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".