PREP Plus combined postrehabilitation programme to support upper limb recovery in community-dwelling stroke survivors: protocol for a mixed-methods, cluster-assigned feasibility study
Bibliographic record
Abstract
INTRODUCTION: Poor recovery of the upper limb following a stroke has been recognised as a significant problem in the UK. Although there is good evidence that early, intense rehabilitation can lead to upper limb recovery, often this is not maintained, with less than 50% of people regaining the ability to use their upper limb for independent function at 6 months. Upper limb recovery potential is reported for many years poststroke, yet current long-term provision is insufficient. METHODS AND ANALYSIS: 60 participants will be recruited into this feasibility study, with 30 allocated to a Post Rehabilitation Enablement Programme (PREP) alone and 30 allocated to a combined programme, PREP Plus, consisting of PREP and the Graded Repetitive Arm Supplementary Programme (GRASP). We will aim to complete four iterative waves. Within each wave, the intervention design will be refined, based on participant feedback. Within each wave, there will be one cluster unit (one intervention group ;PREP Plus) and one control group ;PREP alone)). A total of five PREP sites within Northern Ireland Health and Social Care Trusts will be used for this study. PREP Plus will have a home exercise component along with exercises logs and a behaviour contract. Qualitative and quantitative measures will evaluate the acceptability and feasibility to determine how feasible it is to embed the intervention into practice, as well as to determine the feasibility of a larger, mixed-methods, randomised controlled trial to assess intervention efficacy. Clinical endpoints will also be explored. ETHICS AND DISSEMINATION: This study has been approved by the Health and Social Care Research Ethics Committee A, IRAS project ID (278620). Participants will provide informed consent prior to participating in the study. Information outlining the purpose of the study, what data will be collected and how the data will be managed will be provided. Results will be published in peer-reviewed journals and any published data will be available on the university data repository. The project management group will advise on different avenues for dissemination to ensure it reaches appropriate audiences. TRIAL REGISTRATION NUMBER: NCT05090163.
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 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 | 0.047 | 0.025 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.011 |
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".