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Record W4403477166 · doi:10.1136/bmjopen-2024-088301

Post-rehabilitation programme to support upper limb recovery in community-dwelling stroke survivors: a mixed methods cluster-feasibility controlled trial

2024· article· en· W4403477166 on OpenAlexaff
Katy Pedlow, Niamh Kennedy, Natalie Klempel, Janice J. Eng, Gary Adamson, Jenny Hylands, Noelene Hughes, Zoë A. Campbell, Suzanne McDonough

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineRehabilitationIntervention (counseling)Physical therapyStroke (engine)Randomized controlled trialQuality of life (healthcare)Physical medicine and rehabilitationCluster randomised controlled trialClinical trialGRASPTest (biology)Focus groupNursingSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Less than 50% of stroke survivors regain their pre-stroke level of upper limb function, compounded with a lack of long-term rehabilitation options available. The Graded Repetitive Arm Supplementary Programme (GRASP) is an evidence-based upper limb programme delivered as a standalone programme to stroke survivors. To improve access to such a programme, there is the potential to combine it with a high-utility community-based exercise programme, such as the post-rehabilitation enablement programme (PREP). We aimed to establish if this was feasible to deliver alongside the experience of stroke survivors and therapists, identify any refinements the intervention and the acceptability of the intervention and trial procedures. METHODS: A cluster feasibility-controlled trial was conducted using both quantitative and qualitative outcome measures with stroke survivors who were discharged from NHS care. Participants completed PREP for 6 weeks (control), with the intervention group also completing GRASP. The GRASP intervention was refined in between five iterative testing cycles. Focus groups with participants explored the acceptability and feasibility. Individual interviews with intervention therapists explored how feasible it was to embed the intervention into practice, and determine the feasibility of a future larger, mixed methods, randomised controlled trial. Clinical endpoints for upper limb and overall function were explored through the Rating of Everyday Arm use in the Community and Home, 10-metre walk test (10MWT) and quality of life via the Shortened Edinburgh Warwick questionnaire. No further suggestions for intervention design were noted after cycle 4. RESULTS: Recruitment (n=72) and retention levels (84.7%) were high with 61 participants (mean age of 66 years and 49 weeks post-stroke) completing the study. Participants and therapists reported positive acceptability of the intervention with goal setting and family support noted as beneficial. The home exercise programme was noted as challenging. Participants within both groups demonstrated improvements in clinical measures, with the intervention group demonstrating a greater improvement within the Rating of Everyday Arm-use in the Community and Home and the 10MWT. CONCLUSION: This study successfully recruited and retained stroke survivors into an upper limb community-based programme. It poses a feasible delivery mechanism to combine evidence-based upper limb approaches with established physical activity programmes in a future large scale and fully powered study. 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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.091
GPT teacher head0.462
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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