MétaCan
Menu
← Back to cohort
Record W4384922960 · doi:10.1136/bmjopen-2023-076723

TeleRehabilitation with Aims to Improve Lower extremity recovery in community-dwelling individuals who have had a stroke: protocol for a multisite, parallel group, assessor-blinded, randomised attention-controlled trial

2023· article· en· W4384922960 on OpenAlexafffundabout
Brodie M. Sakakibara, Elise Wiley, Ruth Barclay, Mark Bayley, Jennifer C. Davis, Janice J. Eng, Anne Harris, Elizabeth L. Inness, Marilyn MacKay-Lyons, Jennifer Monaghan, Courtney L. Pollock, Sepideh Pooyania, Amy Schneeberg, Robert Teasell, Jennifer Yao, Ada Tang

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsDalhousie UniversityWestern UniversityUniversity of TorontoUniversity of ManitobaGF Strong Rehabilitation CentreMcMaster UniversityToronto Rehabilitation InstituteUniversity of British Columbia, Okanagan CampusOkanagan University CollegeVancouver Coastal HealthVancouver Coastal Health Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCMcMaster UniversityFondation Brain Canada
KeywordsMedicineTelerehabilitationRandomized controlled trialPhysical therapyProtocol (science)Stroke (engine)Physical medicine and rehabilitationTrial registrationAlternative medicineTelemedicineHealth careSurgeryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Telerehabilitation is an accessible service delivery model that may support innovative lower extremity rehabilitation programmes that extend the stroke recovery continuum into the community. Unfortunately, there is limited evidence on the provision of exercises for lower extremity recovery after stroke delivered using telerehabilitation. In response, we developed the TeleRehabilitation with Aims to Improve Lower extremity recovery poststroke (TRAIL) programme, a 4-week progressive exercise and self-management intervention delivered synchronously using video-conferencing technology. Our primary hypothesis is that individual within 1-year poststroke who participate in TRAIL will experience significantly greater improvements in functional mobility than individuals in an attention-controlled education programme (EDUCATION). METHODS AND ANALYSIS: In this multisite, parallel group, assessor-blinded randomised attention-controlled trial, 96 community-living stroke survivors within 1-year poststroke will be recruited from five sites (Vancouver, Winnipeg, Toronto, London and Halifax, Canada) from the CanStroke Recovery Trials Platform which is a network of Canadian hospital sites that are affiliated with academic institutions to facilitate participant recruitment and quality trial practices. Participants will be randomised on a 1:1 basis to TRAIL or EDUCATION. Participants randomised to TRAIL will receive eight telerehabilitation sessions where they will perform exercises and receive self-management support to improve lower extremity recovery from a TRAIL physical therapist. The primary outcome will be measured using the Timed Up and Go. Secondary outcomes include lower extremity muscle strength, functional balance, motor impairment, balance self-efficacy, health-related quality of life and health service use for our economic evaluation. Measurements will be taken at baseline, immediately after the intervention, 3-month and 6-month postintervention. ETHICS AND DISSEMINATION: Ethics approval for this research has been obtained by all participating sites. All study participants will provide their informed consent prior to enrolling them in the study. Findings from this trial will be disseminated in peer-reviewed journals and presentations at international scientific meetings. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov, NCT04908241.

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)0.041
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.064
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.041
Meta-epidemiology (narrow)0.0080.004
Meta-epidemiology (broad)0.0140.007
Bibliometrics0.0030.004
Science and technology studies0.0040.005
Scholarly communication0.0050.005
Open science0.0050.002
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0640.013

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 head0.082
GPT teacher head0.424
Teacher spread0.342 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations6
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueBMJ Open→Same topicStroke Rehabilitation and Recovery→French-language works237,207→