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Record W4389334167 · doi:10.1093/ptj/pzad165

Investigating the Telerehabilitation With Aims to Improve Lower Extremity Recovery Poststroke Program: A Feasibility Study

2023· article· en· W4389334167 on OpenAlexafffundabout
Sarah Park, Ada Tang, Ruth Barclay, Mark Bayley, Janice J. Eng, Marilyn MacKay-Lyons, Courtney L. Pollock, Sepideh Pooyania, Robert Teasell, Jennifer Yao, Brodie M. Sakakibara

Bibliographic record

VenuePhysical Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsGF Strong Rehabilitation CentreSt Joseph's Health CareParkwood InstituteUniversity of ManitobaMcMaster UniversityVancouver Coastal Health Research InstituteVancouver Coastal HealthUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of TorontoUniversity Health NetworkDalhousie UniversityHamilton Health SciencesToronto Rehabilitation InstituteUniversity of British Columbia Hospital
FundersFondation Brain Canada
KeywordsTelerehabilitationPhysical therapyPhysical medicine and rehabilitationMedicineStroke (engine)TelemedicinePsychologyHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to examine the feasibility of a progressive virtual exercise and self-management intervention, the TeleRehabilitation with Aims to Improve Lower extremity recovery poststroke program (TRAIL), in individuals with stroke. METHODS: A single group pre-post study design was used. Thirty-two participants were recruited who were aged 19 years or older, had a stroke within 18 months of the beginning of the study, had hemiparesis of the lower extremity, and were able to tolerate 50 minutes of activity. Participants completed TRAIL, a synchronous exercise and self-management program delivered via videoconferencing. Participants received 8 telerehabilitation sessions over 4 weeks that were 60 to 90 minutes, with a trained physical therapist in a ≤2 to 1 participant-to-therapist ratio. Feasibility indicators in the areas of process (recruitment and retention rates, perceived satisfaction), resources (treatment fidelity and adherence, participant and assessor burden, therapist burden), management (equipment, processing time), and scientific indicators (safety, treatment response, treatment effect) were collected throughout the study using a priori criteria for success. The treatment effect was examined on the Timed "Up & Go" test, the virtual Fugl-Meyer Lower Extremity Assessment, the 30-Second Sit-to-Stand Test, the Functional Reach, the Tandem Stand, the Activities-Specific Balance Confidence Scale, the Stroke Impact Scale, and the Goal Attainment Scale. RESULTS: Forty-seven individuals were screened, of which 32 (78% male; median age of 64.5 years) were included for the study from 5 sites across Canada. Nine feasibility indicators met our study-specific threshold criteria for success: retention rate (0 dropouts), perceived satisfaction, treatment fidelity, adherence, therapist burden, equipment, and safety. In terms of treatment response and effect, improvements were observed in Timed "Up & Go" test (Cohen d = 0.57); Fugl-Meyer Lower Extremity Assessment (d = 0.76); 30-Second Sit-to-Stand Test (d = 0.89); and Goal Attainment Scale (d = 0.95). CONCLUSION: The delivery of TRAIL, a lower extremity stroke rehabilitation program using videoconferencing technology, is feasible and appears to have positive influences on mobility, lower extremity impairment, strength, and goal attainment. IMPACT: Community-based telerehabilitation programs, such as TRAIL, could extend the continuum of care during the transition back to community postdischarge or during global disruptions, such as Coronavirus Disease 2019 (COVID-19). Delivery of synchronous lower extremity rehabilitation via videoconferencing to community-dwelling stroke survivors is feasible.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.350
Teacher spread0.310 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations16
Published2023
Admission routes3
Has abstractyes

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