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Record W4391404673 · doi:10.3390/healthcare12030365

Acceptability of Telerehabilitation: Experiences and Perceptions by Individuals with Stroke and Caregivers in an Early Supported Discharge Program

2024· article· en· W4391404673 on OpenAlexafffund
Fatimata Ouédraogo, Louis-Pierre Auger, Emmanuelle Moreau, Odile Côté, Rosalba Guerrera, Annie Rochette, Dahlia Kairy

Bibliographic record

VenueHealthcare · 2024
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéCanadian Occupational Therapy Foundation
KeywordsTelerehabilitationThematic analysisRehabilitationContext (archaeology)PsychologyStroke (engine)Qualitative researchStroke recoveryPerceptionTelemedicineMedicineMedical educationApplied psychologyHealth care

Abstract

fetched live from OpenAlex

INTRODUCTION: Telerehabilitation (TR) is a promising method for facilitating the delivery and access to post-stroke rehabilitation services. OBJECTIVE: The aim of this study was to explore the acceptability of TR and factors influencing its adoption by individuals with stroke and caregivers. METHODS: A qualitative descriptive approach was used. Six individuals with stroke and three caregivers participated in individual online interviews. An abductive thematic analysis was employed to analyze the qualitative data, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) model. RESULTS: Participants reported positive experiences with TR, resulting in improvements in functional abilities, such as manual dexterity, balance, and positive interactions with therapists. They found the technology easy to learn and use, facilitating engagement in TR. Participants' prior experiences with technology, along with support from caregivers and therapists, facilitated acceptance and the use of TR. The COVID-19 pandemic also motivated participants to accept TR. However, technical issues, unstable internet connections, and lack of feedback were barriers to the use of TR. CONCLUSION: Despite existing obstacles, TR can be used to provide rehabilitation services for individuals with stroke. Addressing these barriers is necessary to promote the widespread and effective use of TR in the context of stroke recovery.

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)0.000
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 score0.076
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.342
Teacher spread0.326 · 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

Citations18
Published2024
Admission routes2
Has abstractyes

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