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Record W6902238499 · doi:10.6084/m9.figshare.28227979

Stroke survivors with limited walking ability have unique barriers and facilitators to physical activity

2025· article· en· W6902238499 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Thematic analysisRehabilitationMultidisciplinary approachPhysical activityQualitative researchMental healthMEDLINE

Abstract

fetched live from OpenAlex

Stroke is a leading cause of morbidity and mortality in Canada. Approximately 73% of stroke survivors experience limited walking ability, requiring a gait aid or assistance. Physical activity is important for secondary stroke prevention, in addition to its benefits for physical and mental health. Little is known about the barriers and facilitators to physical activity in stroke survivors with limited walking ability. This qualitative study used inductive thematic analysis of structured interviews to explore the barriers and facilitators to physical activity in stroke survivors with limited walking ability. Perceived barriers to physical activity included scarcity of services, societal views, changes in ability, and inclement weather. Perceived facilitators included the desired benefits of physical activity, multidisciplinary rehabilitation services, durable medical equipment, encouragement, positive mindset, and self-efficacy. Improving access to rehabilitation services in the chronic phase of stroke and increasing the availability of structured exercise programmes are important strategies to address barriers to physical activity in this population. Supporting self-efficacy, addressing disability stigma, and policy changes are also needed to facilitate participation. Stroke rehabilitation programmes should prioritize education about exercise and adaptation strategies to improve self-efficacy and facilitate ongoing physical activity outside of structured settings.Rehabilitation teams should emphasize the benefits of physical activity for mental and physical health, as well as secondary stroke prevention, to enhance motivation and adherence to physical activity recommendations.Rehabilitation professionals should advocate for increased access to multidisciplinary services, including physical therapy, orthotics, and physiatry, to address physical impairments and activity limitations that hinder physical activity participation.Rehabilitation professionals should consider the impact of societal views and stigma when developing strategies to increase physical activity in stroke survivors with limited walking ability. Stroke rehabilitation programmes should prioritize education about exercise and adaptation strategies to improve self-efficacy and facilitate ongoing physical activity outside of structured settings. Rehabilitation teams should emphasize the benefits of physical activity for mental and physical health, as well as secondary stroke prevention, to enhance motivation and adherence to physical activity recommendations. Rehabilitation professionals should advocate for increased access to multidisciplinary services, including physical therapy, orthotics, and physiatry, to address physical impairments and activity limitations that hinder physical activity participation. Rehabilitation professionals should consider the impact of societal views and stigma when developing strategies to increase physical activity in stroke survivors with limited walking ability.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.286
Teacher spread0.270 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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