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Record W2032964188 · doi:10.1177/0888439004266304

Training Mobility Tasks after Stroke with Combined Mental and Physical Practice: A Feasibility Study

2004· article· en· W2032964188 on OpenAlexafffund
Francine Malouin, Carol L. Richards, Julien Doyon, Johanne Desrosiers, Sylvie Belleville

Bibliographic record

VenueNeurorehabilitation and neural repair · 2004
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversité LavalUniversité de SherbrookeUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
FundersRéseau Provincial de Recherche en Adaptation-RéadaptationCanada Research Chairs
KeywordsPhysical medicine and rehabilitationPsychologyStroke (engine)Training (meteorology)RehabilitationPhysical therapyMedicineNeuroscience

Abstract

fetched live from OpenAlex

This study examines the potential of using mental practice (MP) to promote the learning of 2 mobility tasks in persons with stroke. Twelve patients were trained with MP to increase the loading of the affected limb while standing up from a chair and sitting down. Vertical forces were recorded using force plates under each foot and the chair. Changes in the loading of the affected limb and in task duration, immediately after 1 training session and 24 h later, served as outcomes. After training, the loading of the affected limb had increased (P < 0.001) during standing up (16.2%) and sitting down (17.9%), and the improvement remained significant 24 h later, indicating a learning effect. In contrast, the duration of the performance did not change with training. The results indicate that, in the early stage of learning with MP, changes in limb-loading strategies are a more sensitive measure of performance than is speed.

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 score0.044
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.329
Teacher spread0.303 · 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

Citations116
Published2004
Admission routes2
Has abstractyes

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