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Record W4406707295 · doi:10.1177/10538135241296772

Improving Gait Ability and Cognition Function through Action Observation Training in Elderly with Dementia

2025· article· en· W4406707295 on OpenAlexaboutno aff
Cinoo Kang, Se‐Hee Park, Sung‐Min Son

Bibliographic record

VenueNeurorehabilitation · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsCadenceGaitDementiaCognitionPhysical medicine and rehabilitationMontreal Cognitive AssessmentPsychologyPhysical therapyTimed Up and Go testMedicineCognitive impairmentDiseaseInternal medicineBalance (ability)Psychiatry

Abstract

fetched live from OpenAlex

BackgroundDementia is one of the most prevalent conditions among older adults.ObjectiveThis study aimed to investigate the effect of action observation training (AOT) on gait ability and cognition in older individuals with dementia.MethodsA total of 36 participants were randomly assigned to the experimental (n=18) or control (n=18) group. The 5-week intervention involved 45-min sessions. The participants engaged in general group exercises for 30 min. The experimental group watched a training video for 5 min, while the control group watched a scenic video. Subsequently, both groups underwent functional training for 10 min. All participants were assessed using a gait analyzer (G-walk), Dynamic Gait Index (DGI), timed up and go (TUG) test, and the Korean version of the Montreal Cognitive Assessment (MoCA-K) before and after the intervention.ResultsThe two groups showed significant within-group changes in gait velocity, cadence, stride length, DGI, and MoCA-K scores (p<0.05). However, the TUG test showed a significant differences only in the experimental group (p<0.05). A significant difference was observed between the experimental and control groups regarding the changes in gait velocity, cadence, DGI, TUG test, and MoCA-K score after the intervention (p<0.05).ConclusionsThe study suggest that AOT is effective in improving the gait and cognitive abilities of older individuals with dementia.

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 score0.470
Threshold uncertainty score0.571

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 communication0.0000.001
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 head0.033
GPT teacher head0.290
Teacher spread0.257 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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