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Record W2098217464 · doi:10.1017/s1041610213002615

A Bahasa Malaysia version of the Montreal Cognitive Assessment: validation in stroke

2014· article· en· W2098217464 on OpenAlexaboutno aff
Ramesh Sahathevan, Nur Ayub Md Ali, Fiona Ellery, Noor Farhanis Mohamad, Nashrah Hamdan, Norlinah Mohd Ibrahim, Leonid Churilov, Toby Cumming

Bibliographic record

VenueInternational Psychogeriatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersState Government of Victoria
KeywordsMontreal Cognitive AssessmentStroke (engine)MedicineMalayPopulationCognitionPhysical therapyCognitive impairmentGerontologyPsychiatryLinguistics

Abstract

fetched live from OpenAlex

BACKGROUND: Many stroke research trials do not include assessment of cognitive function. A Very Early Rehabilitation Trial (AVERT) is an international multicenter study that includes the Montreal Cognitive Assessment (MoCA) as an outcome. At the Malaysian AVERT site, completion of the MoCA has been limited by low English proficiency in some participants. We aimed to develop a Bahasa Malaysia (BM) version of the MoCA and to validate it in a stroke population. METHODS: The original English version of the MoCA was translated into BM and then back-translated to ensure accuracy. Feasibility testing in a group of stroke patients prompted minor changes to the BM MoCA. In the validation phase, a larger group of bilingual stroke patients completed both the original English MoCA and the finalized BM MoCA, with presentation order counter-balanced. RESULTS: Forty stroke patients participated, with a mean age of 57.2 (SD = 10.3). Agreement between BM MoCA and English MoCA was strong (intra-class correlation coefficient = 0.81, 95% CI 0.68-0.90). Scores on BM MoCA were slightly higher than scores on English MoCA (median absolute difference = 2.0, IQR 0-3.5), and this difference was present regardless of which version was completed first. CONCLUSIONS: The existence of a validated BM version of the MoCA will be of major benefit to clinicians and researchers in Malaysia and the wider South-east Asian region, where the Malay language is used by over 200 million people.

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 score0.044
Threshold uncertainty score0.230

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 head0.009
GPT teacher head0.308
Teacher spread0.300 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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