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Record W3049588300 · doi:10.3389/fmed.2020.00447

Validation of the Russian Version of the MoCA Test as a Cognitive Screening Instrument in Cognitively Asymptomatic Older Individuals and Those With Mild Cognitive Impairment

2020· article· en· W3049588300 on OpenAlexaboutno aff
Tamar Freud, Anna Vostrikov, Tzvi Dwolatzky, Boris Punchik, Yan Press

Bibliographic record

VenueFrontiers in Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionAsymptomaticPopulationCognitive evaluation theoryTest (biology)PsychologyGerontologyMedicineAudiologyPhysical therapyCognitive impairmentPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Background: Mild Cognitive Impairment (MCI) in older people is a common syndrome that should be recognized, since interventions such as physical exercise and cognitive training may be useful in maintaining cognitive function and planning for the future is useful. The MoCA test is a useful screening instrument for MCI, but the Russian version of this test has not yet been validated in this condition. The aim of the present study was to validate the Russian version of the MoCA test. Methods: The study population included 160 residents of Israel aged 65 years and older with Russian as their mother tongue, 80 with a clinical diagnosis of MCI, and 80 cognitively asymptomatic controls (AC). All participants underwent cognitive evaluation the Russian version of the MoCA test (MoCA-Ru), and a computerized cognitive assessment battery (Neurotrax) validated for MCI. Results: The mean age of the study population was 78±6.6 years and 123 (76.9%) were women. The MoCA-Ru score was higher in the AC group than in those with MCI (24.3±3.74 vs. 20.2±3.07, P<0.0001). Based on ROC analysis MoCA-Ru was found to have good discriminating capacity for differentiating participants with MCI from asymptomatic controls at a cutoff value of 25. Conclusions: We found the Russian language version of the MoCA test to be useful as a screening tool for MCI. However, there is a need for further adaptation and validation of the current Russian version of the MoCA.

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)0.001
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 score0.072
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.289
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 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

Citations27
Published2020
Admission routes1
Has abstractyes

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