MétaCan
Menu
Back to cohort
Record W3172018166 · doi:10.1111/jgs.17318

Utility of a short, <scp>telephone‐administered</scp> version of the Montreal Cognitive Assessment

2021· article· en· W3172018166 on OpenAlexaboutno aff
Lee A. Jennings, Katy Araujo, Can Meng, Peter Peduzzi, Peter Charpentier, David B. Reuben

Bibliographic record

VenueJournal of the American Geriatrics Society · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute on AgingPatient-Centered Outcomes Research Institute
KeywordsMontreal Cognitive AssessmentMedicineDementiaGerontologyTelephone interviewCognitionCoronavirus disease 2019 (COVID-19)Cognitive impairmentPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Because of the COVID-19 pandemic, the ongoing D-CARE pragmatic trial of two models of dementia care management needed to transition to all data collection by telephone. METHODS: For the first 1069 D-CARE participants, we determined the feasibility of administering a short 3-item version of the Montreal Cognitive Assessment (MoCA) to persons with dementia by telephone and examined the correlation with the full 12-item version. RESULTS: The 3-item version could be administered by telephone in approximately 6 min and was highly correlated with the full MoCA (r = 0.78, p < 0.0001). CONCLUSIONS: This brief version of the MoCA was feasible to collect by telephone and could be used as an alternative to the full MoCA, particularly if the purpose of cognitive assessment is characterization of study participants.

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)0.006
metaresearch head score (Gemma)0.023
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.017
GPT teacher head0.325
Teacher spread0.307 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Geriatrics SocietySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207