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Record W4412034802 · doi:10.1093/ageing/afaf133.108

3153 Comparison of Free-Cog with the Mini-Mental State Examination and Lawton-Brody functional scales

2025· article· en· W4412034802 on OpenAlexaff
Kenneth Rockwood, Selena P. Maxwell, Jodie Lynn Penwarden, Mengtong Sun, Maia von Maltzahn, Shanna Trenaman

Bibliographic record

VenueAge and Ageing · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsCogMedicineMini–Mental State ExaminationClinical psychologyPsychiatryCognitionArtificial intelligenceCognitive impairment

Abstract

fetched live from OpenAlex

Abstract Introduction The Free-Cog is a brief cognitive test designed to capture decline in both general cognition and executive function. The Free-Cog has been validated by comparison with the Mini-Addenbrooke Cognitive Examination in a UK secondary care setting. Here, we compare Free-Cog to the routinely-used Mini-Mental State Examination (MMSE) and the Lawton-Brody Instrumental Activities of Daily Living (IADL) and Physical Self-Maintenance Scales (PSMS). Methods Patients from three memory clinics were recruited (n = 298 records). The Free-Cog, MMSE, IADL and PSMS were administered in-person (n = 267), via telephone (n = 17), or virtually using video conferencing (n = 12). The four tests were compared using Pearson correlation and ability to predict dementia diagnosis using binary logistic regression and the area under receiver operator characteristic (AUROC) curves. Preliminary results In-person Free-Cog score correlations ranged from strong (MMSE; r = 0.86, 95% Confidence Interval [CI]: [0.82–0.89], p < 0.001), to moderate (IADL (r = 0.56, 95% CI: [0.46–0.64], p = <0.001) to weak with the PSMS (r = 0.23, 95% CI: [0.10–0.35], p = <0.001). The Telephone Free-Cog only correlated significantly with MMSE (r = 0.73, 95% CI: [0.39–0.90], p < 0.001) and virtual Free-Cog with MMSE (r = 0.92, 95% CI: [0.74–0.98], p < 0.001) and IADL (r = 0.63, 95% CI: [0.09–0.88], p = 0.03). Each 1-point increase in Free-Cog (Odds ratio [OR]: 0.84, 95% CI: [0.76–0.92], p < 0.001) decreased the odds of being diagnosed with dementia, as the MMSE (OR: 0.79, 95%CI: [0.69–0.90], p < 0.001), and IADL (OR: 0.73, 95% CI: [0.58–0.92], p < 0.01). The Free-Cog (AUROC = 0.79) best discriminated between dementia and diagnosed otherwise, followed by MMSE (AUROC = 0.74), and IADL (AUROC = 0.69), whereas the PSMS did not (AUROC = 0.43). Conclusion The Free-Cog appears to be a free-of-cost, valid alternative to the routinely used MMSE, and supplements the IADL scale in capturing cognitive and functional changes associated with neurodegenerative diseases of cognition.

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 score0.288
Threshold uncertainty score0.145

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 head0.016
GPT teacher head0.297
Teacher spread0.281 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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