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Record W4380893782 · doi:10.1002/alz.060919

Free recall versus combined cued recall and recognition to detect true memory impairment on the Montreal Cognitive Assessment

2023· article· en· W4380893782 on OpenAlexaboutno aff
Liselotte De Wit, Felicia C. Goldstein, David W. Loring

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsFree recallRecallRecall testPsychologyCued recallMontreal Cognitive AssessmentAudiologyCalifornia Verbal Learning TestVerbal learningSerial position effectRecognition memoryCognitionVerbal memoryCued speechCognitive impairmentCognitive psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background The Montreal Cognitive Assessment (MoCA) is widely used as a brief screening measure to characterize overall cognitive status. Although only delayed free recall of the brief 5‐item memory list contributes to widely used MoCA total scores, the optional cued recall and multiple‐choice recognition subtests may provide better diagnostic accuracy than free recall alone. Method Data on 719 individuals with Mild Cognitive Impairment and 601 cognitively unimpaired controls were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The Rey Auditory Verbal Learning Test (AVLT) delayed free recall condition was used to characterize level of memory performance. Participants with demographically adjusted T‐scores of ≤ 2 SDs below the mean were classified as ‘impaired.’ Binary logistic regressions assessed if combined MoCA cued/recognition performance was a significant predictor of impaired delayed recall on the AVLT beyond the contribution of free recall and while covarying for age, education, and gender. Sensitivity, specificity, and likelihood ratio values were also examined for the MoCA free recall and combined cued/recognition scores. Result Free recall on the MoCA was a significant predictor of delayed recall on the AVLT (b = ‐1.207, Wald χ2 (1) = 128.044, p < 0.001, OR = 0.299, 95%CI = [0.243, 0.369]. The addition of the combined MoCA cued recall/recognition conditions improved the overall model fit (χ2(1) = 30.616, p<.001) and predicted impaired AVLT recall such that for every additional word on combined MoCA cued recall/recognition, the likelihood of being in the AVLT memory impaired group decreased by 33% (b = ‐0.400, Wald χ2 (1) = 29.834, p < 0.001, OR = 0.670, 95%CI = [0. 581, 0.774]). Combined MoCA cued recall/recognition had both higher specificity and likelihood ratios in detecting AVLT memory impairment than MoCA free recall, while higher sensitivity values were present for MoCA free recall (see Table 1). Conclusion Use of combined cued/recognition memory conditions provides clinicians with improved diagnostic accuracy in detecting memory impairment. In settings where specificity in detecting memory impairment is important, administration of the MoCA free recall as well as cued recall and recognition conditions is recommended.

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)0.004
metaresearch head score (Gemma)0.016
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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.332
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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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