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Record W4380893705 · doi:10.1002/alz.064520

Modality matters for health disparity groups on the Montreal Cognitive Assessment (MoCA): Findings from the Einstein Aging Study (EAS)

2023· article· en· W4380893705 on OpenAlexaboutno aff
Cuiling Wang, Caroline O. Nester, Katherine H. Chang, Laura A. Rabin, Ali Ezzati, Richard B. Lipton, Mindy J. Katz

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentGerontologyMedicineIntraclass correlationEthnic groupDementiaPsychologyDemographyCognitionClinical psychologyCognitive impairmentPsychiatryInternal medicinePsychometrics

Abstract

fetched live from OpenAlex

Abstract Background The Telephone‐Montreal Cognitive Assessment (T‐MoCA) is a widely‐used, remotely administered cognitive screen. The T‐MoCA demonstrates adequate psychometric properties and may be used when standard, in‐person administration of the MoCA is not feasible (Katz et al., 2020). There is a critical need to investigate the agreement of the T‐MoCA across administration modalities (in‐person versus telehealth) among ethnically and racially diverse populations. Methods The Einstein Aging Study (EAS) includes a community‐based of racially/ethnically diverse community‐dwelling individuals, ≥ age 70 from the Bronx, NY. Participants (N = 424) were free of dementia at enrollment and completed the T‐MoCA along with in‐person neuropsychological tests including the MoCA‐22, which excludes items unsuitable for telephone administration paralleling the T‐MoCA (Table 1). Intraclass correlation coefficients (ICCs) between T‐MoCA and MoCA‐22 were used to measure agreement. Linear mixed effects models were applied to compare mean scores and ICCs among ethnic/racial groups, with and without adjusting for age, gender, education and depressive symptoms. Results Participants were on average 78.2 years, 65.8% female, 47.6% non‐Hispanic White, 38.0% non‐Hispanic Black, and 14.4% Hispanic. There was no significant difference between mean T‐MoCA and MoCA‐22 scores and no differential associations with age, gender, education, and depressive symptoms. For both modalities, NH Black (difference ‐1.54, p<.0001) and Hispanic (difference ‐2.04, p<.0001) groups demonstrated significantly lower scores compared to non‐Hispanic Whites (Table 2). As shown in Table 2, ICCs among non‐Hispanic White, non‐Hispanic Black, and Hispanic groups were 0.64, 0.50 and 0.42, respectively, and comparisons of ICCs to non‐Hispanic White were significantly lower in non‐Hispanic Black (p = 0.0495) and borderline significant in Hispanic participants (p = 0.0552). Findings were similar after adjusting for covariates. Conclusion The agreement between telephone and in‐person modalities of the MoCA was weaker in non‐Hispanic Black and Hispanic participants (compared to non‐Hispanic White). Further investigation of factors and/or items that contribute to these lower correlations is warranted. Although the T‐MoCA and other remotely administered cognitive screens have the potential to broaden accessibility to marginalized groups, researchers must use caution when developing or selecting appropriate demographically adjusted norms and interpreting scores of diverse older adults.

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)0.003
metaresearch head score (Gemma)0.014
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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.054
GPT teacher head0.375
Teacher spread0.321 · 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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