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Record W4367296803 · doi:10.1212/wnl.0000000000202732

Telehealth Equivalence of the Montreal Cognitive Assessment (MoCA): Results from the Emory Healthy Brain Study (EHBS) (P6-6.001)

2023· article· en· W4367296803 on OpenAlexaboutno aff
David W. Loring, James J. Lah, Felicia C. Goldstein

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentTelehealthCognitionMoodMedicineConfidence intervalPsychologyTelemedicineClinical psychologyPsychiatryCognitive impairmentHealth careInternal medicine

Abstract

fetched live from OpenAlex

Objective: To characterize potential differences in Montreal Cognitive Assessment (MoCA) performance between in-person cognitive testing and video telehealth administration. In addition to global MoCA scores, we examined potential telehealth effects on mood (PHQ-8, GAD-7), and explored whether the presence of an observer at the participant’s home during remote MoCA testing influenced task performance. Background: Telehealth cognitive testing has become a common assessment approach following the COVID-19 pandemic when in-person testing was restricted for safety considerations. Although the equivalence of telehealth results to the traditional face-to-face testing is often assumed, formal equivalence validation is limited. Design/Methods: Scores from participants in the Emory Health Brain Study (EHBS) were contrasted based upon whether they were tested in the standard face-to-face (F2F) assessment (n=1205) or using a video telehealth administration (n=491). All EHBS participants were cognitively normal via self-report. Results: Total MoCA scores did not differ across administration method (F2F MoCA=26.6, SD=2.4, telehealth MoCA=26.5, SD=2.4). The 95% confidence interval for difference in administration was small (CI = −0.16 – 0.34). When examining individual MoCA domain scores, administration differences were either associated with no statistically significant effect, or if present were due to large sample sizes, were associated with small effect sizes and differences < 0.5 point. Groups did not differ on GAD-7, although F2F patients reported slightly higher GAD-7 scores of 0.4 point but well within the normal range. The presence of an observer during telehealth testing did not influence MoCA scores. Conclusions: While no single study design provides complete evidence of task equivalence between in-person and video telehealth assessment, this report with its large sample size and between subject cohort provides reassurance that administration mode does not introduce systematic performance differences for MoCA test administration. Continuing studies in clinically impaired groups will be needed to demonstrate the robustness of our findings. Disclosure: Dr. Loring has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer Nature. Dr. Loring has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for ILAE. The institution of Dr. Loring has received research support from NIH. Dr. Loring has received publishing royalties from a publication relating to health care. Dr. Lah has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Roche Diagnostics. The institution of Dr. Lah has received research support from Roche. Felicia Goldstein has nothing to disclose.

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)0.021
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 score0.015
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.055
GPT teacher head0.395
Teacher spread0.339 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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