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Record W3215577429 · doi:10.3389/fnagi.2021.756891

Comparison of Time Taken to Assess Cognitive Function Using a Fully Immersive and Automated Virtual Reality System vs. the Montreal Cognitive Assessment

2021· article· en· W3215577429 on OpenAlexaboutno aff
Wei Teen Wong, Ngiap Chuan Tan, Jie En Lim, John Carson Allen, Wan Sian Lee, Joanne Hui Min Quah, Paulpandi Muthulakshmi, Tuan Ann Teh, Soon Huat Lim, Rahul Malhotra

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersInfo-communications Media Development AuthorityDuke-NUS Medical SchoolMitsui Sumitomo Insurance Welfare Foundation
KeywordsCognitionVirtual realityHuman–computer interactionFunction (biology)Cognitive evaluation theoryComputer sciencePsychologyNeuroscienceSelf-determination theoryBiology

Abstract

fetched live from OpenAlex

Introduction: Dementia is increasingly prevalent globally. Existing questionnaire-based cognitive assessment tools may not comprehensively assess cognitive function and real-time task-performance across all cognitive domains. CAVIRE (Cognitive Assessment by VIrtual REality), a fully immersive virtual reality system incorporating automated audio-visual instructions and a scoring matrix was developed to assess the six cognitive domains, with potential to maintain consistency in execution of the testing environment and possibly time-saving in busy primary care practice. Aims: This is a feasibility study to compare the completion times of the questionnaire-based Montreal Cognitive Assessment (MoCA) and the CAVIRE in cognitively-healthy Asian adults aged between 35 and 74 years, overall, and in and across each 10-year age group (35–44; 45–54; 55–64; 65–74). Methods: A total of 100 participants with a MoCA score of 26 or more were recruited equally into the four 10-year age groups at a primary care clinic in Singapore. Completion time for the MoCA assessment for each participant was recorded. They were assessed using the CAVIRE, comprising 13 segments featuring common everyday activities assessing all six cognitive domains, and the completion time was also recorded through the embedded automated scoring and timing framework. Results: Completion time for CAVIRE as compared to MoCA was significantly ( p < 0.01) shorter, overall (mean difference: 74.9 (SD) seconds) and in each age group. Younger, vs. older, participants completed both the MoCA and CAVIRE tasks in a shorter time. There was a greater variability in the completion time for the MoCA, most markedly in the oldest group, whereas completion time was less variable for the CAVIRE tasks in all age groups, with most consistency in the 45–54 year-age group. Conclusion: We demonstrate almost equivalent completion times for a VR and a questionnaire-based cognition assessment, with inter-age group variation in VR completion time synonymous to that in conventional screening methods. The CAVIRE has the potential to be an alternative screening modality for cognition in the primary care setting.

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)0.001
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 score0.194
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.377
Teacher spread0.327 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

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