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Record W3197569287 · doi:10.32628/ijsrst218424

Comparison of Traditional Versus Computer-Based Cognitive Training on Cognition in Elderly with Mild Cognitive Impairment

2021· article· en· W3197569287 on OpenAlexaboutno aff
Vidhi Shah, Bhakti Panchal, Tushar Palekar, P. S. Guruprasad, Pooja Pokar, Kundan Mehta

Bibliographic record

VenueInternational Journal of Scientific Research in Science and Technology · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionCognitive trainingPsychologyHippocampusExecutive functionsCognitive rehabilitation therapyEffects of sleep deprivation on cognitive performanceComputer trainingAudiologyPhysical medicine and rehabilitationMedicineCognitive impairmentNeuroscience

Abstract

fetched live from OpenAlex

Normal ageing cause alterations in the prefrontal cortex, medial temporal lobe system, hippocampus and cerebellum. These changes are the cause of mild cognitive impairment in terms of decreased memory function, reduced speed and executive functions, personality and behavioral disturbances. Computer-based cognitive training is a new tool used for cognitive rehabilitation. This randomized control trial includes 50 subjects, Group A received computer-based cognitive training (n=25) by using BrainHQ app and Group B received Tradition cognitive training (n=25) for 3 weeks. Montreal cognitive assessment (MOCA) was taken as outcome measure. The comparison of difference of pre and post MOCA score between Group A and Group B shows p=0.002. Also comparison of MOCA score between male and female of group A shows statistically significant difference with respect to MALE P=0.008 and FEMALE P=0.000.This study provides a strong evidence that Computer Based Cognitive Training showed added improvements in cognition function compared to traditional training.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.180
GPT teacher head0.456
Teacher spread0.277 · 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.

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
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Scientific Research in Science and TechnologySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207