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Evaluation of the Effectiveness of Neurocognitive Rehabilitation of Patients with Mild Cognitive Decline under Restrictions during the COVID-19 Pandemic

2023· article· en· W4315796148 on OpenAlexaboutno aff
Roshchina If, Timur Syunyakov, N. G. Osipova, M V Kurmyshev, Victor Savilov, A. V. Andruchsenko

Bibliographic record

VenuePsikhiatriya · 2023
Typearticle
Languageen
FieldMedicine
TopicTechnology and Human Factors in Education and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeurorehabilitationNeuropsychologyCognitionNeurocognitivePsychologyMini–Mental State ExaminationNeuropsychological assessmentMultivariate analysis of varianceCognitive declineNeuropsychiatryRehabilitationClinical psychologyPhysical medicine and rehabilitationPhysical therapyPsychiatryMedicineDementiaCognitive impairmentDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Background: the development of programs for the correction of cognitive impairment in elderly patients with various types of mild cognitive decline is an urgent task of geriatric medicine and clinical psychology. The aim of the study was to conduct neuropsychological and psychometric evaluation of the results of a modified neurorehabilitation program (combination of full time and part time studies) in patients of the “Memory Clinic”. Patients and methods: a total of 114 patients (mean age 73 years) with mild cognitive impairment was studied. Neuropsychological and psychometric evaluation of the dynamics of the cognitive sphere in patients with mild cognitive decline (MCI) before and after participation (week 6) in the full-time/part-time neurorehabilitation program at the “Memory Clinic” was carried out. For psychometric assessment, the Mini-mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used. The neuropsychological study was carried out using the “Express Method for the Study of Cognitive Functions at a Late Age” (N.K. Korsakova et al.). For psychometric assessment, the Mini-mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used. The neuropsychological study was carried out using the “Express Method for the Study of Cognitive Functions at a Late Age” (N.K. Korsakova, E.Yu. Balashova, I.F. Roshchina). Results: using the method of multivariate analysis of variance (MANOVA), a statistically significant effect (p < 0.05) of the neurorehabilitation program on psychometric tests (MMSE, MoCA) and on the total score of the “Express Methods for the Study of Cognitive Functions at a Late Age”, as well as on its subscales —verbal memory, visual memory, semantic memory, dynamic, spatial and regulatory praxis was detected. Conclusions: a psychometric and neuropsychological study showed the effectiveness of a full time/part-time neurocognitive rehabilitation program for patients with mild cognitive decline under conditions of limited visits to the Memory Clinic during the COVID-19 pandemic.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.386
Teacher spread0.328 · 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".

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Citations3
Published2023
Admission routes1
Has abstractyes

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