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Record W4399783062 · doi:10.54097/r1dqa896

Study On the Impact of Hand Exercise on The Cognitive Function of The Elderly Brain

2024· article· en· W4399783062 on OpenAlexaboutno aff
Jintao Shen, Xiaowei Xu, Jing Yang

Bibliographic record

VenueAcademic Journal of Science and Technology · 2024
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMontreal Cognitive AssessmentPhysical therapyIntervention (counseling)MedicineCognitive impairmentPhysical medicine and rehabilitationPsychologyPsychiatry

Abstract

fetched live from OpenAlex

This study aims to evaluate the impact of unarmed strength training on the cognitive function of middle-aged and elderly patients with mild cognitive impairment (MCI). The study subjects are 60 elderly male MCI patients from the Community Health Service Center in Hangzhou, with an age range of 66±5 years. The participants were randomly divided into two groups: the control group and the intervention group. The control group did not receive any intervention measures, while the intervention group underwent a 12-week unarmed strength training program. Before and after the study, the Montreal Cognitive Assessment Scale (MoCA) was used to assess the changes in cognitive function of the subjects. The data analysis was conducted using SPSS 23.0 software, and t-tests and chi-square tests were used for inter-group comparisons based on the distribution characteristics of the data. After 12 weeks of unarmed training, the MoCA score of the intervention group at T2 was significantly higher than that of the control group (P<0.05), indicating that the cognitive function of the intervention group had significantly improved. Unarmed strength training has a positive impact on the cognitive function of middle-aged and elderly MCI patients, and a 12-week training program can effectively improve the cognitive ability of this group.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.023
GPT teacher head0.338
Teacher spread0.315 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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