MétaCan
Menu
Back to cohort
Record W3120958254 · doi:10.13005/bpj/2081

A Comparison Between Brain Vitalization Gymnastics and Elderly Gymnastics to Improving Cognitive Function Among Elderly

2020· article· en· W3120958254 on OpenAlexaboutno aff
I Gusti Ayu Dwiantari, Anak Agung Ayu Putri Laksmidewi, I Made Oka Adnyana, I Putu Eka Widyadharma

Bibliographic record

VenueBiomedical & Pharmacology Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionBrain functionElderly peoplePhysical therapyPsychologyMontreal Cognitive AssessmentMedicineGerontologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Objective: Two of the most frequently elderly's health-associated problems are balanced disorder and cognitive decline. One of the solutions to prevent cognitive decline in the elderly is via performing brain vitalization gymnastics. According to these facts and arguments, the authors were interested in studying the effects of brain vitalization gymnastics performed twice every week for four weeks upon cognitive function in the elderly. Methods: This was a randomized pretest-posttest control group design study involving 38 elderly subjects who were registered in the geriatric subgroup of West Denpasar primary health care clinic. The subjects were equally divided into two groups, i.e., those who performed brain vitalization gymnastics and elderly gymnastics. Montreal Cognitive Assessment Indonesian Version(MoCA-Ina) score as tested with paired t-test among brain vitalization gymnastics and elderly gymnastics groups. Results: both groups before and after the exercise increased by 1.53 and 0.11 points, respectively. Furthermore, the brain vitalization gymnastics group had a statistically significant higher MoCA-Ina score as opposed to the elderly gymnastics group (p=0.047). Conclusion: This study had shown that brain vitalization gymnastics was more effective in increasing elderly's MoCA-Ina score as opposed to elderly gymnastics.

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)0.001
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 score0.573
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.394
Teacher spread0.353 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBiomedical & Pharmacology JournalSame topicHealth and Well-being StudiesFrench-language works237,207