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Record W2917076649

GAMBARAN FUNGSI KOGNITIF PADA LANJUT USIA DI KELURAHAN MAASING KECAMATAN TUMINTING

2019· article· ms· W2917076649 on OpenAlexaboutno aff
Mutiara Toreh, Junita Maja Pertiwi, Finny Warouw

Bibliographic record

Venuenot available
Typearticle
Languagems
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychology
DOInot available

Abstract

fetched live from OpenAlex

Latar Belakang:Jumlah penduduk lanjut usia yang terus meningkat dapat menimbulkan masalah kesehatan seperti gangguan fungsi kognitif dan dapat di periksa dengan pemeriksaan Montreal Cognitive Assessment versi Indonesia (INA MoCA) dan Trail Making Test (TMT). Tujuan: Mengetahui gambaran fungsi kognitif pada lanjut usia di Kelurahan Maasing Kecamatan Tuminting. Metode:Penelitiandeskriptif dengan metode crosssectional, dilaksanakan bulan Oktober-November 2018 bertempat di Kelurahan Maasing Kecamatan Tuminting.Hasil: Dari penelitian diperoleh 50 orang yang memenuhi kriteria inklusi. Pemeriksaan Ina MoCA menunjukkan 92% lanjut usia mengalami penurunan fungsi kognitif, pada pemeriksaan TMT-A menunjukkan 96% lanjut usia terganggu dan pada TMT-B menunjukkan 100% lanjut usia terganggu. Kelompok lanjut usia yang paling menunjukkan penurunan fungsi kognitif yaitu jenis kelamin laki-laki, usia 60-74 tahun dan 75-90 tahun, jenis pekerjaan nelayan dan IRT, tingkat pendidikan SMA dan SD, lanjut usia dengan riwayat hipertensi menunjukkan penurunan fungsi kognitif  97% dan lanjut usia dengan riwayat diabetes melitus menunjukkan penurunan fungsi kognitif 75% pada Ina MoCA dan 100% pada TMT. Kesimpulan:Dari hasil penelitian menunjukkan 92% lanjut usia mengalami penurunan fungsi kognitif pada pemeriksaan Ina MoCA dan pada TMT-A 96% terganggu, pada TMT-B 100% terganggu.   Kata kunci : Lanjut usia, fungsi kognitif, Ina MoCA, TMT-A, TMT-B   Abstract Background: The increasing number of elderly people can cause health problems such as impaired cognitive function. Impaired cognitive function can be examined by Montreal Cognitive Assessment Indonesian Version (Ina MoCA) examination and Trail Making Test (TMT). Objective: Knowing overview of cognitive function in elderly at Maasing sub-district Tuminting district. Methods:The descriptive research with cross sectional method, was conducted in October-November 2018 held at Maasing sub-district Tuminting district. Results:From the research gained 50 people who met the inclusion criteria. Ina MoCA examination showed 92% elderly people had decline in cognitive function, on the TMT-A showed 96% elderly people disturbed and on the TMT-B showed 100% elderly people disturbed. The elderly people group showed the most decline in cognitive function that is male gender, age of 60-74 years and 75-90 years, the type of work fishermen and housewives, high school and elementary school level. Elderly people with a history of hypertension showed a decline in cognitive function 97% and elderly people with a history of diabetes mellitus showed a decline in cognitive function 75% on the Ina-MoCA and 100% on the TMT.Conclusion: Based on the result showed 92% elderly people had decline in cognitive function on the Ina MoCA and on the TMT-A 96% disturbed, on the TMT-B 100% disturbed.   Keywords :Elderly people, cognitive function, Ina MoCA, TMT-A, TMT-B

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.016
GPT teacher head0.283
Teacher spread0.267 · 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; both teacher heads agree on what is shown here.

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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Citations9
Published2019
Admission routes1
Has abstractyes

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