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Record W4213325359 · doi:10.55313/ojs.v7i2.61

Hubungan Tingkat Pengetahuan Tentang Penyakit Hipertensi dengan Kepatuhan Kontrol Tekanan Darah di Desa Mangge Kecamatan Barat Kabupaten Magetan

2020· article· id· W4213325359 on OpenAlexaff
Nia Agustin, Siti Maimunah, Edy Prawoto

Bibliographic record

Venuee-Journal Cakra Medika · 2020
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Hipertensi ( tekanan darah tinggi ) merupakan keadaan perubahan dimana tekanan darah dalam pembuluh darah arteri seseorang mengalami peningkatan yang abnormal dan berlangsung secara terus menerus. Kepatuhan Kontrol tekanan darah adalah kegiatan atau aktivitas yang dilakukan penderita hipertensi untuk melakukan perawatan kontrol tekanan darah ke pelayanan kesehatan dan menjalani pengobatan. Tujuan penelitian ini adalah mengalisis hubungan tingkat pengetahuan tentang penyakit hipertensi dengan kepatuhan kontrol tekanan darah di Desa Mangge Kecamatan Barat Kabupaten Magetan. Desain penelitian adalah deskriptif korelasi dengan pendekatan cross sectional. Populasinya adalah penderita hipertensi di Desa Mangge Kecamatan Barat Kabupaten Magetan yang melakukan kontrol tekanan darah ke Puskesmas Tebon, yang berjumlah 33 orang. Data diambil dengan menggunakan kuesioner, lembar observasi, dan menggunakan uji Chi-Square. Hasil penelitian menunjukkan bahwa responden yang mempunyai tingkat pengetahuan yang baik sebanyak 17 orang (56,7%) dan 16 orang (53,3%) patuh melakukan kontrol tekanan darah. Hasil uji statistic Chi Square menunjukkan tingkat pengetahuan tentang penyakit hipertensi signifikan dengan kepatuhan kontrol tekanan darah dengan (nilai ρ = 0,004 dengan nilai α = 0,05 ).

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.041
GPT teacher head0.280
Teacher spread0.239 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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