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Record W4389250912 · doi:10.36973/jkih.v11i1.496

HUBUNGAN PENGETAHUAN IBU HAMIL TENTANG ANEMIA DENGAN KEPATUHAN MENGKONSUMSI TABLET TAMBAH DARAH DI DESA CITAMIANG WILAYAH KERJA PUSKESMAS KADUDAMPIT KABUPATEN SUKABUMI

2023· article· id· W4389250912 on OpenAlexaff
Susilawati Susilawati

Bibliographic record

VenueJURNAL KESEHATAN INDRA HUSADA · 2023
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Anemia dalam kehamilan adalah kondisi kadar hemoglobin <11gr/dl. Kepatuhan Ibu hamil dalam mengkonsumsi tablet tambah darah selama kehamilan dapat mencegah anemia. Faktor yang dapat mempengaruhi terjadinya kepatuhan adalah pengetahuan. Tujuan penelitian ini untuk mengetahui hubungan pengetahuan Ibu hamil tentang anemia dengan kepatuhan mengkonsumsi tablet tambah darah di Desa Citamiang Wilayah Kerja Puskesmas Kadudampit Kabupaten Sukabumi. Pengetahuan merupakan hasil tahu setelah orang melakukan penginderaan terhadap suatu objek. Kepatuhan merupakan tahap pasien melaksanakan cara pengobatan serta perilaku yang disarankan oleh petugas kesehatan. Jenis penelitian ini adalah penelitian korelasional. Populasi adalah sekumpulan orang ditetapkan peneliti untuk ditarik kesimpulannya dengan sampel sebanyak 46 responden. Cara pengambilan sampel menggunakan total sampling. Analisis hipotesis menggunakan Korelasi Somer’s d. Hasil penelitian menunjukkan sebagian besar memiliki pengetahuan yang kurang dan Sebagian besar memiliki kepatuhan sedang. Hasil uji korelasi didapatkan P-value 0.004 yang berarti H0 ditolak, nilai korelasi somer’s d 0.415. Penelitian ini dapat disimpulkan ada hubungan pengetahuan tentang anemia dengan kepatuhan mengkonsumsi tablet tambah darah. Diharapkan Puskesmas Kadudampit melakukan pembinaan kepada kader untuk meningkatkan motivasi Ibu hamil agar selalu memeriksakan kehamilannya.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.004

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 head0.033
GPT teacher head0.297
Teacher spread0.264 · 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.

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
Published2023
Admission routes1
Has abstractyes

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