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Record W2900025874 · doi:10.32668/jitek.v5i2.29

EFEKTIFITAS PEMBERIAN WEDANG JAHE TERHADAP FREKUENSI MUAL DAN MUNTAH PADA IBU HAMIL TRIMESTER I DI KABUPATEN BENGKULU UTARA TAHUN 2017

2018· article· en· W2900025874 on OpenAlexaff
Iluh Meta Indrayani, Rialike Burhan, Desi Widiyanti

Bibliographic record

VenueJurnal Ilmu dan Teknologi Kesehatan · 2018
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsNauseaVomitingMedicinePregnancyHyperemesis gravidarumObstetricsAntiemeticGynecologyAnesthesia

Abstract

fetched live from OpenAlex

Emesis gravidarum is a usual complaint that is often experienced by the first trimester pregnant women, and coul develop become hyperemesis gravidarum thus increasing the risk of pregnancy. Ginger is kind of herbs which has been known to prevent nausea vomiting. The purpose of this study is the effectiveness of giving wedang ginger to the frequency of nausea and vomiting in pregnant women trimester I. The design of this research is Quasi experiment with One Group Pre test-Post test design. The sampling technique used purposive sampling with the sample of 10 first trimester pregnant women who experience emesis gravidarum. This research was conducted at Work Area of ​​Air Lais Puskesmas of North Bengkulu Regency on January 5, 2018 until February 6, 2018. Analysis of difference of frequency of nausea vomiting before and after intervention using Paired Sample T-Test. The results of this study indicate the average frequency of nausea vomiting pregnant women trimester I before given wedang ginger of 9.30. While the average frequency of nausea vomiting trimester pregnant women I after given ginger wedang of 4.50. The result of bivariate analysis showed that there was difference of mean of nausea vomiting frequency before and after intervention of wedang ginger equal to 4,80 with p = 0.000. Expected for the community can take advantage of ginger wedang as an alternative treatment before using antiemetic drugs, and can process other variants of ginger plants that can be used to lower the emesis gravidarum frequency.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.041
GPT teacher head0.313
Teacher spread0.272 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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