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Record W2953661070 · doi:10.33088/jmk.v10i2.332

PENGARUH PENDIDIKAN KESEHATAN TERHADAP PENGETAHUAN DAN SIKAP WANITA USIA SUBUR TENTANG PEMERIKSAAN IVA TEST

2018· article· en· W2953661070 on OpenAlexaff
Chairun Nisah

Bibliographic record

VenueJURNAL MEDIA KESEHATAN · 2018
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsNonprobability samplingCervical cancerTest (biology)MedicinePopulationHealth educationSampling (signal processing)Simple random sampleFamily medicineSignificant differenceGynecologyDemographyEnvironmental healthCancerNursingPublic healthInternal medicine

Abstract

fetched live from OpenAlex

IVA Test is a simple method in early detection of cervical cancer early. The target of IVA Test is WUS aged 15-49 years. In Bengkulu Province WUS who perform the examination of cervical cancer detection by IVA test method is still low. The purpose of this study is to determine the effect of health education on knowledge and attitude of WUS on examination of IVA test in the work area of Sukamerindu Puskesmas Bengkulu City 2017 ".This research use pre experiment method one group pretest - posttest design. Population taken in this research is married WUS aged 20-49 years in work area of Sukamerindu health center with sample amounted to 30 people taken by purposive sampling technique. Sampling is done by purposive sampling technique. Data analysis using T-dependent Test.The results of this study obtained the average knowledge before the provision of health education that is 6.80 and the average after 13.00 with mean difference 6.2.And obtained the average attitude before the provision of health education that is 35.50 and the average after 38.80 with mean difference 3,3. It was concluded that health education influenced WUS knowledge and attitude about IVA test in Sukamerindu Puskesmas area of Bengkulu city in 2017.It is expected that the puskesmas can actively conduct home visits to provide health education, especially in providing information about the examination of IVA test to married WUS to reduce the risk of cervical cancer.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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