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Record W2908133500 · doi:10.33490/jkm.v4i2.104

Efektifitas Buku Saku dalam Meningkatkan Pengetahuan Pendamping Ibu Nifas di Kabupaten Mamuju

2018· article· en· W2908133500 on OpenAlexaff
Ahmady Ahmady, Agus Erwin Ashari

Bibliographic record

VenueJurnal Kesehatan Manarang · 2018
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineIntervention (counseling)PediatricsFamily medicinePsychologyNursing

Abstract

fetched live from OpenAlex

Perinatal and neonatal period is a critical period for the baby's life. Two-thirds of infant deaths occur within 4 weeks after delivery and 60% of newborn deaths occur within 7 days after birth. Regular neonatal visits may early detect to prevent infant mortality. The family's role and support is enormous for the regularity of neonatal visits. The objective of the study was to know the effectiveness of the Pocket Book on the Knowledge of the Psychologist's Companion of the Babies' Period and the visit of the neonate. This research uses experimental Pre design. In this study, the subjects in the study consisted of two groups, the intervention group and the non-intervention group. The samples were the nearest relatives and lived in the same house with the mothers who delivered in housemother health service facilities from June to November 2017 in the work area of ​​the Binanga and Puskesmas Padang. The results showed that statistically significant results showed that there were differences in the average score of the puerperal and neonatal visits between the intervention group and the control group, thus the pocket book was effective for the improvement of maternal companion knowledge. Conclusion and Suggestion in this research that pocket book is effective for knowledge enhancement of maternal companion, and hopefully this pocket book need to be tested its validity by experts.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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