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Record W4308275198 · doi:10.35335/midwifery.v10i4.828

The Effect of Pregnancy Gymnastics on Reducing Pain on The Backs of Pregnant Women in the Practice of Independent Midwives Sri Ratu Alam Batam City in 2022

2022· article· en· W4308275198 on OpenAlexaboutno aff
Lisa Putri Utami Damanik, Sri Ratu Alam

Bibliographic record

VenueScience Midwifery · 2022
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyObstetricsLow back painPhysical therapyGynecologyAlternative medicine

Abstract

fetched live from OpenAlex

Pregnancy brings great changes in the female body, including the back. Since entering the second tricemester period, some pregnant women began to experience back pain due to the increasingly large baby. 50-80% of women have experienced back and hip pain during pregnancy, chiropractic doctor Ronald J. Tyszkowski said. Back pain is a side effect of a normal pregnancy. The prevalence of spinal pain in pregnant women occurs more than 50% in the United States, Canada, Iceland, Turkey, Korea, and Israel. Meanwhile, in northern America, Africa, the Middle East, Norway, Hong Kong, the prevalence is higher which ranges from 21% to 89.9%. The results of research on pregnant women in various regions in Indonesia reached 60-80% of pregnant women experiencing back pain in their pregnancies. In East Java, around 65% of all pregnant women experience back pain. The method used with the Crossectiona design was a study sample of pregnant women in the II and III trimesters with a total of 35 people. Based on the results of research conducted at BPM Sri Ratu Alam Batam City on, using the Statistics Produck Service Solution (SPSS) program and from the analysis using the Chi-Square test, a P Value value = 0.001 < 0.05 was obtained, this shows that there is an influence of pregnant gymnastics on reducing pain in the back of pregnant women at BPM Sri Ratu Alam Batam City

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)0.032
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.017
GPT teacher head0.323
Teacher spread0.306 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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