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Record W2907035321 · doi:10.4103/jehp.jehp_141_17

The effect of auriculotherapy on the severity and duration of labor pain

2018· article· en· W2907035321 on OpenAlexaboutno aff
Masoume Pirhadi, Mahboubeh Valiani, Masoumeh Azimi, ZahraMohebbi Dehnavi, Soheila Mohammadi

Bibliographic record

VenueJournal of Education and Health Promotion · 2018
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineShahidMcGill Pain QuestionnaireLabor painVisual analogue scalePhysical therapyAnalysis of varianceClinical trialSignificant differenceStatistical analysisInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Pain is a common phenomenon and an inevitable part of the labor process. Labor pain is one of the most severe pains. Auriculotherapy is one of the nonpharmacological aspects of relieving pain, reduces the intensity of pain, and improves its compatibility. The purpose of this study was to determine the effect of auriculotherapy on labor pain in primiparous women. MATERIALS AND METHODS: This clinical trial was performed on 84 pregnant women aged between 18 and 35 years, who referred to Isfahan Shahid Beheshti Hospital in 2017. This study was carried out between two groups: control group (receiving routine hospital care) and interventional group (20 min for auriculotherapy). We used the McGill Short-Form Standard questionnaire with Visual Analog Scale. Data were analyzed by SPSS software using paired t-test and ANOVA. RESULTS: The results showed that there was no significant difference between demographic variables in the two groups. Statistical analysis also showed that the severity of labor pain in the interventional group (auriculotherapy) was lower than that of the control group (P = 0.001). CONCLUSION: Auriculotherapy reduces the severity of labor pain in primiparous women. Due to the easy, inexpensive, and noninvasive nature of this method, its use has been recommended in these cases.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.377
Teacher spread0.359 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations54
Published2018
Admission routes1
Has abstractyes

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