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Record W1567493569 · doi:10.5539/gjhs.v7n6p198

The Effect of Mother's Voice on Arterial Blood Sampling Induced Pain in Neonates Hospitalized in Neonate Intensive Care Unit

2015· article· en· W1567493569 on OpenAlexvenueno aff
Elham Azarmnejad, Forogh Sarhangi, Mahrooz Javadi, Nahid Rejeh

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeonatal intensive care unitBlood samplingAnesthesiaPain scaleIntensive care unitIntensive careSampling (signal processing)Arterial bloodTest (biology)PediatricsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Due to devastating effects of pain in neonates, it is very important to ease it though safe and feasible methods. This study was to determine the effect of familiar auditory stimuli on the arterial blood sampling (ABS) induced pain in term neonates. RESEARCH METHOD: This study was done on 30 newborns hospitalized in neonate intensive care unit (NICU) of a hospital in Tehran. Research samples were selected by using convenience sampling and randomly divided into two groups of control and test. In the test group, the recorded mothers' voices were played for the newborns before and after blood sampling procedure. Then, pain measures were recorded 10 minutes before, during and 10 minutes after blood collection based on Neonatal Infant Pain Scale (NIPS); then the pain level changes were reviewed and studied. FINDINGS: The findings showed significant differences between the control and test groups that indicating the effect of mother's voice on reducing the pain of neonates during the ABS (p<0.005). CONCLUSION: Research findings demonstrate that mother's voice reduces ABS induced pain in the term neonates.

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.360
Teacher spread0.328 · 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

Citations50
Published2015
Admission routes1
Has abstractyes

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