Evidence map›Paper›PMID 36763618›Full record

Trial reportPloS one2023

Efficiency analysis by training sequence of high-fidelity simulation-based neonatal resuscitation program (NRP).

Seoheui Choi, Hoyeon Shim, Jang H Lee

Abstract readClinical Trial
In one paragraph

Trial report in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Seoheui ChoiDepartment of Paediatrics, Ajou University School of Medicine, Suwon, South Korea.ORCID 0000-0001-7515-0554
Hoyeon ShimDepartment of Simulation Center, Hallym University Dongtan Sacred Heart Hospital, Hwaseong-si, South Korea.
Jang H LeeDepartment of Paediatrics, Ajou University School of Medicine, Suwon, South Korea.ORCID 0000-0003-4765-9948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study was conducted to find a more effective education method in a neonatal resuscitation program (NRP) using a high-fidelity simulation that has recently shown positive results in terms of its effectiveness. STUDY

designA single-blind prospective cohort study was performed. The high-fidelity simulation model was used in a formal NRP training course for trainees caring for neonatal patients. The trainees were divided into a group that conducted the scenario after the lecture (Group A) and a group that attended the lecture after the scenario (Group B) and they both took the test before, during, and after the training.

resultsThe increase in score after theory training was statistically significant in both groups, but the final score did not differ between the two groups. However, when compared by career, in Group A, trainees under 24 months tended to be more effective, and in Group B, trainees over 24 months tended to be more effective.

conclusionThe difference in short-term memory of trainees according to the order of education identified by the test score was not prominent, but it was found that the degree of difference in test scores for the order of education tended to be different according to the career. It is thought that the effectiveness of the training might be increased by changing the education order according to the degree of experience of each trainee. More effective educational methods should be introduced by continuously developing lectures for repeated education of various trainees in the future.

Indexed as

High Fidelity Simulation TrainingSimulation TrainingClinical CompetenceHumansInfant, NewbornProspective StudiesResuscitationSingle-Blind Method

Identifiers

PMID36763618
PMCPMC9916567

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.