Evidence map›Paper›PMID 41446848›Full record

ArticleFrontiers in medicine2025

The application of blended learning in obstetrics teaching: a comprehensive teaching model integrating an intelligent, interactive induction platform.

Kaifen Gu, Haiyan Pan, Meiyuan Dong, Xuanjin Chen, Huiping Yuan

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Kaifen GuDepartment of Obstetrics, Zhoushan Hospital, Zhoushan, Zhejiang, China.
Haiyan PanDepartment of Public Health, Zhoushan Hospital, Zhoushan, Zhejiang, China.
Meiyuan DongDepartment of Nursing, Zhoushan Hospital, Zhoushan, Zhejiang, China.
Xuanjin ChenUniversity College London, London, United Kingdom.
Huiping YuanDepartment of Director's Office, Zhoushan Hospital, Zhoushan, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Hybrid learning, integrating diverse teaching methods and resources, is promising in education. In nursing, it suits varied learning styles via multiple channels and offers time-place flexibility, aiding busy practice nurses. Information and Communication Technology (ICT) is vital in modern nursing education. Medical intelligent induction platforms, as its form, simulate real-life scenarios for safe skill practice and provide real-time feedback for learning enhancement. Objective: This study aimed to evaluate impact of blended learning in obstetrics teaching using a medical intelligent induction interactive platform on multiple dimensions. These dimensions include the scores of theoretical teaching and practical operation, independent learning ability, comprehensive ability, and overall nursing quality. Methods: From August 2022 to August 2023, 70 practice nurses in our hospital were selected, and they were divided into the control group and the research group. The control group received training and teaching through conventional methods. The research group adopted a blended learning model using the medical intelligent induction interactive platform. Results: The research group outperformed the control group significantly ( Conclusion: Integrating the blended learning method with the medical intelligent induction interactive platform for teaching clinical intern nurses can significantly enhance their relevant nursing knowledge, practical operation skills, and autonomous learning ability, thereby elevating the quality of nursing.

Indexed as

diversified blended teaching learningmedical intelligent induction interaction platformnursing teachingobstetricsstudent nurse

Identifiers

PMID41446848
PMCPMC12722430

What OpenQuestion holds

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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.