Evidence map›Paper›PMID 38327397›Full record

ArticleHeliyon2024

Core competence of midwives in township hospitals and its influencing factors-A cross-sectional study.

Huiyi Luo, Huping Gong, Feng Luo, Ying Xing, Xin Wang, Jingwen Huang, Mei Ding, Dongmei Lin, Yanli Lan

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In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Huiyi LuoCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Huping GongCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Feng LuoDepartment of Obstetrics, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China.
Ying XingCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Xin WangCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Jingwen HuangCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Mei DingCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Dongmei LinCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.
Yanli LanCollege of Nursing, Gannan Medical University, Ganzhou, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to assess the core competence of midwives in township hospitals through a self-assessment questionnaire. The relationship between professional identity and core competence and the factors influencing midwives' core competence was also investigated. Method: Convenience sampling was conducted in 77 township hospitals in Ganzhou, Jiangxi Province, China, with 150 participants. The questionnaires were distributed online in November 2021. We conducted a descriptive data analysis, a correlation analysis of the two variables of professional identity and core competencies, and multivariate linear regression to analyse the influencing factors, including the sociodemographic information, the Midwife Core Competence Scale, and the Nurses' Professional Identity Scale scores. Results: The mean score for the core competence was 206.43 (±37.45) out of 270. The highest score was for pregnancy care (3.97 ± 0.70) and the lowest was for newborn care (3.72 ± 0.78). The independent sample Conclusions: The core competencies of midwives in township hospitals were lower than those reported in other studies. Advancements in education, midwifery working years, and professional identity may increase midwives' core competencies.

Indexed as

Core competenceCross-sectional studyInfluencing factorsMidwifeTownship hospitals

Identifiers

PMID38327397
PMCPMC10848002

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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.