Evidence map›Paper›PMID 40312687›Full record

ArticleBMC nursing2025

Development and validation of an evaluation index system of health education competence for dental nurses in China: a mixed methods study.

Xiaowen Feng, Wei Xiao, Fang Shen, Ziwen Ye, Wanying Su, Anqi Cai, Xiaohong Wu, Jinsu Chen

Abstract read
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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
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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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Xiaowen FengSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.ORCID http://orcid.org/0009-0005-6684-8834
Wei XiaoSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China. 2012690440@gzhmu.edu.cn.ORCID http://orcid.org/0009-0005-1374-8178
Fang ShenSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.
Ziwen YeSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.ORCID http://orcid.org/0000-0003-3331-9301
Wanying SuSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.
Anqi CaiSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.
Xiaohong WuSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.
Jinsu ChenSchool and Hospital of Stomatology, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Medical University, Guangdong, China.

Funding

Guangdong Medical Research Foundation A2024302The nursing key specialty training project of Stomatological Hospital Affiliated to Guangzhou Medical University in 2023 HL202301
6 · The paper itself

Abstract

backgroundThe global prevalence of oral diseases has imposed substantial health and economic burden. In China, oral health knowledge, behaviors, and literacy among residents remain insufficient, highlighting the need for improvement. Thus, strengthening the health education competence of dental nurses is important to address this issue, enhance oral health education, and support the development of an effective evaluation system. Therefore, this study aimed to develop a set of evaluation tools to facilitate the scientific and objective assessment of dental nurses' health education competence.

methodsA mixed-methods approach integrating qualitative and quantitative research methods was employed. Initially, we constructed a pool of index system items through a thorough literature review and semi-structured interviews. The initial draft was then refined using the Delphi method, which involved expert consensus to enhance accuracy and relevance. We determined the weights of the items using the Analytic Hierarchy Process, and to assess the reliability and validity of the constructed system, a questionnaire survey was conducted, followed by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

resultsA total of 15 experts, including dental nursing and dentistry professionals, participated in the Delphi process, resulting in 3 primary, 11 secondary, and 46 tertiary indicators. The experts' enthusiasm in the two rounds was 93.75% and 100%, with authority coefficients of 0.88 and 0.92, and coordination coefficients ranging from 0.10 to 0.41 and 0.10-0.22, respectively. A total of 425 questionnaires were collected, with a Cronbach's α value of 0.978. EFA identified four common factors and led to the exclusion of 15 items, leaving 31 items that explained 70.43% of the total variance. The final evaluation system included 4 primary, 9 secondary, and 31 tertiary indicators. CFA showed good model fit (χ

conclusionThe evaluation tool constructed in this study demonstrates adequate psychometric properties (e.g., reliability and validity) and can serve as a valuable resource for evaluating the health education competence of dental nurses in China, ultimately informing the development of targeted strategies to enhance their skills and improve public oral health outcomes.

Indexed as

Dental nursesEvaluation indexHealth education competenceIceberg model

Identifiers

PMID40312687
PMCPMC12046882

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LicenceCC BY-NC-ND
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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.