Evidence map›Paper›PMID 42742490›Full record

ReviewInternational nursing review2026

Healthcare Professionals' Perspectives on Nursing Competency: A Synthesis of Qualitative Evidence.

Junlin Yang, Na Wang, Bi Guan, Yan Li, Hai Yu, Haiyan Wan, Xiaofei Gao, Liangnan Zeng

Abstract readReview
In one paragraph

Review in International nursing review, 2026. 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

8 authors.

Junlin YangOperating Room, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0006-9657-1482
Na WangDepartment of Nursing, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Bi GuanDepartment of Nursing, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yan LiDepartment of Nursing, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Hai YuHuman Resources Department, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
Haiyan WanDepartment of Nursing, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Xiaofei GaoOperating Room, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
Liangnan ZengDepartment of Nursing, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.ORCID https://orcid.org/0000-0002-3720-8230

Funding

Health Commission of Chengdu 2026514Sichuan Provincial Administration of Traditional Chinese Medicine 26MSZX096
6 · The paper itself

Abstract

aimThis study systematically evaluates healthcare professionals' views on nursing competency in an effort to provide a foundation for developing an evaluation framework for it.

backgroundCompetency is the core part of determining nurses' talent. This study represents a meta-synthesis of qualitative research on the competency of medical staff for nurses and, as such, provides a reference for exploring innovative nursing human resource management models.

methodsWe searched Web of Science, PubMed, Cochrane Library, Embase, and CINAHL for qualitative studies on nursing competency published from their respective inceptions to February 2024. Literature quality was assessed using the 2016 Joanna Briggs Institute criteria, and a subsequent meta-synthesis was used to analyze the data.

resultsTen studies from Asian developing countries were finally included. From these studies, the views of medical staff regarding the capabilities required to hold nursing positions, including complexity of personal traits, comprehensive knowledge and skill requirements, specialized competency requirements, and requirements for advanced nursing roles, were systematically categorized and summarized. DISCUSSION: The diverse views of healthcare professionals on nursing competency in the healthcare settings of Asian developing countries were characterized by various traits and a multidimensional perspective on the development of the nursing profession.

conclusionThis study systematically delineates the multidimensional expectations held by healthcare professionals in Asia concerning nurses' competencies and finds that the region's nursing profession is undergoing a profound transformation from "technical operational labor" to "knowledge-intensive profession." It therefore may provide references for educational system reform, clinical training, and career path planning and policy formulation. IMPLICATIONS FOR NURSING: This meta-synthesis may help to enable nurses to formulate individualized career development plans that are both suited to their own characteristics and responsive to the evolving demands of the healthcare industry IMPLICATIONS FOR HEALTH POLICY: The healthcare landscape in Asia has been undergoing a profound transformation. Driven by population aging, persistent nursing workforce shortages, and the advancement of digital transformation, multiple factors have rendered the professional demands placed on nurses by other healthcare professionals increasingly complex. In response to this shift, policymakers can adopt a series of measures, including broadening nurses' scope of practice; advancing nursing education reform; reforming the nurse compensation system to ensure effective recruitment, retention, and equitable deployment; implementing mandatory staffing standards; and providing institutional support and resources for nurses' professional development.

Indexed as

Attitude of Health PersonnelClinical CompetenceNurse's RoleAsiaDeveloping CountriesFemaleHumansMaleQualitative Research

Identifiers

PMID42742490
PMCPMC13576856

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.