Evidence map›Paper›PMID 42310619›Full record

ArticleBMC nursing2026

Self-assessed Traditional Chinese Medicine nursing competency profiles among clinical nurses in a tertiary hospital in China: a cross-sectional latent profile analysis.

Ming Jin, Yongping Lu, Jing Yang, Zhiqiang Wang

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Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Ming JinScience and Technology Innovation Center, Guangyuan Central Hospital, Guangyuan, Sichuan, 628000, China.
Yongping LuScience and Technology Innovation Center, Guangyuan Central Hospital, Guangyuan, Sichuan, 628000, China.
Jing YangScience and Technology Innovation Center, Guangyuan Central Hospital, Guangyuan, Sichuan, 628000, China.
Zhiqiang WangSchool of Medicine, Yangtze University, Jingzhou, Hubei, 434023, China. 1941838243@qq.com.

Funding

the National Natural Science Foundation of China 52503166the Science and Technology Department of Sichuan Province 2024NSFSC1023
6 · The paper itself

Abstract

backgroundTo describe the overall level of self-assessed Traditional Chinese Medicine (TCM) nursing competency among clinical nurses, identify latent competency profiles, and examine demographic and training-related attitude factors associated with profile membership.

methodsThis cross-sectional study was conducted from January to October 2024 at a tertiary Grade A hospital in China. Eligible nurses were recruited voluntarily from multiple clinical departments in which TCM nursing services were routinely provided. A total of 457 valid questionnaires were analyzed. Data were collected using the Traditional Chinese Medicine Nursing Competency Questionnaire and a questionnaire assessing training-related attitudes and needs among TCM nursing staff. Latent profile analysis was used to identify competency profiles, and multinomial logistic regression was performed to examine factors associated with profile membership.

resultsThe overall level of self-assessed TCM nursing competency was moderate. Scores were higher for TCM nursing techniques but lower for advanced clinical practice, indicating relatively limited advanced-practice and integrative application capacity. Latent profile analysis supported a three-profile solution (entropy = 0.846): low self-assessed competency (12.3%), moderate self-assessed competency (64.3%), and high self-assessed competency (23.4%) profiles. Profiles differed significantly in years of service, professional title, educational attainment, intention to participate in training, and perceived importance of training. In multinomial logistic regression, educational attainment, intention to participate in training, and perceived importance of training were consistently associated with membership in higher self-assessed competency profiles. Professional title was significant only in the high-profile contrast, whereas years of service was not independently associated with profile membership after adjustment.

conclusionsClinical nurses working in departments where TCM nursing services were routinely provided showed heterogeneous patterns of self-assessed TCM nursing competency, with most nurses classified into the moderate self-assessed competency profile and advanced clinical practice emerging as a relative weakness. Profile-informed, tiered training strategies focusing on contextualized practice and clinical application may be warranted. However, given the cross-sectional design and reliance on self-reported data, the identified profiles should be interpreted as patterns of perceived competency rather than developmental stages or evidence of progression over time. Longitudinal or intervention studies are needed to further verify these associations. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Clinical nursesCross-sectional studyIntention to participate in trainingLatent profile analysis (LPA)Multinomial logistic regressionSelf-assessed competency profileTraditional Chinese Medicine (TCM) nursing competencyTraining needs

Identifiers

PMID42310619
PMCPMC13520143

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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.