Evidence map›Paper›PMID 41387857›Full record

ArticleBMC nursing2025

Knowledge, attitudes and practices levels of clinical nurses towards humanistic caring: the first nationwide multi-centre cross-sectional survey in China.

Hongwei Chang, Danli Xiong, Deying Hu, Ruiying Yu, Yanjin Liu, Dongmei Dai, Zheng Lin, Yongyi Chen, Guanghong Zhao, Rong Tan and 2 more

Abstract read
In one paragraph

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Hongwei Chang *Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Danli Xiong *Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Deying HuDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Ruiying YuChongqing Jiulongpo People's Hospital, Chongqing, China.
Yanjin LiuDepartment of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Dongmei DaiTaian Municipal Hospital, Taian, Shandong Province, China.
Zheng LinDepartment of Nursing, Jiangsu Province Hospital, Nanjing, Jiangsu Province, China.
Yongyi ChenDepartment of Nursing, Hunan Cancer Hospital, Changsha, Hunan Province, China.
Guanghong ZhaoWuhan City Polytechnic, Wuhan, Hubei Province, China.
Rong TanDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Hongyan WuDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China. 641270729@qq.com.
Yilan LiuDepartment of Nursing, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China. yilanl2020@163.com.

Funding

the Chinese Nursing Association, 2020 Research Projects. ZHKY202006
6 · The paper itself

Abstract

backgroundHumanistic caring in China has developed rapidly in recent years; however, patients’ satisfaction with nurses’ humanistic caring remains moderate. To date, there has been no nationwide, multi-centre, large-sample survey exploring nurses’ knowledge, attitudes, and practices (KAP) regarding humanistic caring, which limits the identification of gaps and evidence-based strategies for improvement.

aimThis study aimed to assess the levels of knowledge, attitude, and practices regarding humanistic caring among nurses in tertiary hospitals across China, and to analyze the associated influencing factors, thereby providing a data-driven foundation and practical evidence for developing targeted improvement strategies.

methodA multi-centre cross-sectional survey was conducted from July to August 2022 in 25 provinces (cities and districts) across China. Nurses meeting the inclusion and exclusion criteria were recruited through convenience sampling in tertiary hospitals. Data were collected using a self-developed demographic questionnaire and The Knowledge, Attitudes and Practices of Clinical Nursing Staff on Humanistic Care Questionnaire developed by Li Yuqin. The original scale demonstrated excellent reliability and validity (content validity index = 0.980; Cronbach’s α = 0.982; test–retest reliability = 0.983), and the Cronbach’s α in the present study was 0.991 (P < 0.001). Questionnaires were distributed and collected via the online platform Questionnaire Star. A total of 14,305 valid responses were obtained, yielding an effective response rate of 99.72%. Data were analyzed using SPSS version 26.0 for descriptive and inferential statistics.

resultAmong the 14,305 participants from 25 provinces, 95.48% were female, with a mean age of 32.37 ± 6.62 years; 85.53% held at least a bachelor’s degree. Notably, 42.17% had never received humanistic caring training. The mean scores for knowledge, attitude, and practice were 80.24%, 83.62%, and 87.95%, respectively, with practice scoring highest and knowledge lowest. Significant differences in KAP scores were observed across gender, region, department, professional title, work experience, and job-related factors (all P < 0.05). Nurses who expressed love for nursing, engaged in self-caring, received family support, and were satisfied with their work and salary or had undergone humanistic caring training achieved significantly higher scores in all three dimensions (P < 0.001). Stepwise multiple regression identified job and salary satisfaction, enthusiasm for nursing, self-caring awareness, and prior training as major positive predictors of knowledge and attitude, whereas knowledge and attitude significantly predicted humanistic caring practices. Correlation analysis confirmed strong positive associations among the three dimensions (r = 0.636–0.827, P < 0.001), aligning with the KAP theoretical model.

conclusionChinese clinical nurses demonstrate moderate levels of knowledge and attitudes toward humanistic caring but relatively strong humanistic caring behaviors. Training programs should be strengthened, with content emphasizing the concept, significance, and core competencies of humanistic caring. Hospitals are encouraged to integrate humanistic values into organizational management and promote a supportive humanistic caring culture to enhance nurses’ humanistic practice.

Indexed as

ChineseHumanistic caringHumanistic nursingInfluencing factorsNational surveyNurses

Identifiers

PMID41387857
PMCPMC12817640

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.