Evidence map›Paper›PMID 39004705›Full record

ArticleBMC nursing2024

Mindful self-care among oncology nurses in China: a latent profile analysis.

Yan Shi, Peng Wang, Lamei Liu, Mengmeng Li

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Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yan ShiSchool of Nursing and Health, Zhengzhou University, No. 101 Science Avenue, Zhengzhou, Henan Province, China.
Peng WangSchool of Nursing and Health, Zhengzhou University, No. 101 Science Avenue, Zhengzhou, Henan Province, China. upliz@zzu.edu.cn.
Lamei LiuSchool of Nursing and Health, Zhengzhou University, No. 101 Science Avenue, Zhengzhou, Henan Province, China.
Mengmeng LiZhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOncology nurses are considered the group with the highest risk for moral distress, compassion fatigue and burnout. Mindful self-care may help oncology nurses improve their well-being and solve psychological problems. However, the investigation and in-depth analysis of mindful self-care among oncology nurses in China is lacking.

objectivesTo identify heterogeneity groups of oncology nurses on mindful self-care ability and examine the sociodemographic correlation to these profiles.

designCross-sectional descriptive study.

participantsThe study was carried out among oncology nurses in two affiliated comprehensive hospitals and one affiliated oncology hospital. A total of 839 oncology nurses were enrolled in this survey.

methodsFrom January to May 2023, a cross-sectional study was carried out among oncology nurses using convenient sampling. The subjects were given the brief Mindful Self-Care Scale (B-MSCS) and the General Demographic Information Questionnaire. Latent profile analysis using the Mplus 7.4 program was used to separate oncology nurses' mindful self-care into a variety of subgroups. The SPSS 25.0 statistical program was used to analyze the data. One-way ANOVA and the chi-square test were performed to compare the score of B-MSCS in each class and the difference in sociodemographic characteristics among the subgroups. Multinomial logistic regression was used to examine the influence of the sociodemographic variables on each class.

resultsThe total score of the B-MSCS was 76.40 ± 13.19. The support structure dimension had the highest score, with an average mean value of 3.60, and physical care had the lowest score at 2.57. The findings of the latent profile analysis showed that respondents were divided into three classes, moderate mindful self-care(51.2%), low-low mindful relaxation(14.8%), and high-high mindfulness self-awareness(34.0%). Across scale scores and dimensions, three groups demonstrated statistically significant differences (p < 0.05). Univariate analysis revealed significant differences between the three profiles in terms of professional title, position, concern about self-care, interest in mindfulness, and experience with meditation (p < 0.05). Profile membership was predicted by 3 factors, namely, self-care status, interest in mindfulness, and experience with meditation.

conclusionThe mindful self-care among oncology nurses can be categorized into three latent profiles: moderate mindful self-care, low-low mindful relaxation, and high-high mindfulness self-awareness. Multinomial logistic regression results indicated that whether oncology nurses concern about self-care, interest in mindfulness and have experience with meditation influenced different latent profiles. Nursing manager should develop targeted intervention based on the typological characteristics of the oncology nurses to improve their mindful self-care ability and mental health.

Indexed as

ChineseInfluencing factorsLatent profile analysisMindful self-careOncology nurses

Identifiers

PMID39004705
PMCPMC11246578

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