{"title":"与护士精神工作量相关的影响因素：潜在特征分析","authors":"","doi":"10.1016/j.ijnss.2024.04.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>This study aimed to examine the latent profile of nurses' mental workload (MWL) and explore the influencing factors via a person-centred approach.</p></div><div><h3>Methods</h3><p>From March to July 2023, a quantitative cross-sectional study was carried out to investigate 526 Chinese clinical nurses from five tertiary hospitals in Sichuan Province, China, by using demographic information, the Perceived Social Support Scale, Simplified Coping Skill Questionnaire, and NASA-Task Load Index. Latent profile analyses were performed using Mplus 7.3 software. Pearson’s chi-squared and logistic regression analysis was done using SPSS 24.0 software.</p></div><div><h3>Results</h3><p>Three profiles of mental workload were identified based on the nurses’ responses to the mental workload assessment, designated as “low MWL-high self-rated (<em>n</em> = 70, 13.3%)”, “moderate MWL (<em>n</em> = 273, 51.9%)”, and “high MWL-low self-rated (<em>n</em> = 183, 34.8%)”. Based on the analysis of the three subtypes, nurses with working years < 5 years (<em>χ</em><sup><em>2</em></sup> = 12.135, <em>P</em> < 0.05), no children (<em>χ</em><sup><em>2</em></sup> = 16.182, <em>P</em> < 0.01), monthly income < 6000 (<em>χ</em><sup><em>2</em></sup> = 55.231, <em>P</em> < 0.001), poor health status (<em>χ</em><sup><em>2</em></sup> = 39.658, <em>P</em> < 0.001), no psychological training in the past year (χ<sup>2</sup> = 56.329, <em>P</em> < 0.001) and suffering from workplace violence (<em>χ</em><sup><em>2</em></sup> = 19.803, <em>P</em> < 0.001) were significantly associated with MWL. Moreover, the multivariate logistic regression analysis showed that negative coping styles (<em>OR</em> = 1.146, 95% CI: 1.060–1.238, <em>P</em> = 0.001) were accompanied by higher MWL while negatively associated with perceived social support (<em>OR</em> = 0.927, 95% CI: 0.900–0.955, <em>P</em> < 0.001).</p></div><div><h3>Conclusion</h3><p>Our results showed that the MWL of nurses could be classified into three subtypes. Monthly income, health status, psychological training, workplace violence, negative coping style, and perceived social support were the factors influencing MWL. Managers can employ personalised intervention strategies according to the individual characteristics of different subgroups to reduce nurses’ MWL.</p></div>","PeriodicalId":37848,"journal":{"name":"International Journal of Nursing Sciences","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352013224000528/pdfft?md5=a923008a880d40a6bb1fe851525dc1a9&pid=1-s2.0-S2352013224000528-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Influencing factors associated with mental workload among nurses: A latent profile analysis\",\"authors\":\"\",\"doi\":\"10.1016/j.ijnss.2024.04.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>This study aimed to examine the latent profile of nurses' mental workload (MWL) and explore the influencing factors via a person-centred approach.</p></div><div><h3>Methods</h3><p>From March to July 2023, a quantitative cross-sectional study was carried out to investigate 526 Chinese clinical nurses from five tertiary hospitals in Sichuan Province, China, by using demographic information, the Perceived Social Support Scale, Simplified Coping Skill Questionnaire, and NASA-Task Load Index. Latent profile analyses were performed using Mplus 7.3 software. Pearson’s chi-squared and logistic regression analysis was done using SPSS 24.0 software.</p></div><div><h3>Results</h3><p>Three profiles of mental workload were identified based on the nurses’ responses to the mental workload assessment, designated as “low MWL-high self-rated (<em>n</em> = 70, 13.3%)”, “moderate MWL (<em>n</em> = 273, 51.9%)”, and “high MWL-low self-rated (<em>n</em> = 183, 34.8%)”. Based on the analysis of the three subtypes, nurses with working years < 5 years (<em>χ</em><sup><em>2</em></sup> = 12.135, <em>P</em> < 0.05), no children (<em>χ</em><sup><em>2</em></sup> = 16.182, <em>P</em> < 0.01), monthly income < 6000 (<em>χ</em><sup><em>2</em></sup> = 55.231, <em>P</em> < 0.001), poor health status (<em>χ</em><sup><em>2</em></sup> = 39.658, <em>P</em> < 0.001), no psychological training in the past year (χ<sup>2</sup> = 56.329, <em>P</em> < 0.001) and suffering from workplace violence (<em>χ</em><sup><em>2</em></sup> = 19.803, <em>P</em> < 0.001) were significantly associated with MWL. Moreover, the multivariate logistic regression analysis showed that negative coping styles (<em>OR</em> = 1.146, 95% CI: 1.060–1.238, <em>P</em> = 0.001) were accompanied by higher MWL while negatively associated with perceived social support (<em>OR</em> = 0.927, 95% CI: 0.900–0.955, <em>P</em> < 0.001).</p></div><div><h3>Conclusion</h3><p>Our results showed that the MWL of nurses could be classified into three subtypes. Monthly income, health status, psychological training, workplace violence, negative coping style, and perceived social support were the factors influencing MWL. Managers can employ personalised intervention strategies according to the individual characteristics of different subgroups to reduce nurses’ MWL.</p></div>\",\"PeriodicalId\":37848,\"journal\":{\"name\":\"International Journal of Nursing Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352013224000528/pdfft?md5=a923008a880d40a6bb1fe851525dc1a9&pid=1-s2.0-S2352013224000528-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Nursing Sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352013224000528\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Nursing Sciences","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352013224000528","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Influencing factors associated with mental workload among nurses: A latent profile analysis
Objective
This study aimed to examine the latent profile of nurses' mental workload (MWL) and explore the influencing factors via a person-centred approach.
Methods
From March to July 2023, a quantitative cross-sectional study was carried out to investigate 526 Chinese clinical nurses from five tertiary hospitals in Sichuan Province, China, by using demographic information, the Perceived Social Support Scale, Simplified Coping Skill Questionnaire, and NASA-Task Load Index. Latent profile analyses were performed using Mplus 7.3 software. Pearson’s chi-squared and logistic regression analysis was done using SPSS 24.0 software.
Results
Three profiles of mental workload were identified based on the nurses’ responses to the mental workload assessment, designated as “low MWL-high self-rated (n = 70, 13.3%)”, “moderate MWL (n = 273, 51.9%)”, and “high MWL-low self-rated (n = 183, 34.8%)”. Based on the analysis of the three subtypes, nurses with working years < 5 years (χ2 = 12.135, P < 0.05), no children (χ2 = 16.182, P < 0.01), monthly income < 6000 (χ2 = 55.231, P < 0.001), poor health status (χ2 = 39.658, P < 0.001), no psychological training in the past year (χ2 = 56.329, P < 0.001) and suffering from workplace violence (χ2 = 19.803, P < 0.001) were significantly associated with MWL. Moreover, the multivariate logistic regression analysis showed that negative coping styles (OR = 1.146, 95% CI: 1.060–1.238, P = 0.001) were accompanied by higher MWL while negatively associated with perceived social support (OR = 0.927, 95% CI: 0.900–0.955, P < 0.001).
Conclusion
Our results showed that the MWL of nurses could be classified into three subtypes. Monthly income, health status, psychological training, workplace violence, negative coping style, and perceived social support were the factors influencing MWL. Managers can employ personalised intervention strategies according to the individual characteristics of different subgroups to reduce nurses’ MWL.
期刊介绍：
This journal aims to promote excellence in nursing and health care through the dissemination of the latest, evidence-based, peer-reviewed clinical information and original research, providing an international platform for exchanging knowledge, research findings and nursing practice experience. This journal covers a wide range of nursing topics such as advanced nursing practice, bio-psychosocial issues related to health, cultural perspectives, lifestyle change as a component of health promotion, chronic disease, including end-of-life care, family care giving. IJNSS publishes four issues per year in Jan/Apr/Jul/Oct. IJNSS intended readership includes practicing nurses in all spheres and at all levels who are committed to advancing practice and professional development on the basis of new knowledge and evidence; managers and senior members of the nursing; nurse educators and nursing students etc. IJNSS seeks to enrich insight into clinical need and the implications for nursing intervention and models of service delivery. Contributions are welcomed from other health professions on issues that have a direct impact on nursing practice.
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