Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study
Abstract This study aims to identify the potential classifications of sleep disturbances within the ICU nurse population, and to compare the between-group differences in demographic data and sleep characteristics. Through convenience sampling, ICU nurses from three tertiary A-level hospitals in Chin...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-01643-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849309779680296960 |
|---|---|
| author | Lili Li Jiali Hua Qiuwen Xu Jing Wu Ying Zhang Fei Li Huiping Yao |
| author_facet | Lili Li Jiali Hua Qiuwen Xu Jing Wu Ying Zhang Fei Li Huiping Yao |
| author_sort | Lili Li |
| collection | DOAJ |
| description | Abstract This study aims to identify the potential classifications of sleep disturbances within the ICU nurse population, and to compare the between-group differences in demographic data and sleep characteristics. Through convenience sampling, ICU nurses from three tertiary A-level hospitals in China were selected as research subjects from March to May 2024. A survey was conducted using a demographic data questionnaire, the PSQI scale, the DASS-21 scale, and the BPS scale, and the data on the sleep quality of ICU nurses was collected via electronic questionnaires. This research also utilized latent class analysis to examine the symptomatic traits of sleep quality in ICU nurses. Additionally, it applied univariate analysis and unordered multinomial logistic regression models to determine the factors influencing the various categories of their sleep quality. A total of 545 questionnaires were distributed, of which 522 were validly returned, yielding an effective response rate of 95.7%. Four potential sleep quality profiles were identified, including “high sleep quality - no sleeping pills,” “medium sleep quality - low sleeping pills,” “medium sleep quality - medium sleeping pills,” and “low sleep quality - high sleeping pills,” with proportions of 43.7%, 40.6%, 10.5%, and 5.2%, respectively. Unordered multinomial logistic regression analysis indicated that the number of night shifts per week, marital status, BPS scores, FSS scores, and DASS-21 scores were key factors affecting the sleep quality classification of ICU nurses(P < 0.05). The sleep quality characteristics of ICU nurses are diverse and can be divided into four different categories. Therefore, nursing managers should be aware of this heterogeneity and take corresponding intervention measures based on the classification of nurses to ensure their sleep quality and promote psychological health. |
| format | Article |
| id | doaj-art-0d7608dcde3241d694f09e5dd3bab693 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0d7608dcde3241d694f09e5dd3bab6932025-08-20T03:53:58ZengNature PortfolioScientific Reports2045-23222025-05-011511810.1038/s41598-025-01643-6Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional studyLili Li0Jiali Hua1Qiuwen Xu2Jing Wu3Ying Zhang4Fei Li5Huiping Yao6Emergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeEmergency and Critical Care Center, Intensive Care Unit, Affiliated People’s Hospital, Zhejiang Provincial People’s Hospital, Hangzhou Medical CollegeAbstract This study aims to identify the potential classifications of sleep disturbances within the ICU nurse population, and to compare the between-group differences in demographic data and sleep characteristics. Through convenience sampling, ICU nurses from three tertiary A-level hospitals in China were selected as research subjects from March to May 2024. A survey was conducted using a demographic data questionnaire, the PSQI scale, the DASS-21 scale, and the BPS scale, and the data on the sleep quality of ICU nurses was collected via electronic questionnaires. This research also utilized latent class analysis to examine the symptomatic traits of sleep quality in ICU nurses. Additionally, it applied univariate analysis and unordered multinomial logistic regression models to determine the factors influencing the various categories of their sleep quality. A total of 545 questionnaires were distributed, of which 522 were validly returned, yielding an effective response rate of 95.7%. Four potential sleep quality profiles were identified, including “high sleep quality - no sleeping pills,” “medium sleep quality - low sleeping pills,” “medium sleep quality - medium sleeping pills,” and “low sleep quality - high sleeping pills,” with proportions of 43.7%, 40.6%, 10.5%, and 5.2%, respectively. Unordered multinomial logistic regression analysis indicated that the number of night shifts per week, marital status, BPS scores, FSS scores, and DASS-21 scores were key factors affecting the sleep quality classification of ICU nurses(P < 0.05). The sleep quality characteristics of ICU nurses are diverse and can be divided into four different categories. Therefore, nursing managers should be aware of this heterogeneity and take corresponding intervention measures based on the classification of nurses to ensure their sleep quality and promote psychological health.https://doi.org/10.1038/s41598-025-01643-6NurseSleep qualityLatent profilesICUPittsburgh sleep quality index |
| spellingShingle | Lili Li Jiali Hua Qiuwen Xu Jing Wu Ying Zhang Fei Li Huiping Yao Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study Scientific Reports Nurse Sleep quality Latent profiles ICU Pittsburgh sleep quality index |
| title | Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study |
| title_full | Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study |
| title_fullStr | Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study |
| title_full_unstemmed | Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study |
| title_short | Latent profile analysis of factors influencing sleep quality in ICU nurses cross-sectional study |
| title_sort | latent profile analysis of factors influencing sleep quality in icu nurses cross sectional study |
| topic | Nurse Sleep quality Latent profiles ICU Pittsburgh sleep quality index |
| url | https://doi.org/10.1038/s41598-025-01643-6 |
| work_keys_str_mv | AT lilili latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT jialihua latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT qiuwenxu latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT jingwu latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT yingzhang latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT feili latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy AT huipingyao latentprofileanalysisoffactorsinfluencingsleepqualityinicunursescrosssectionalstudy |