Characterizing Patterns of Nurses' Daily Sleep Health: a Latent Profile Analysis.
Background: Nursing is a demanding occupation characterized by dramatic sleep disruptions. Yet most studies on nurses' sleep treat sleep disturbances as a homogenous construct and do not use daily measures to address recall biases. Using person-centered analyses, we examined heterogeneity in nurses'...
| Publicado en: | International Journal of Behavioral Medicine Vol. 29; no. 5; pp. 648 - 659 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159440558&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159440558 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10705503 7M2 jtl: International Journal of Behavioral Medicine issn: 10705503 maglogo: N pubinfo: dt: Oct2022 vid: 29 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159440558 154505735 159440558 159440558 10.1007/s12529-021-10048-4 159440558 ppf: 648 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Characterizing Patterns of Nurses' Daily Sleep Health: a Latent Profile Analysis. aug: au: Slavish, Danica C. Contractor, Ateka A. Dietch, Jessica R. Messman, Brett Lucke, Heather R. Briggs, Madasen Thornton, James Ruggero, Camilo Kelly, Kimberly Kohut, Marian Taylor, Daniel J. affil: University of North Texas, Denton, USA sug: subj: Nurses Diaries Sleep Quality Health Status Mental Health Human Female Male Adult Inflammation Biological Markers Interleukins C-Reactive Protein Latent Structure Analysis Insomnia Multivariate Analysis Funding Source Adult: 19-44 years Female Male ab: Background: Nursing is a demanding occupation characterized by dramatic sleep disruptions. Yet most studies on nurses' sleep treat sleep disturbances as a homogenous construct and do not use daily measures to address recall biases. Using person-centered analyses, we examined heterogeneity in nurses' daily sleep patterns in relation to psychological and physical health. Methods: Nurses (N = 392; 92% female, mean age = 39.54 years) completed 14 daily sleep diaries to assess sleep duration, efficiency, quality, and nightmare severity, as well as measures of psychological functioning and a blood draw to assess inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP). Using recommended fit indices and a 3-step approach, latent profile analysis was used to identify the best-fitting class solution. Results: The best-fitting solution suggested three classes: (1) "Poor Overall Sleep" (11.2%), (2) "Nightmares Only" (8.4%), (3) "Good Overall Sleep" (80.4%). Compared to nurses in the Good Overall Sleep class, nurses in the Poor Overall Sleep or Nightmares Only classes were more likely to be shift workers and had greater stress, PTSD symptoms, depression, anxiety, and insomnia severity. In multivariate models, every one-unit increase in insomnia severity and IL-6 was associated with a 33% and a 21% increase in the odds of being in the Poor Overall Sleep compared to the Good Overall Sleep class, respectively. Conclusion: Nurses with more severe and diverse sleep disturbances experience worse health and may be in greatest need of sleep-related and other clinical interventions. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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