Characterizing Patterns of Nurses’ Daily Sleep Health: a Latent Profile Analysis
- 05.01.2022
- Full length manuscript
- Verfasst von
- Danica C. Slavish
- Ateka A. Contractor
- Jessica R. Dietch
- Brett Messman
- Heather R. Lucke
- Madasen Briggs
- James Thornton
- Camilo Ruggero
- Kimberly Kelly
- Marian Kohut
- Daniel J. Taylor
- Erschienen in
- International Journal of Behavioral Medicine | Ausgabe 5/2022
Abstract
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.
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- Titel
- Characterizing Patterns of Nurses’ Daily Sleep Health: a Latent Profile Analysis
- Verfasst von
-
Danica C. Slavish
Ateka A. Contractor
Jessica R. Dietch
Brett Messman
Heather R. Lucke
Madasen Briggs
James Thornton
Camilo Ruggero
Kimberly Kelly
Marian Kohut
Daniel J. Taylor
- Publikationsdatum
- 05.01.2022
- Verlag
- Springer US
- Erschienen in
-
International Journal of Behavioral Medicine / Ausgabe 5/2022
Print ISSN: 1070-5503
Elektronische ISSN: 1532-7558 - DOI
- https://doi.org/10.1007/s12529-021-10048-4
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