Characterizing Patterns of Nurses’ Daily Sleep Health: a Latent Profile Analysis

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

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
JournalInternational Journal of Behavioral Medicine
DOIs
StatePublished - Oct 2022

Keywords

  • Latent profile analysis
  • Longitudinal
  • Nightmares
  • Nurses
  • Sleep diary

ASJC Scopus subject areas

  • Applied Psychology

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