Changes in the Work Schedule of Nurses Related to the COVID-19 Pandemic and Its Relationship with Sleep and Turnover Intention

Ingebjørg Louise Rockwell Djupedal, Ståle Pallesen, Anette Harris, Siri Waage, Bjørn Bjorvatn and Øystein Vedaa
Additional contact information
Ingebjørg Louise Rockwell Djupedal: Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway
Ståle Pallesen: Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway
Anette Harris: Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway
Siri Waage: Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway
Bjørn Bjorvatn: Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, 5021 Bergen, Norway
Øystein Vedaa: Department of Psychosocial Science, University of Bergen, 5015 Bergen, Norway

IJERPH, 2022, vol. 19, issue 14, 1-12

Abstract: Background: This study aimed to investigate whether different types of changes in the work schedule of nurses working rotating shifts during the COVID-19 pandemic were associated with sleep duration, sleep quality, and turnover intention. Methods: Cross-sectional questionnaire data from 694 nurses participating in the SUrvey of Shift work, Sleep and Health (SUSSH) were collected between the first and the second wave of the COVID-19 pandemic in Norway. A total of 89.9% were female, and mean age was 44.6 years (SD = 8.6 years). Changes in the shift work schedule related to the pandemic comprised reports of more long workdays (>8 h), less days off between work periods, more night shifts, more quick returns (i.e., 11 h or less between two consecutive shifts), more day shifts, and more evening shifts compared to no change in the respective shift characteristics. Change in sleep duration, sleep quality, and turnover intention as well as demographics were also assessed. Logistic regression analyses were performed to investigate whether changes in the specific work schedules were associated with sleep duration, sleep quality, and turnover intention, controlling for sex, age, cohabitation, children living in household, percentage of full time equivalent and other changes in the work schedule. Results: A total of 17% reported experiencing one or more changes in their work schedule during the pandemic. Experiencing any change in the work schedule predicted worse sleep quality (OR = 2.68, p < 0.001), reduced sleep duration (OR = 4.56, p < 0.001), and higher turnover intention (OR = 1.96, p = 0.006) compared to experiencing no change in work schedule. Among the specific changes in work schedules, experiencing an increase in quick returns had the highest odds ratio for worse sleep quality (OR = 10.34, p = 0.007) and higher turnover intention (OR = 8.49, p = 0.014) compared to those who reported no change in quick returns. Nurses experiencing an increase in long workdays were more likely to report higher turnover intention (OR = 4.37, p = 0.003) compared to those experiencing no change in long workdays. Conclusions: Change in work schedule related to the pandemic was associated with worse sleep quality, reduced sleep duration, and higher turnover intention. Increase in quick returns emerged as especially problematic in terms of sleep quality and turnover intention, along with long workdays, which were associated with higher turnover intention.

Keywords: shift work; quick return; sleep; turnover intention; nurse (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/14/8682/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/14/8682/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2022:i:14:p:8682-:d:864552

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().