Change in Sleep Quality of Residents the Night Before High-Fidelity Simulation: Results From a Prospective 1-Year National Survey
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Original Article
P: 295-302
August 2022

Change in Sleep Quality of Residents the Night Before High-Fidelity Simulation: Results From a Prospective 1-Year National Survey

Turk J Anaesthesiol Reanim 2022;50(4):295-302
1. Department of Anaesthesiology and Reanimation, Hospices Civils de Lyon, Lyon, France
2. Lyonnais Center for Education by Simulation in Health, Claude Bernard Lyon 1 University, SAMSEI, Lyon, France
3. Department of Health Data, Hospices Civils de Lyon, Lyon, France
4. Research on Healthcare Performance (RESHAPE), Claude Bernard Lyon 1 University, Lyon, France
5. Department of Anaesthesia and Surgical Resuscitation, Hôtel Dieu, Nantes University Hospital, Nantes, France
6. Department of Anaesthesiology and Surgical Resuscitation, CHU Bicêtre LabForSIMS Faculty of Medicine, Paris-Sud, Le Kremlin Bicêtre, France
7. CEnSIM Savoie Emergency Care - Savoie Simulation Education Center, Savoie Metropole Hospital Center, France
8. Medsim Simulation Center, University of Franche Comté, France
9. Department of Anaesthesia, Reanimation and Pain Emergency, SIMHU-Nîmes Medical Simulation Center, Carémeau Hospital Group, Nîmes University Hospital, France
10. Normandy Health Simulation Center (NorSimS), Caen University Hospital, France
11. Emergency Care Teaching Center, CESU, University Hospital Center of Rouen, France
12. UNISIMES European Health Simulation Unit, Strasbourg University Faculty of Medicine, France
13. University of Claude Bernard Lyon 1-Bio mericux-Hospices Civils de Lyon, Lyon, France
No information available.
No information available
Received Date: 06.08.2021
Accepted Date: 05.01.2022
Publish Date: 15.08.2022
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ABSTRACT

Objective:

The stress level of participants in high-fidelity simulation stems from various factors but may result in anticipatory anxiety causing sleep disturbances during the night prior to simulation. The objective of this survey was to determine the change in sleep quality of residents during the night prior to the simulation.

Methods:

The survey was proposed for 1 year to all residents at the beginning of the simulation, in 10 simulation centres. The questionnaire combined demographics and the Leeds Sleep Evaluation Questionnaire using visual analogue scales divided into 4 sleep qualitative domains. The primary outcome was the prevalence of sleep disturbance (>10 mm on 1 domain). Secondary outcomes were the prevalence of severe sleep disturbance (>25 mm), as well as qualitatively and quantitatively reported explanatory sleep parameters.

Results:

Among respondents, 66% [95% CI: 63 to 69] of residents had more than 10 mm and 27% [95% CI: 24 to 30] had more than 25 mm of sleep disturbance. Residents with a sleep disturbance of more than 10 mm had fewer hours of sleep (6.4 [standard deviation=1.8] vs 7.3 [standard deviation=1.3], difference: −0.9 [95% CI: −1.1 to −0.7]; P < .0001), with a higher number of night-time awakenings (1.3 [standard deviation=1.5] vs 0.7 [standard deviation=0.9], difference: 0.6 [95% CI: 0.4 to 0.8]; P < .0001).

Conclusion:

Among residents participating in the simulation, a high prevalence of change in sleep quality during the night before the simulation was noted. Strategies to help residents achieve better sleep prior to simulation should be explored.

Keywords: Education, high-fidelity simulation, Leeds Sleep Evaluation Questionnaire, sleep disturbance

References

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