P095: Wellness, sleep and exercise in emergency medicine residents: an observational study

Abstract

Introduction: Burnout is well documented in residents and emergency physicians. Wellness initiatives are becoming increasingly prevalent, but there is a lack of data supporting their efficacy. In some populations, a relationship between sleep, exercise and wellness has been documented, but this relationship has not been established in emergency medicine (EM) residents or physicians. We aim to determine whether exercise and sleep quality and quantity as measured by a Fitbit are associated with greater perceived wellness in EM residents. Methods: Fifteen EM residents from two training sites wore a Fitbit during a 4-week EM rotation. The Fitbit recorded data on sleep quantity (minutes sleeping)/quality (sleep disruptions) and exercise quantity (daily step count)/quality (daily active minutes performing activity of 3-6 and >6 metabolic equivalents). Participants completed an end-of-rotation Perceived Wellness Survey (PWS) which provided information on six domains of personal wellness (psychological, emotional, social, physical, spiritual and intellectual). Associations between PWS scores and the Fitbit markers were evaluated using a Mann-Whitney-U statistical analysis. Results: Preliminary results indicate that residents who scored ≥50 th percentile for sleep quantity had significantly higher PWS scores than those who scored ≤50 th percentile (median PWS 17.0 vs 13.0 respectively, p=0.04). There was no significant correlation between PWS scores, sleep interruptions, daily step count and average daily active minutes. Postgraduate Year PGY1 and PGY2-5 report median PWS scores of 13.9 and 17.2 respectively. Conclusion: To our knowledge, this is the first study to objectively measure the quality and quantity of sleep as well as exercise habits of EM residents using a Fitbit device. Our data indicates a significant relationship between better sleep quantity and higher wellness scores in this population. We aim to enroll 30 residents in order to obtain a more robust data set. A larger sample size will increase statistical power and allow us to more extensively evaluate the use of exercise and sleep monitoring devices in the efficacy assessment of wellness initiatives.