280 Tracking Physical Activity and Sleep Patterns in Emergency Medicine Residents Using Wearable Activity Monitors
Gunaga S, Park J, Obrycki B, Hashim J, Spencer R, and Jarski R. 280 Tracking Physical Activity and Sleep Patterns in Emergency Medicine Residents Using Wearable Activity Monitors. Ann Emerg Med 2019; 74(4):S110-S111.
Ann Emerg Med
Study Objectives: There has been much attention and effort placed by the emergency medicine (EM) community on attempting to reduce resident and attending physician burnout and depression. Though the literature on EM wellness continues to grow, little is documented about the physical impact of the EM work schedule and lifestyle on a physician’s health and wellness. This prototype study was designed to better quantify some vital health indicators, and to define baseline physical activity and sleep patterns of EM residents. A secondary objective was to evaluate the feasibility, methodology and challenges associated with studies utilizing wearable activity monitoring technology. Methods: We conducted a single center, prospective, observational study of 25 EM residents. Subjects were 1st through 4th year EM residents who were asked to wear a Fitbit FlexTM activity monitor day and night for 14 days during an EM rotation. These residents work 9-10 hour shifts in a 400-bed community hospital that sees approximately 60,000 emergency department (ED) visits per year. Multiple baseline variables were measured including resident age, sex, post graduate level, body mass index (BMI), and marital and parental status. Activity and sleep variables included number of steps/day, steps/ED shift, and number of hours of sleep/day. Step and sleep data were excluded on days when Fitbit monitors were not worn, and a subject was excluded if the Fitbit was worn for less than 30% of the collection period. Categorical data were compared using the chi-square test for association. Between-group mean differences were compared by calculating t-tests for independent measures and analysis of variance. A p-value ≤0.05 (two-tail) was considered statistically significant. Results: A total of 5,568 hours of Fitbit biometric data were collected and analyzed from our sample. Of the 25 subjects who enrolled in the study, 5 were excluded for not meeting the study inclusion criteria. Mean age of residents was 30 years old with a standard deviation (SD) of 2.5 years. 60% of the sample was male, 40% female, 35% married and 10% were parents. Average BMI for the entire group was 25.5 kg/m2 with a SD of 5.7 kg/m2. The mean total daily steps, the mean total steps taken per shift and mean total sleep per day are presented in Figure 1. Steps/day, steps/shift, sleep/day, and BMI were compared across all post graduate year levels and sex with no significant differences noted between these groups. Conclusion: This is only the third study to date to use wearable activity monitoring devices to measure the activity of emergency physicians and the first to create a biometric profile for the EM resident. We live in a time where this technology is accurate, minimally invasive, affordable and worn by many emergency physicians. There is an opportunity for future studies to replicate this design across subspecialties and in multiple centers in different geographical settings. Building biometric profiles that can be applied to any physician demographic group can provide great insight towards improving the health and wellness practices of busy and often overextended providers. [Figure presented]