Intervention
sleep disorders
The smartphone app for the intervention was developed and made available as a Progressive Web Application so that it could be used on an iOS or Android device (Well-being prediction is an essential component of an app. On the basis of earlier studies on machine learning and subjective well-being [The second essential component is personalized sleep advice from physicians. Participants received personalized sleep advice from 2 board-certified psychiatrists specializing in sleep disorders and CBT 3-4 times a week. The advice was suggested after the psychiatrists reviewed the fitness tracker data and surveys, without seeing the well-being prediction results. This ensured that sleep advice was solely based on the physician’s clinical judgment. Physicians chose 3 to 5 messages among 23 fixed-format sleep advice messages (eg, “Avoid alcohol before you go to sleep” and “Try to wake up at a consistent time.”; On the “activity and sleep chart” tab, the participants were readily able to see how much activity and sleep they had in 24 hours for the past 7 days, along with their shift schedule. These data were retrieved every hour from the Fitbit server using its web application programming interface. The intervention has been described in detail in a previous study protocol [The user interface of the app, translated from Japanese to English. Left: Awake times are displayed as red bars, where higher activity levels (higher number of steps/min) are shown in deeper shades of red. Sleep times are displayed as blue bars, where deeper sleep stages are shown in deeper shades of blue. Right: The happiness score is illustrated by a graphic that resembles a weather forecast: cloudy for scores 0 to 50, cloudy and partly sunny for scores 60 to 80, and sunny for scores 90 to 100.