The aim of this study is to evaluate the efficacy of using a reinforcement learning algorithm to determine the optimal content of a mobile health intervention (message delivered via smartphone) for improving the mood, physical activity, and sleep of medical interns.
Due to their high workloads, less sleep and physical activity and other stressors, medical interns suffer from depression at higher rates than the general population. The goal of this study is to evaluate the efficacy of a mobile health intervention intending to help prevent the degradation of health behaviors and the development of depression. The intervention sends mobile phone notifications which aim to help interns improve their mood, maintain physical activity, and obtain adequate sleep during their internship year. A reinforcement learning algorithm will use prior survey, daily mood, and wearable data to decide each day whether to send a message or not.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
PREVENTION
Masking
NONE
Enrollment
1,000
The study's mobile app will be used to deliver push notifications. The notifications appear on the participant's phone lock screen. The notifications include 3 categories: mood notifications, activity notifications, sleep notifications. Mood notifications aim to increase the participant's mood. Activity notifications aim to increase the participant's physical activity. Sleep notifications aim to increase the participant's sleep duration. All notifications are categorized as one of five therapeutic approaches: 1) CBT-Behavioral, 2) CBT-Cognitive, 3) Distanced Self-Talk, 4) Mindfulness, 5) Motivational Interviewing.
University of Michigan
Ann Arbor, Michigan, United States
Average daily mood
Through the mobile app, participants enter a mood score (scale 1 - 10) every day of the study. 1 corresponds to lowest mood and 10 corresponds to highest mood.
Time frame: Daily, through study completion at the end of intern year (1 year)
Average daily step count
Participant's daily step counts are recorded through a fitness tracker. High step counts are considered a positive outcome as it indicates more physical activity.
Time frame: Daily, through study completion at the end of intern year (1 year)
Average nightly sleep duration
Participant's nightly sleep duration (in minutes) is recorded through a fitness tracker. High sleep duration is considered a positive outcome.
Time frame: Daily, through study completion at the end of intern year (1 year)
Patient Health Questionnaire-9 (PHQ-9)
Prior to the start of the intervention and at quarterly intervals throughout internship year, all participants complete the Patient Health Questionnaire 9 (0-27). Higher scores on the PHQ-9 correspond to a larger number of depressive symptoms (worse outcome).
Time frame: Quarterly (every 3 months for 1 year)
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