Depression - Major Depressive Disorder, Mood, Physical Activity, Sleep
Conditions
Brief summary
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.
Detailed description
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 make three types of choices each day: 1) whether to send a message or not on a given day, and, if sending a message, 2) the therapeutic strategy (Behavioral Strategy, Cognitive Strategy, Mindfulness, Motivational Interviewing, Distanced Self-Talk), and 3) whether or not to include feedback (the intern's own data) in the message.
Interventions
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.
Sponsors
University of Michigan
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Medical intern during the 2025-2026 internship year * iPhone or Android phone user * Completed the Intern Health Study consent and baseline survey by June 20 prior to the start of intern year
Exclusion criteria
* None
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Average daily mood | Daily, through study completion at the end of intern year (1 year) | 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. |
| Average daily step count | Daily, through study completion at the end of intern year (1 year) | 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. |
| Average nightly sleep duration | Daily, through study completion at the end of intern year (1 year) | Participant's nightly sleep duration (in minutes) is recorded through a fitness tracker. High sleep duration is considered a positive outcome. |
| Patient Health Questionnaire-9 (PHQ-9) | Quarterly (every 3 months for 1 year) | Prior to the start of the intervention and at quarterly intervals throughout internship year, all participants complete the Patient Health Questionnaire 9. High scores on the PHQ-9 correspond to a larger number of depressive symptoms. |
Countries
United States
Outcome results
None listed