Personalized Circadian mHealth for Shift Work Sleep Disorder

(SAIL Trial)

Overseen By Marleigh Treger, BS

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Henry Ford Health System

Must not be taking: Sleep medications

Disqualifiers: Sleep disorders, Neurological disorders, Bipolar, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

300 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The goal of this project is to establish the evidence base for equitable accessibility and implementation of the precision sleep medicine mobile application, SHIFT.

Will I have to stop taking my current medications?

Yes, if you are currently using medications that affect sleep-wake functioning, you will need to stop taking them to participate in this trial.

Is the Personalized Circadian mHealth treatment for Shift Work Sleep Disorder safe for humans?

The studies reviewed focus on the usability and effectiveness of mobile apps for managing sleep in shift workers, but they do not provide specific safety data. However, these apps are generally designed to improve sleep patterns and alertness, which suggests they are safe for use in humans. ^{1 2 3 4 5}

How does the treatment SHIFT differ from other treatments for Shift Work Sleep Disorder?

SHIFT is unique because it uses a mobile app to provide personalized sleep schedules based on real-time data from wearable devices, helping shift workers align their sleep patterns with their natural circadian rhythm to improve alertness and reduce daytime sleepiness. ^{1 2 4 6 7}

What data supports the effectiveness of the treatment SHIFT for Shift Work Sleep Disorder?

Research shows that personalized sleep-wake management tools, like mobile apps, can improve sleep and alertness for shift workers by providing tailored sleep schedules. These tools help align sleep patterns with the body's natural rhythms, reducing daytime sleepiness and improving overall well-being. ^{1 2 4 5 6}

Are You a Good Fit for This Trial?

This trial is for night shift workers who often get less than 7 hours of sleep during the day, can stick to a set sleep schedule after work, and work shifts starting between 6 PM and 2 AM. Participants must be willing to use the SHIFT app and follow its light exposure advice, work at least four night shifts per month, and have certain scores indicating sleepiness or insomnia. It's not for those with bipolar disorder, changing shift schedules, pregnancy, substance issues, on sleep-impacting meds or with other serious sleep disorders.

Inclusion Criteria

Inadequate sleep duration (habitual sleep less than 7 hours during the day)

Ability to follow a set sleep schedule of 7 hours in bed after the night shifts

Shifts that must begin between 18:00 and 02:00 and last 8 to 12 hours

Exclusion Criteria

Bipolar disorder

Termination of shift schedule

Pregnancy

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Initial Treatment

Participants in the SHIFT App condition receive an access code to download the app and conduct an orientation. They then enter four weeks of study-directed use of SHIFT.

4 weeks

Orientation session (in-person or virtual)

Self-directed Use

Participants continue with self-directed use of the SHIFT app after the initial treatment phase.

4 months

Booster Session

Participants complete a booster session with two additional weeks of study-directed use, followed by continued self-directed use.

2 weeks

Follow-up

Participants are monitored for outcomes such as work productivity, satisfaction, and turnover at the 8-month follow-up.

8 months

What Are the Treatments Tested in This Trial?

Interventions

• SHIFT

Trial Overview The study tests a mobile health app called SHIFT designed to improve the quality of sleep in people working night shifts. The app provides personalized lighting recommendations based on circadian rhythms to help users achieve better rest.

How Is the Trial Designed?

Group I: SHIFT App Experimental Treatment 1 Intervention

Participants in this condition will receive an access code to download the mobile application and conduct an orientation to SHIFT and the study procedures with a study team member. They will then enter four weeks of study directed use of SHIFT where they are trained on a daily procedure of opening SHIFT at the beginning of their day and planning their day in accordance with the app recommendations. App usage (4 times per week) will be incentivized with weekly bonuses added to study compensation. Following the four weeks of study-directed use, participants will continue with self-directed use. At four months, participants will then complete a booster session with two additional weeks of study-directed use, followed by self-directed use until the end of the study. The structure with the booster session has evidence for maintaining treatment gains and is also in alignment with the commercialization plan.

Group II: Waitlist Control Active Control 1 Intervention

Participants in this condition will only complete questionnaires for the initial eight months. Those who remain shift workers will have the option of receiving the SHIFT app and the option to complete follow-up surveys in the same manner as the SHIFT App condition.

Who Is Running the Clinical Trial?

Henry Ford Health System

Lead Sponsor

Trials

334

Recruited

2,197,000+

Published Research Related to This Trial

The SleepSync mobile app significantly improved various sleep-related outcomes for shift workers, including total sleep time, ability to fall asleep, and sleep quality, based on a trial with 27 participants over two weeks.

Users reported positive engagement and usability with the app, indicating it effectively integrated into their routines and influenced their sleep behaviors, suggesting its potential as a valuable tool for managing sleep in shift workers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile app for personalized sleep-wake management for shift workers: A user testing trial. Murray, JM., Magee, M., Giliberto, ES., et al.[2023]

A novel data pre-processing algorithm improved the accuracy of sleep labeling from wearable technology in 27 police trainees during shiftwork, allowing for better monitoring of circadian misalignment.

Nightshift workers showed significant changes in resting heart rate and sleep regularity, along with altered salivary cortisol levels, indicating that shiftwork negatively impacts metabolic health and sleep patterns.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Field-Based Assessments of Behavioral Patterns During Shiftwork in Police Academy Trainees Using Wearable Technology. Erickson, ML., Wang, W., Counts, J., et al.[2022]

There is a significant lack of research on the effectiveness of mobile sleep applications specifically for early start shift workers, with only two relevant studies identified in a review of 945 papers.

The review emphasizes the need for more studies to explore how these mobile applications can help shift workers manage their sleep, highlighting an important gap in the current literature.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile phone sleep self-management applications for early start shift workers: A scoping review of the literature. Bullock, B., Learmonth, C., Davis, H., et al.[2023]

A personalized sleep intervention framework was developed using data from wearable devices to optimize alertness for shift workers, based on their unique sleep-wake patterns over a study involving 71 participants over 13 to 21 days.

The framework identified a new sleep-wake pattern called adaptive circadian split sleep, which combines a main sleep period with a late nap, helping shift workers maintain high alertness during both work and non-work hours, potentially improving their health and reducing errors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A real-time, personalized sleep intervention using mathematical modeling and wearable devices. Song, YM., Choi, SJ., Park, SH., et al.[2023]

The study identified two distinct insomnia phenotypes among 34 permanent night workers: 'alert insomniacs' (AI), who exhibit normal sleepiness but heightened brain activity, and 'sleepy insomniacs' (SI), who show excessive sleepiness with normal brain activity, indicating different underlying mechanisms of insomnia related to shift work.

Circadian misalignment was found to be a key factor for the sleepy insomnia phenotype, while the alert insomnia phenotype appears to be more similar to a traditional insomnia disorder, suggesting tailored interventions may be needed for each group.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Differential sleep, sleepiness, and neurophysiology in the insomnia phenotypes of shift work disorder. Gumenyuk, V., Belcher, R., Drake, CL., et al.[2022]

This study demonstrated that wrist actigraphy can accurately predict dim light melatonin onset (DLMO) in fixed night shift workers, showing a strong agreement with laboratory measurements (Lin's concordance coefficient of 0.70).

The predictions from actigraphy had a mean error of only 2.88 hours, with a high percentage (76% and 91%) falling within 2 and 4 hours of the actual DLMO, making it a promising tool for assessing circadian phase in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Predicting circadian misalignment with wearable technology: validation of wrist-worn actigraphy and photometry in night shift workers. Cheng, P., Walch, O., Huang, Y., et al.[2021]

Shift workers who align their sleep-wake patterns with their circadian rhythm experience less daytime sleepiness, even if their total sleep time is shorter, indicating the importance of circadian alignment over just sleep duration.

A new computational package can help individuals optimize their sleep-wake patterns in real-time, potentially reducing daytime sleepiness by adjusting sleep durations based on varying bedtimes, which could be integrated with wearable technology.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness. Hong, J., Choi, SJ., Park, SH., et al.[2021]

Citations

1. United States pubmed.ncbi.nlm.nih.gov

Mobile app for personalized sleep-wake management for shift workers: A user testing trial. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

A real-time, personalized sleep intervention using mathematical modeling and wearable devices. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness. [2021]

4. United States pubmed.ncbi.nlm.nih.gov

Differential sleep, sleepiness, and neurophysiology in the insomnia phenotypes of shift work disorder. [2022]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Mobile phone sleep self-management applications for early start shift workers: A scoping review of the literature. [2023]

6. United States pubmed.ncbi.nlm.nih.gov

Field-Based Assessments of Behavioral Patterns During Shiftwork in Police Academy Trainees Using Wearable Technology. [2022]

7. United States pubmed.ncbi.nlm.nih.gov

Predicting circadian misalignment with wearable technology: validation of wrist-worn actigraphy and photometry in night shift workers. [2021]