Personalized Circadian mHealth for Shift Work Sleep Disorder

(SAIL Trial)

Recruiting in Palo Alto (17 mi)

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Henry Ford Health System

Must not be taking: Sleep medications

Disqualifiers: Sleep disorders, Neurological disorders, Bipolar, others

No Placebo Group

Trial Summary

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.

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.

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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.

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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.

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Eligibility Criteria

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

Trial Timeline

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

Participant Groups

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.

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.

Find a Clinic Near You

Research Locations Nearby Select from list below to view details:

Henry Ford Columbus Medical Center Novi, MI

Who Is Running the Clinical Trial?

Henry Ford Health System Lead Sponsor

References

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

Mobile app for personalized sleep-wake management for shift workers: A user testing trial. [2023] Label="Objective" NlmCategory="UNASSIGNED">Development of personalized sleep-wake management tools is critical to improving sleep and functional outcomes for shift workers. The objective of the current study was to test the performance, engagement and usability of a mobile app (SleepSync) for personalized sleep-wake management in shift workers that aid behavioural change and provide practical advice by providing personalized sleep scheduling recommendations and education.

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

A real-time, personalized sleep intervention using mathematical modeling and wearable devices. [2023] The prevalence of artificial light exposure has enabled us to be active any time of the day or night, leading to the need for high alertness outside of traditional daytime hours. To address this need, we developed a personalized sleep intervention framework that analyzes real-world sleep-wake patterns obtained from wearable devices to maximize alertness during specific target periods. Our framework utilizes a mathematical model that tracks the dynamic sleep pressure and circadian rhythm based on the user's sleep history. In this way, the model accurately predicts real-time alertness, even for shift workers with complex sleep and work schedules (N = 71, t = 13~21 days). This allowed us to discover a new sleep-wake pattern called the adaptive circadian split sleep, which incorporates a main sleep period and a late nap to enable high alertness during both work and non-work periods of shift workers. We further developed a mobile application that integrates this framework to recommend practical, personalized sleep schedules for individual users to maximize their alertness during a targeted activity time based on their desired sleep onset and available sleep duration. This can reduce the risk of errors for those who require high alertness during nontraditional activity times and improve the health and quality of life for those leading shift work-like lifestyles.

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

Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness. [2021] Shift workers and many other groups experience irregular sleep-wake patterns. This can induce excessive daytime sleepiness that decreases productivity and elevates the risk of accidents. However, the degree of daytime sleepiness is not correlated with standard sleep parameters like total sleep time, suggesting other factors are involved. Here, we analyze real-world sleep-wake patterns of shift workers measured with wearables by developing a computational package that simulates homeostatic sleep pressure - physiological need for sleep - and the circadian rhythm. This reveals that shift workers who align sleep-wake patterns with their circadian rhythm have lower daytime sleepiness, even if they sleep less. The alignment, quantified by the sleep parameter, circadian sleep sufficiency, can be increased by dynamically adjusting daily sleep durations according to varying bedtimes. Our computational package provides flexible and personalized real-time sleep-wake patterns for individuals to reduce their daytime sleepiness and could be used with wearables to develop smart alarms.

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

Differential sleep, sleepiness, and neurophysiology in the insomnia phenotypes of shift work disorder. [2022] To characterize and compare insomnia symptoms within two common phenotypes of Shift Work Disorder.

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] Poor sleep has significant impacts on both mental and physical well-being. This is especially the case for shift workers who rely on good sleep practices to manage the disruption caused by their working conditions. In recent years there has been a proliferation of sleep-focused mobile phone applications, some of which may be suitable for use by shift workers. There is limited evidence however, on whether these applications are sufficient in managing the sleep needs of the early start shift working population (i.e., those whose work schedules begin pre-dawn). This scoping review aims to identify and discuss peer-reviewed literature on mobile sleep applications used by early start shift workers for sleep-self management. Four databases (Scopus, EBSCOhost, CINAHL and PsycInfo) were searched for relevant literature using a pre-determined search string. The initial search using the term early start shift work returned no papers, however a broadened search on shift work in general found 945 papers for title and abstract screening, of which 21 were deemed eligible for full text screening. Two of these papers met the inclusion criteria for this review. The results highlight, firstly, the paucity of research on the use of mobile phone applications for sleep self-management amongst early start shift workers, and secondly, the need for further research on the effectiveness of mobile applications for sleep self-management amongst shift workers in general. A working definition of early start shift work that can be used to stimulate research in this understudied population of shift workers is also proposed.

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

Field-Based Assessments of Behavioral Patterns During Shiftwork in Police Academy Trainees Using Wearable Technology. [2022] Circadian misalignment, as occurs in shiftwork, is associated with numerous negative health outcomes. Here, we sought to improve data labeling accuracy from wearable technology using a novel data pre-processing algorithm in 27 police trainees during shiftwork. Secondarily, we explored changes in four metabolic salivary biomarkers of circadian rhythm during shiftwork. Using a two-group observational study design, participants completed in-class training during dayshift for 6 weeks followed by either dayshift or nightshift field-training for 6 weeks. Using our novel algorithm, we imputed labels of circadian misaligned sleep episodes that occurred during daytime, which were previously were mislabeled as non-sleep by Garmin, supported by algorithm performance analysis. We next assessed changes to resting heart rate and sleep regularity index during dayshift versus nightshift field-training. We also examined changes in field-based assessments of salivary cortisol, uric acid, testosterone, and melatonin during dayshift versus nightshift. Compared to dayshift, nightshift workers experienced larger changes to resting heart rate, sleep regularity index (indicating reduced sleep regularity), and alterations in sleep/wake activity patterns accompanied by blunted salivary cortisol. Salivary uric acid and testosterone did not change. These findings show wearable technology combined with specialized data pre-processing can be used to monitor changes in behavioral patterns during shiftwork.

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] A critical barrier to successful treatment of circadian misalignment in shift workers is determining circadian phase in a clinical or field setting. Light and movement data collected passively from wrist actigraphy can generate predictions of circadian phase via mathematical models; however, these models have largely been tested in non-shift working adults. This study tested the feasibility and accuracy of actigraphy in predicting dim light melatonin onset (DLMO) in fixed night shift workers.