A Pilot of a Personalized Circadian MHealth to Improve Sleep in Night Shift Workers

Not Applicable

Recruiting

• Conditions: Shift Work Sleep Disorder

• Registration Number: NCT06809335
• Lead Sponsor: Henry Ford Health System

Brief Summary

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

Detailed Description

Not available

Study Timeline

• Study Start: 2023-10-23
• Status Verified: 2025-01
• Study First Submitted: 2025-01-23
• Study First Submitted QC: 2025-01-30
• Last Update Submitted: 2025-01-30
• Study First Posted: 2025-02-05
• Last Update Posted: 2025-02-05
• Primary Completion: 2027-06
• Study Completion: 2027-06

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 300

Inclusion Criteria

• Inadequate sleep duration (habitual sleep less than 7 hours during the day)
• Willingness to download the SHIFT app and follow the lighting recommendations
• Ability to follow a set sleep schedule of 7 hours in bed after the night shifts
• Working at least 4 night shifts a month
• Shifts that must begin between 18:00 and 02:00 and last 8 to 12 hours
• Score of 8 or above on the Epworth Sleepiness scale and/or a score of 8 or above on the Insomnia Severity Index

Exclusion Criteria

• Other independent sleep disorders (e.g., obstructive sleep apnea, narcolepsy, etc.)
• History of seizures or other significant neurological disorders
• Bipolar disorder
• Termination of shift schedule
• Pregnancy
• Current use of medications that impact sleep-wake functioning
• Alcohol and substance use disorder

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Establish the effect of SHIFT on stakeholder-centered outcomes.	From enrollment to the 8 month point.	Aim 1a. Measure the effect of SHIFT on work productivity and satisfaction compared to waitlist control using the Job Satisfaction Index. Effect will be tested using a mixed-effects linear regression model with participants as the random effect and Time, Condition, and the Time × Condition interaction term as the fixed effects.; Aim 1b: Measure the effect of SHIFT on global health compared to waitlist control using the NIH PROMIS Global Health questionnaire. Effect will be tested using the same method as Aim 1a.; Aim 1c. Measure the effect of SHIFT on turnover compared to waitlist control, measured at 8-month follow-up. Turnover will be operationalized as an individual who has either terminated the position they were in at baseline or is no longer engaged in shift work as operationalized in the study. Effect will be determined using a generalized mixed-effects regression with turnover as a dichotomous outcome.
Compare use experience and accuracy of SLEEP Android to the original iOS version.	From enrollment to the 8 month point.	Aim 2a. Measure user experience of Android and iOS versions of SHIFT using the User Experience Questionnaire (UEQ). The following ranges of clinical indifference will be used: ± 3 points on the User Experience Questionnaire based on the bin size of 6 for each of the thresholds (bad, neutral, and good user experience).; Aim 2b. Measure accuracy of predicted circadian misalignment (CM), sleep, and depression in Android and iOS versions. CM will be indexed with the outputs of the biomathematical model of the circadian system. Sleep will be measured using the Insomnia Severity Index and sleep diaries. Depression will be measured using the Quick Inventory of Depressive Symptomatology. The following ranges of clinical indifference will be used: 1) predicted CM = ± 3 hours based on approximately 2x the absolute mean error of our model predictions, 2) insomnia severity = ± 6 points, and 3) depression = 28.5% of the QIDS-SR16 score.

Secondary Outcome Measures

Name	Time	Method
Assess facilitators and barriers to engagement and implementation.	Immediately following completion of 8-month treatment period.	A series of semi-structured interviews will be used for thematic analysis, and a comprehensive roadmap for future app updates based on user feedback. The semi-structured interviews will utilize the interview-guide approach following the CFIR framework selected for this study. Six phases will be followed for thematic analysis: (1) data familiarization, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) producing the report. We will combine deductive and inductive techniques to increase the accuracy of thematic analyses.

Trial Locations

Locations (1)

Henry Ford Columbus Medical Center; 🇺🇸 Novi, Michigan, United States