Sensible Sleep: Measuring Alarm and Snooze Behavior in Teens Using Wearables and Smartphones

NCT04786678 | Withdrawn FDA Device

• 1 other identifier: 20-10-6256
• Study Type: interventional
• Target: N/A
• Locations: 0 countries
• Sites: N/A

Brief Summary

Pilot data suggests that working professionals and college students routinely use alarms and snooze. Alarm usage and snoozing is associated with several negative health biomarkers including lighter sleep, higher resting heart rate, and reduced sleep duration. It is unclear when this behavior is established, but it is likely in the teenage years when chronic sleep restriction begins to effect a large percentage of Americans. We will ask teens about psychological traits (e.g. personality) and snoozing behavior in a repeated measures design. In addition, we will implement a smartphone based intervention which notifies teens when they are awake past their minimum bedtime for adequate sleep. throughout the study, we will monitor sleep and heart-rate via wearable. From this data, we will establish the prevalence of alarm and snoozing behaviors in teens. We will determine what demographic, psychological, and behavioral traits predict snoozing, and if there are any differences in health biomarkers (e.g. sleep duration, resting heart rate)between snooze and/or alarm users. We will use data from the wearables and smartphones to generate features that can detect snoozing, and will validate them against self-report. Finally, we seek to determine if alarm and snoozing behavior can be reduced via a smartphone intervention aimed at increasing sleep duration.

Conditions

Sleep; Sleep Inertia; Stress

Keywords

Sleep; Sleep Inertia; Caffeine; Sleep Disturbance; Snooze; Alarm

Outcome Measures

Primary Outcomes (4)

• Sleep Duration

  Reduced sleep duration is associated with negative health outcomes. We will compare average baseline and intervention sleep durations (measured by wearables) using 1-way ANCOVA. Covariates will be significant factors from a bivariate logistical regression predicting the proportion of days woken to an alarm or snoozing from total answered survey using demographic, behavioral, psychological, and physiological factors as predictors. If the ANCOVA reveals a significant effect of intervention, a followup ANCOVA will compare average sleep duration for the first two weeks of intervention to the last two weeks of intervention using same covariates to determine if intervention effects change over time. Another follow correlation will compare the number of times the intervention occurred with the average difference of baseline and intervention sleep duration.

  12 weeks, daily sleep measured passively via wearable

• Resting Heart Rate

  Higher resting heart rate (RHR) rate is associated with negative health outcomes. We will compare average baseline and intervention RHR (measured by wearables) using 1-way ANCOVA. Covariates will be significant factors from a bivariate logistical regression predicting the proportion of days woken to an alarm or snoozing from total answered survey using demographic, behavioral, psychological, and physiological factors as predictors. If the ANCOVA reveals a significant effect of intervention, a followup ANCOVA will compare average RHR for the first two weeks of intervention to the last two weeks of intervention using same covariates to determine if intervention effects change over time. Another follow correlation will compare the number of times the intervention occurred with the average difference of baseline and intervention RHR.

  12 weeks, Heart rate measured every minute passively via wearable

• Alarm and Snooze Self Report

  Alarm and Snoozing (AS) behaviors are associated with negative health outcomes. We will compare average baseline and intervention AS proportions using 1-way ANCOVA. Covariates will be significant factors from a bivariate logistical regression predicting the proportion of days woken to an alarm or snoozing from total answered survey using demographic, behavioral, psychological, and physiological factors as predictors. If the ANCOVA reveals a significant effect of intervention, a followup ANCOVA will compare AS proportion for the first two weeks of intervention to the last two weeks of intervention using same covariates to determine if intervention effects change over time. Another follow correlation will compare the number of times the intervention occurred with the average difference of baseline and intervention AS proportion.

  6 weeks via survey. 2 weeks at beginning of study (BASELINE), 2 weeks at beginning of intervention, 2 weeks at end of intervention

• Reaction Time

  Sleep inertia is a cognitive impairment measured using reaction time (RT) following sleep. We will compare average baseline and intervention RTs using 1-way ANCOVA. Covariates will be significant factors from a bivariate logistical regression predicting the proportion of days woken to an alarm or snoozing from total answered survey using demographic, behavioral, psychological, and physiological factors as predictors. If the ANCOVA reveals a significant effect of intervention, a followup ANCOVA will compare RTs for the first two weeks of intervention to the last two weeks of intervention using same covariates to determine if intervention effects change over time. Another follow correlation will compare the number of times the intervention occurred with the average difference of baseline and intervention RTs.

  6 weeks via survey. 2 weeks at beginning of study (BASELINE), 2 weeks at beginning of intervention, 2 weeks at end of intervention

Study Arms (1)

All participants

EXPERIMENTAL

All participants will have a baseline before all participants undergo intervention. The purpose is to pilot the intervention to establish possible effects, as well as to determine if there are any usability or other issues.

Device: Cell phone notification

Interventions

Cell phone notification DEVICE

Habitual bed and wake times will be detected using a wearable for 4 weeks. Using habitual wake time, a minimum bedtime to achieve adequate sleep will be calculated (8 hours). If phone usage is detected after this minimum bedtime, participants will receive a notification informing them they are awake past their minimum bedtime and recommend they go to bed to obtain adequate sleep.

All participants

Eligibility Criteria

• Age: 13 Years - 17 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)

Sponsors & Collaborators

• University of Notre Dame: lead

MeSH Terms

Conditions

Idiopathic Hypersomnia; Parasomnias

Condition Hierarchy (Ancestors)

Disorders of Excessive Somnolence; Sleep Disorders, Intrinsic; Dyssomnias; Sleep Wake Disorders; Nervous System Diseases; Mental Disorders

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: All participants will be passively monitored for 4 weeks, and all will undergo cell phone based intervention which will notify participants if they are using the cell phone past their latest bedtime for adequate sleep (e.g. if a participant habitually wakes at 8am, and are using their phone past midnight, they will receive a notification).

Study Record Dates

• First Submitted: March 3, 2021
• First Posted: March 8, 2021
• Study Start: August 1, 2021
• Primary Completion: August 1, 2022
• Study Completion: August 1, 2023
• Last Updated: June 15, 2025

Record last verified: 2025-06