Efficacy of a Novel Sleep Intervention in Short Sleepers

NCT ID: NCT04697680

Last Updated: 2025-07-31

Basic Information

• Recruitment Status: WITHDRAWN
• Clinical Phase: NA
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-01-15
• Study Completion Date: 2021-12-31

Brief Summary

Approximately 1/3 of Americans sleep ≤6h per night, an amount that has been deemed sub-optimal by the American Academy of Sleep Medicine and Sleep Research Society, the National Sleep Foundation, American Thoracic Society, and the American Heart Association. These consensus statements echo findings from many reviews on this topic. This is alarming, given epidemiologic and experimental research showing that reduced sleep time is associated with a variety of negative health outcomes including obesity, diabetes, cardiovascular disease, and mortality. Different people may need different amounts of sleep. And some people may not be able to make large changes to their sleep schedule all at once. Many individuals have situational constraints that change over time. As such, short sleep represents an unmet public health problem. There are, however, no empirically supported interventions for insufficient sleep. The proposed study addresses this critical gap by evaluating the efficacy of a novel intervention that is theoretically grounded, feasible, and has positive impacts on sleep duration. The intervention in the proposed study is by design self-correcting, individually-tailored, and not dependent on unknown individual sleep needs. It can adapt to any schedule and situation and can adapt to changes in a person's sleep schedule. The main goal of this study is to evaluate whether a manually determined sleep extension intervention is effective at improving sleep and related outcomes among adults who find it difficult to get enough sleep.

Detailed Description

Approximately 35 % of Americans sleep ≤6h per night, an amount that has been deemed sub-optimal by the American Academy of Sleep Medicine and Sleep Research Society, the National Sleep Foundation, American Thoracic Society, and the American Heart Association. These consensus statements echo findings from many reviews on this topic. This is alarming, given epidemiologic and experimental research showing that reduced sleep time is associated with a variety of negative health outcomes including obesity, diabetes, cardiovascular disease, and mortality. As such, short sleep represents an unmet public health problem. There are, however, no empirically supported interventions for insufficient sleep. The proposed study addresses this critical gap by evaluating the efficacy of a novel intervention that is theoretically grounded, feasible, and has positive impacts on sleep duration.

Previous studies have associated habitual short sleep duration with important adverse cardiometabolic outcomes, including weight gain, obesity, diabetes, cardiovascular disease, stress, etc. They suggest that those that report short sleep may be more likely to experience functional impairments and are less likely to engage in behaviors consistent with a healthy lifestyle. A proposed mechanism of these relationships is that insufficient sleep duration triggers metabolic disturbances and increased immune response resulting in appetite dysregulation, adverse cardiovascular outcomes, and resultant disease states. In addition to cardiometabolic effects, behavioral and functional consequences of short sleep have been well-documented. For example, short sleepers are more likely to exhibit difficulties initiating and/or maintaining sleep daytime sleepiness drowsy driving, and other impairments as a result of sleep loss. Laboratory studies have extensively documented neurocognitive and behavioral effects of sleep loss, including increased objective sleepiness, impaired vigilance using computer-based psychomotor assessments, and deficits in working memory, decision-making, and executive function, as assessed using standardized neuropsychologic and neuroimaging techniques.

Most, if not all, sleep disorders have targeted interventions. Interventions have not been developed or evaluated for insufficient sleep. An effective and disseminable intervention for insufficient sleep will likely differ from those of sleep disorders- rather than an in-clinic, visit-based, medication/device/procedure-focused, non-tailored approach, a successful approach for insufficient sleep will likely be out-of-clinic, population/community-based, lifestyle-focused, and individually-tailored. The problem of insufficient sleep is less like other sleep disorders and more like other health behaviors, such as smoking, poor diet, and lack of physical activity, in that the reasons for insufficient sleep involve beliefs and attitudes, home and work demands, and environmental constraints.

With this in mind, a behavioral intervention was developed based on concepts originally implemented in Cognitive Behavioral Therapy for Insomnia (CBTI), the most well-supported treatment approach for insomnia. Although CBTI does not routinely increase sleep duration, it has sleep efficiency as its primary endpoint and employs concepts that can potentially be used to increase sleep time while maintaining high levels of sleep efficiency. The intervention originally developed included algorithms that recognize the natural "ebb and flow" of sleep ability within an individual seek to use an individual's own sleep data to predict (1) when is an optimal time to make a change to sleep, and (2) what sort of incremental change should be made with the eventual goal of increasing sleep efficiency and duration.

Different people may need different amounts of sleep. And some people may not be able to make large changes to their sleep schedule all at once. Many individuals have situational constraints that change over time. The intervention in the proposed study is by design self-correcting, individually-tailored, and not dependent on unknown individual sleep needs. It can adapt to any schedule and situation and can adapt to changes in a person's sleep schedule.

This sleep extension intervention specifically uses a novel approach, where individualized feedback will be provided to each participant, based on information provided by the wearable devices and the sleep diary. The goal is recognizing the optimal time to make a change to sleep patterns and deciding what kind of change should be made.

Conditions

Sleep

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: BASIC_SCIENCE
• Blinding Strategy: SINGLE

Study Groups

Group 1

Subjects randomized into Group 1 will be provided with a sleep schedule each week based on an algorithm (Algorithm 1) calculated from sleep diaries and fitbit data. Subjects will complete questionnaires at an initial clinic visit. Subjects will then complete a sleep diary upon waking each day and wear a Fitbit Charge 2 device for sleep monitoring each day for 8 weeks. At the end of the study, subjects will complete follow-up questionnaires at a final clinic visit.

Group Type: ACTIVE_COMPARATOR

Algorithm 1

Intervention Type: BEHAVIORAL

A sleep extension algorithm (algorithm 1) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Group 2

Subjects randomized into Group 2 will be provided with a sleep schedule each week based on an algorithm (Algorithm 2) calculated from sleep diaries and fitbit data. Subjects will complete questionnaires at an initial clinic visit. Subjects will then complete a sleep diary upon waking each day and wear a Fitbit Charge 2 device for sleep monitoring each day for 8 weeks. At the end of the study, subjects will complete follow-up questionnaires at a final clinic visit.

Group Type: ACTIVE_COMPARATOR

Algorithm 2

Intervention Type: BEHAVIORAL

A sleep extension algorithm (algorithm 2) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Group 3

Subjects randomized into Group 1 will be provided with a sleep schedule each week based on an algorithm (Algorithm 3) calculated from sleep diaries and fitbit data. Subjects will complete questionnaires at an initial clinic visit. Subjects will then complete a sleep diary upon waking each day and wear a Fitbit Charge 2 device for sleep monitoring each day for 8 weeks. At the end of the study, subjects will complete follow-up questionnaires at a final clinic visit.

Group Type: ACTIVE_COMPARATOR

Algorithm 3

Intervention Type: BEHAVIORAL

A sleep extension algorithm (algorithm 3) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Interventions

Algorithm 1

A sleep extension algorithm (algorithm 1) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Intervention Type: BEHAVIORAL

Algorithm 2

A sleep extension algorithm (algorithm 2) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Intervention Type: BEHAVIORAL

Algorithm 3

A sleep extension algorithm (algorithm 3) will be calculated and implemented based on information obtained from Sleep Diary and Fitbit data.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

1. Be between the ages of 18-60 years old

2. Have a typical sleep schedule of <6 hours per night

Exclusion Criteria

1. Any condition that the PI considers would significantly impede participation in the study.

2. Participant is under 18 years of age or older than 60 years of age

3. Do not have a typical sleep schedule of <6 hours per night

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 60 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Arizona

OTHER

Sponsor Role: lead

Responsible Party

MICHAEL A GRANDNER

Director of Sleep and Health Research Program, Associate Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

University of Arizona

Tucson, Arizona, United States

Countries

United States

Other Identifiers

1812207442

Identifier Type: -

Identifier Source: org_study_id