Health Behavior Clinical Trial
Official title:
The Effects of a Personalized Sleep Improvement Smartphone Application From SleepScore Labs: A Single-blinded Randomized Waitlist Controlled Trial
The study is a single-blinded randomized waitlist controlled trial that aims to assess changes in objective and self-report sleep improvement through use of a dynamic and personalized sleep improvement smartphone app and advice engine in those with poor sleep (i.e., subclinical threshold insomnia) when compared to a waitlist control group after 6 weeks and 12 weeks.
| Status | Recruiting |
| Enrollment | 600 |
| Est. completion date | August 2023 |
| Est. primary completion date | June 2023 |
| Accepts healthy volunteers | Accepts Healthy Volunteers |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility | Inclusion Criteria: - iOS user - Sub-clinical threshold insomnia symptoms (Regensburg Insomnia Scale Score 13-24) - = 18 years old. - Naive to the SleepScore Labs App - Able to fully understand information on data protection and provide written informed consent Exclusion Criteria: - Non-iOS device users due to technical restrictions of the application - Bedtime less than 6 hours - Any of the following medical problems: - Untreated psychological disorder affecting sleep (e.g., depression, anxiety disorders, bipolar disorder, schizophrenia) - Current severe medical conditions (e.g. chronic pain, cancer) - Any of the following medications/substance use: - Prescription sleep medications or regular use of over-the-counter sleep medications - Medication for other conditions (e.g., anxiety, ADHD) that affect sleep, e.g. antidepressants, antipsychotics - Consumption of 3+ units of alcohol on 4 or more nights per week - Recreational or nightly drug use - Pregnant or nursing mothers - Shift work - Travel across 2 or more time zones during study period - Sleeping more than 7 nights not at home during study period - Users who newly received a diagnosis of a sleep disorders - Users who start sleep or other psychoactive medication during the study period - Use of other Sleep Tracking App's during the study period |
| Country | Name | City | State |
|---|---|---|---|
| Germany | Ruhrlandklinik Essen | Essen | Northrhine-Westphalia |
| Lead Sponsor | Collaborator |
|---|---|
| ResMed | SleepScore Labs International LTD |
Germany,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Changes in subjective sleep quality between active sleep-change condition through the Dein Schlaf. Dein Tag. App and the waitlist condition comparing baseline with 6 weeks and 12 weeks measures. | Self-reported outcome sleep quality measures are those collected using the Sleep Quality score (SQ) of the SF-B (9 Items). The SQ can vary from 1 (very low) to 5 (very good).
The investigators will analyze between-group differences at each time-point using established statistical tests (t-test for normally distributed data, Mann Whitney-U test for non-normally distributed data). |
12 weeks | |
| Secondary | Changes in overall sleep problems. | Overall self-reported sleep problems are collected using the Pittsburgh Sleep Quality Index (PSQI), which yields a global score that can range from 0 to 21. A global score of 5 or more indicates poor sleep quality, whereby the higher the score, the worse the quality.
The investigators will analyze between-group differences at each time-point using a t-test if normally distributed, or the Mann Whitney-U test for non-normally distributed continuous data. |
12-weeks | |
| Secondary | Changes in feeling of being refreshed in the morning. | Self-reported feeling of being refreshed in the morning is collected using the Schlaffragebogen B (SF-B). The score for feeling of being refreshed in the morning (GES) can vary from 1 (very low) to 5 (very good).
The investigators will analyze between-group differences at each time-point using a t-test if normally distributed, or the Mann Whitney-U test for non-normally distributed continuous data. |
12-weeks | |
| Secondary | Changes in health measures. | Self-reported health measures are collected using the Short Form 12 Health Survey Questionnaire (SF-12), which yields a global score of 0-100. A global score of 0 indicates maximum disability and a score of 100 is equivalent to no disability.
The investigators will analyze between-group differences at each time-point using a t-test if normally distributed, or the Mann Whitney-U test for non-normally distributed continuous data. |
12 weeks | |
| Secondary | Changes in mental health stress. | Self-reported mental health stress is collected using the Perceived Stress Scale (PSS). Scores on the PSS can range from 0 to 40 with higher scores indicating higher perceived stress.
The investigators will analyze between-group differences at each time-point using a t-test if normally distributed, or the Mann Whitney-U test for non-normally distributed continuous data. |
12 weeks | |
| Secondary | Recorded sleep parameters (only app condition). | Recorded objective sleep outcome measures are those collected daily using the sonar-based sleep measurement application with the same units of measure (sleep-wake in minutes) and include total time in bed (minutes), total sleep time (minutes), sleep onset latency (minutes) and wake after sleep onset (minutes). Sleep efficiency is the ratio of total sleep time divided by total time in bed, expressed as a ratio between 0-100% (higher scores indicate better sleep efficiency).
To assess the impact of the sleep change intervention, the investigators will run hierarchical regression models to quantify changes of objective sleep measures over time. |
12 weeks | |
| Secondary | Self-reported app-based health measures(only app condition). | Self-reported app-based health measures are those collected using the "Log Your Day" in the application including caffeine (cups), alcohol (glasses), sports (minutes), cigarettes (number),stress (not at all to extreme), fatigue (not at all to extreme), mood (very poor to excellent), energy (very low to very high) and focus (very poor to excellent).
To assess the impact of the sleep change intervention, the investigators will run hierarchical regression models to quantify changes of self-reported sleep measures over time. |
12 weeks |
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