Improving Sleep and Quality of Life after Use of a Haptic Vibrotactile Trigger Technology, Drug-Free, Topical Patch: Results from the HARMONI Study
Bibliographic record
Abstract
Sleep issues are widely prevalent throughout the US and can greatly impact a person’s quality of life while imparting a significant personal and societal burden. Evidence supports the importance of sleep health to overall physical health, behavioral health, wellness, and safety. Several diseases have been identified as having a significant association with sleep disorders and sleep duration, including depression, diabetes, obesity, hypertension, and cardiovascular events. Conventional pharmacological treatments for sleep disorders have been associated with dangerous adverse effects. Identifying effective and safe alternative treatment strategies, including those that are non-invasive and non-pharmacologic and that have reduced and limited side effect profiles, will provide options that may be preferable in how clinicians traditionally treat sleep disorders. There has been research focusing on neuronal pathways and circuits that have been shown to respond to sensory (nociceptive) stimulation. Researchers have shown that these pathways and specific areas of the brain can change in response to external stimuli. Haptic vibrotactile trigger technology (VTT) is designed to target the nociceptive pathways and theorized to disrupt these brain centers. The technology has been incorporated into non-invasive, non-pharmacological topical patches and other routes of delivery. The purpose of this IRB-approved, minimal risk observational study was to evaluate patients’ experiences and/or perceptions and patient response for those who received a haptic vibrotactile trigger technology (VTT) embedded non-pharmacologic, non-invasive, over-the-counter sleep patch (REM Sleep Patch with VTT; Super Patch Company, Srysty Holding Co, Toronto, Canada). Methods: Baseline, 7- and 14-day data were recorded in one hundred thirteen (113) adult subjects (79 females and 34 males) with a mean age of 53 years who presented with sleep- or insomnia- related issues or associated symptoms. The study evaluated changes in overall sleep quality and insomnia severity scores via validated scales (PSQI (Pittsburgh Sleep Quality Index) and the ISI (Insomnia Severity Index)), changes in the use of prescription and OTC medications, patient satisfaction, and any side effects reported while using the patch. Future analysis will compare the outcomes reported here with control and crossover treatment groups. Results: The results showed statistically significant decreases in time to fall asleep, an increase in number of hours of sleep, improvement in the quality of sleep, and reduction in global PSQI Score after using the VTT embedded sleep patch. After 14 days, the vast majority of patients reported a reduction of usage of oral medications, that the patch was convenient and easy to use, and preferred the patch over oral and other medications for sleep. Results also showed positive outcomes in Quality of Life (QoL) components with improvements in daytime fatigue, mood, ability to function at work/daily chores, concentration, memory, and mood. Conclusions: Study results indicate that this non-pharmacologic, non-invasive, haptic vibrotactile trigger technology (VTT) embedded topical patch improves sleep quality, duration, and quality-of-life components and may reduce the use of concurrent medications, including prescribed and other oral medication for adult patients with sleep or insomnia-related symptoms. Results reported suggest that the non-pharmacological topical sleep patch has incredible potential to be added to the current approaches and treatments of noninvasive and nonpharmacological sleep therapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".