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| ID | Type | Description | Link |
|---|---|---|---|
| 2R44AG058339-02A1 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| Innovative Design Labs | INDUSTRY |
| University of Minnesota | OTHER |
| Mayo Clinic | OTHER |
| National Institute on Aging (NIA) |
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This study seeks to evaluate the utility and efficacy of the Non-Contact Sleep Quality Monitor System when used to monitor the sleep quality of individuals living in long-term care (LTC) with either Alzheimer's Disease (AD) or Alzheimer's Disease Related Dementia (ADRD). This before-after comparison trial will be conducted in several LTC facilities to evaluate the effect access to System Sleep Quality Data has on documentation of sleep disorders or treatments and sleep quality change over time for AD/ADRD participants in the intervention group as compared to the control group.
All subjects will undergo sleep quality monitoring for 4-weeks. At the end of the first 2-weeks, research staff and LTC facility staff and medical providers will receive access to sleep monitoring data. We hypothesize that when real-time System Sleep Data is shared with LTC staff or healthcare providers, that sleep disturbances will be more readily detected, leading to timelier, better tailored treatment interventions for sleep disturbances, thereby improving sleep quality and decreasing daytime physical inactivity.
The purpose of this study is to evaluate the utility of a Non-Contact Sleep Quality Monitor System and determine the effect that sharing System Sleep Data with long-term care (LTC) staff and healthcare providers has on documentation and treatment of sleep disorders and change in AD/ADRD participant sleep quality. System Sleep Data will be collected for a total of 4-weeks. During the Intervention condition System Sleep Data will be shared for 2-weeks, while in the initial Control condition no System Sleep Data will be shared for 2-weeks. Healthcare providers can prescribe a non-pharmacologic sleep protocol and/or if they so choose, pharmacotherapy to manage sleep disturbances for subjects in either the Intervention or Control condition, in accordance with standard medical practice. The investigators hypothesize that when real-time System Sleep Data is shared with LTC staff or healthcare providers, that sleep disturbances will be more readily detected, leading to timelier, better tailored treatment interventions for sleep disturbances, thereby improving sleep quality and decreasing daytime physical inactivity.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Long-Term Care Facility Residents with Alzheimer's Disease or other Related Dementias | Experimental |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Non-Contact Sleep Quality Monitor System | Device | Residents of long-term care facilities with Alzheimer's or other related dementias will utilize a sleep monitoring device for the four-week period they are involved in the study. |
| Measure | Description | Time Frame |
|---|---|---|
| Documentation of sleep disorders or treatment | Primary outcome documentation of diagnosis, or evidence of treatment of sleep disorders, will be obtained through review of the medical record. Evidence of such a diagnosis or treatment could be indicated in nursing notes, physician notes, psychoactive or sedative medication changes, new ICD 10 sleep disorder diagnoses, medical orders for sleep studies or sleep medicine consults, all contained in the medical record. | 4-weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Sleep Quality Over Time: Total Nocturnal Sleep Time (TNST) | Total Nocturnal Sleep Time (TNST) will be derived from System Data and Algorithms. | 4-weeks |
| Change in Epworth Sleepiness Scale Total Score Over Time |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kathleen Unroe, MD, MHA, MS | Contact | 317-274-9227 | kunroe@iu.edu | |
| Richard Holden, PhD, MS | Contact | 317-278-5323 | rjholden@iu.edu |
| Name | Affiliation | Role |
|---|---|---|
| Kathleen Unroe, MD, MHA, MS | Indiana University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Indiana University School of Medicine | Indianapolis | Indiana | 46202 | United States |
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| ID | Term |
|---|---|
| D000544 | Alzheimer Disease |
| D003704 | Dementia |
| D020447 | Parasomnias |
| D012893 | Sleep Wake Disorders |
| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D024801 | Tauopathies |
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| NIH |
| Regenstrief Institute, Inc. | OTHER |
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The Epworth Sleepiness Scale is a validated, self-report measure of sleepiness. It is an 8-item questionnaire that measures one's tendency to become sleepy using a scale from 0 (no chance of dozing) to 3 (high chance of dozing). The total score is based on a scale of 0 to 24, with a score of 24 indicating the potential need for medical attention.
| 4-weeks |
| Change in QOL-AD Over Time | The Quality-Of-Life-Alzheimer's Disease (QOL-AD) instrument is a 13-item questionnaire that measures the domains of physical condition, mood, memory, functional abilities, interpersonal relationships, ability to participate in meaningful activities, financial situation, and global assessments of self as a whole and QOL as a whole. | 4-weeks |
| Attitudes Toward Technology | A questionnaire that measures attitudes toward technology created by Jay & Willis 1992. | 4-weeks |
| Technology Acceptance Survey Questionnaire | A validated 12-item questionnaire that measures perceptions of technology usefulness and usability, derived from Davis 1989 | 4-weeks |
| System Usage | The total number of days out of 28 that the system collected data, and the number of times the System Sleep Data User Interface was accessed. | 4-weeks |
| Change in Sleep Quality Over Time: Sleep Efficiency (SE) | Sleep Efficiency (SE) will be derived from System Data and Algorithms. | 4-weeks |
| Change in Sleep Quality Over Time: Sleep Onset Latency (SOL) | Sleep Onset Latency (SOL) will be derived from System Data and Algorithms. | 4-weeks |
| Change in Sleep Quality Over Time: Wake After Sleep Onset (WASO) | Wake After Sleep Onset (WASO) will be derived from System Data and Algorithms. | 4-weeks |
| D019636 |
| Neurodegenerative Diseases |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |