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| ID | Type | Description | Link |
|---|---|---|---|
| 1R01AG072935-01A1 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute on Aging (NIA) | NIH |
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The social distancing requirements for COVID-19 coupled with the adverse health impacts of social isolation and decreased access to healthcare in rural areas places older adults with disabilities in a dire situation. The smart sensor system to be deployed and studied in this project aims to reduce disability for rural community-dwelling older adults and improve health-related quality of life, including depression and anxiety. An implementation guide will be developed to increase success of future scale-up evaluations.
Over 85% of Missouri is rural and individuals in these rural areas are older and have reduced access to regular healthcare as compared to individuals living in urban areas of Missouri. Those with disabilities, particularly older adults, are at higher risk for contracting COVID-19. There is a critical need to reduce disability and improve quality of life for community-dwelling older adults with disabilities for successful aging-in-place during the COVID-19 pandemic. The investigators have developed, with our partner company Foresite Healthcare, a proven sensor-based technology solution for monitoring health-related behaviors in the home. In a multi-site randomized controlled trial, the investigators demonstrated that the sensor system with nursing care coordination prevents declines in function for older adults living in assisted living facilities. The long-term goal of this research is to support independent living for older adults with disabilities for as long as possible. The purpose of this project is to deploy the sensor system in the homes of rural community-dwelling older adults with disabilities and evaluate the effect of the sensor system on reducing disability and improving health-related quality of life. Using a two-arm randomized controlled trial, the sensor system will be installed in the homes of 64 older adults. Participants randomized to Study Arm 1 will receive a multidisciplinary (nursing, occupational therapy, and social work) self-management intervention paired with the sensor system. This intervention is based on the 5As self-management approach and is a direct translation of the nursing care coordination in our prior research. Participants randomized to Study Arm 2 will have standard health education paired with the sensor system. An implementation guide for future use with different partner agencies will be developed using individual and setting level data collected from Aims 1, 2 and 3 using the RE-AIM framework. The project will be accomplished in three aims. In Aim 1, the investigators will evaluate the effect of a sensor system paired with a multidisciplinary self-management intervention as compared to the sensor system paired with standard health education care on disability and health-related quality of life after 1 year. In Aim 2, the investigators will evaluate the effect of the sensor system on secondary health outcomes (depression, anxiety, occupational performance, and caregiver burden), rates of falls, and healthcare usage. In Aim 3, the investigators will collect individual participant data for satisfaction and adoption and stakeholder data about organizational setting. Data from Aims 1, 2 and 3 will be analyzed using RE-AIM to produce implementation guidance contextualized by organizational setting. For older adults with disabilities living in rural areas, the sensor system has the potential to change the approach to healthcare and disability management.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Self Management | Experimental | The 5A's Behavior Change Mode [39] is the framework for the self-management intervention. The five "A"s will be addressed through the integration of the self-management intervention and the sensor system. There will be a minimum of four intervention sessions with each healthcare profession (OT, RN, and SW) for 12 visits per participant. |
|
| Health Education | Active Comparator | Participant's randomized to the standard health education arm will receive the intervention at Month 1 and then months 3, 6, 9 and 12. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Standard Health Education | Behavioral | Participants randomized to the standard health education arm will receive the intervention at month 1 and then months 3, 6, 9, and 12 (coinciding with the quarterly interviews). The participant will use the tablet and telehealth platform to complete the interview and education session with research staff. The content of these sessions will be focused on helping the participant (and family member/caregiver as appropriate) understand their health data, assisting them with any technology issues and providing the participant with education on their condition(s) and any requested resources. Research staff will will also provide any additional health education if there are changes to conditions or new diagnoses after an outside provider visit. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Katz ADL Index | Disability | 1 year |
| Change in PROMIS-29 | Health-related quality of life | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Hospital Anxiety and Depression Scale | Depression and anxiety | 1 year |
| Change in Canadian Occupational Performance Measure | Occupational performance |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Rachel M Proffitt, OTD | University of Missouri-Columbia | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Missouri | Columbia | Missouri | 65211 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Background | Missouri Department of Health and Senior Services 2019. Health in rural Missouri: Biennial report 2018-2019. http://health.mo.gov/living/families/ruralhealth/pdf/biennial2019.pdf | ||
| Background | Research and Training Center on Disability in Rural Communities. 2020. Missouri State Profile. http://rtc.ruralinstitute.umt.edu/state-profile-map-series/missouri-state-profile/ | ||
| Background | Kane, R, L, (1999). A new model of chronic care. Generations-Journal of the American Society on Aging, 23(2), 35-37 | ||
| 28711423 | Background | Rantz M, Phillips LJ, Galambos C, Lane K, Alexander GL, Despins L, Koopman RJ, Skubic M, Hicks L, Miller S, Craver A, Harris BH, Deroche CB. Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing. J Am Med Dir Assoc. 2017 Oct 1;18(10):860-870. doi: 10.1016/j.jamda.2017.05.012. Epub 2017 Jul 12. |
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The investigators will share de-identified clinical outcome data and parameters extracted from the sensor system (e.gs., motion density, gait speed) associated with the study participants by depositing these data at the National Archive of Computerized Data on Aging (NACDA) which is an NIH-funded repository. Submitted data will confirm with relevant data and terminology standards. Data will be de-identified following the University of Missouri IRB procedures. All sensor parameters are stored on the secure server as de-identified data so no further processing will be required before depositing at NACDA. Identifiers will be removed from clinical outcome data before depositing at NACDA. All personal and private information of study participants will be protected using our secure data collection system (RedCap) on an encrypted network. No personal or private information will be shared.
Data will be available at the completion of the study and will be held according to parameters for the National Archive of Computerized Data on Aging (NACDA)
As I will be using National Archive of Computerized Data on Aging (NACDA), which is an NIH-funded repository, this repository has policies and procedures in place that will provide data access to qualified researchers, fully consistent with NIH data sharing policies and applicable laws and regulations.
| Type | Date | Date Unknown |
|---|---|---|
| Release | Jan 15, 2026 | |
| Reset | Feb 4, 2026 | |
| Release | Feb 16, 2026 | |
| Reset | Mar 6, 2026 | |
| Release | May 26, 2026 | |
| Reset | Jun 22, 2026 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Jan 15, 2026 | Feb 4, 2026 | |||
| Feb 16, 2026 |
| ID | Term |
|---|---|
| D000073278 | Self-Management |
| ID | Term |
|---|---|
| D012046 | Rehabilitation |
| D006296 | Health Services |
| D005159 | Health Care Facilities Workforce and Services |
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Individuals will be randomized to one of two study arms in blocks of 4.
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Outcomes assessor will be masked to study participant assignment. Baseline assessments will be completed prior to enrollment.
|
| Self Management | Behavioral | The self-management intervention will be delivered over the course of a year. There will be a minimum of four intervention sessions with each healthcare profession (OT, RN and SW) for 12 visits per participant. The team (OT, RN and SW) will meet twice during the first 2 months to determine a lead interventionist based on the participant's SMART goals and areas of concern. The lead interventionist will have three additional sessions with the participant and will be the point-person for sensor system alerts and messages. Goal Attainment Scaling [83] will be administered during the quarterly interview to assess participant progress on SMART goals. This measure is administered collectively with the participant, provides further accountability, offers opportunities to the participant for reflection on progress, and is a concrete measure of "success" of the self-management intervention. |
|
| 1 year |
| Change in Patient Activation Measure | Patient activation/self-efficacy | 1 year |
| Technology Experience Profile | Experience with technology | Baseline |
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