Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology

Quality of Life Clinical Trial

Official title:

Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT05379504
• Other study ID #: 2043542
• Secondary ID: 1R01AG072935-01A
• Status: Active, not recruiting
• Phase: N/A
• Start date: June 1, 2022
• Est. completion date: November 2024

Study information

• Verified date: February 2024
• Source: University of Missouri-Columbia
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

Description:

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. We 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, we 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, we 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, we 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, we 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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 58
• Est. completion date: November 2024
• Est. primary completion date: November 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 65 Years and older

Eligibility

Inclusion Criteria:

• Over the age of 65, Live in a rural defined county, Have difficulty with at least 1 self-care task or 2 daily living tasks, Have internet access, Able to stand with or without assistance

Exclusion Criteria:

• Life expectancy less than one year, Severe cognitive impairment (mini mental state exam score <17), Life in a facility that provides care services, Katz ADL Score of 6, Receiving in-home physical therapy, occupational therapy or nursing, Have been hospitalized more than three times in teh previous 12 months, Plan to change residences within the next year

Related Conditions & MeSH terms

• Disabilities Multiple
• Quality of Life

Intervention

Behavioral:
• Standard Health Education
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.
• Self Management
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.

Locations

Country	Name	City	State
United States	University of Missouri	Columbia	Missouri

Sponsors (2)

Lead Sponsor	Collaborator
University of Missouri-Columbia	National Institute on Aging (NIA)

Country where clinical trial is conducted

United States, 

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Wang S, Skubic M, Zhu Y. Activity density map visualization and dissimilarity comparison for eldercare monitoring. IEEE Trans Inf Technol Biomed. 2012 Jul;16(4):607-14. doi: 10.1109/TITB.2012.2196439. Epub 2012 Apr 25. — View Citation

Wang, S. (2011). Change Detection for Eldercare Using Passive Sensing. PhD. Thesis, Electrical and Computer Engineering Dept., University of Missouri, Columbia, MO

Weisz, J.R. (2015). Bridging the research-practice divide in youth psychotherapy. The deployment-focused model and transdiagnostic treatment. Verhaltenstherapie, 25(2), 129-132

Wu, W., Keller, J.M., Skubic, M., Popescu, M., & Lane, K.R. (in review). Early detection of health changes in the elderly using in-home multi-sensors data streams.

* Note: There are 95 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in Katz ADL Index	Disability	1 year
Primary	Change in PROMIS-29	Health-related quality of life	1 year
Secondary	Change in Hospital Anxiety and Depression Scale	Depression and anxiety	1 year
Secondary	Change in Canadian Occupational Performance Measure	Occupational performance	1 year
Secondary	Change in Patient Activation Measure	Patient activation/self-efficacy	1 year
Secondary	Technology Experience Profile	Experience with technology	Baseline