Self-Management Behaviors of Caregivers of the Chronically Critically Ill
NCT ID: NCT03065829
Last Updated: 2018-07-10
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
19 participants
INTERVENTIONAL
2016-02-29
2017-07-31
Brief Summary
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The purpose of this study is to evaluate a theoretically-derived Adaptive SenSor-Based Intervention for Caregiver Self-ManagemenT (ASSIST) intervention compared to an attention control condition for first time caregivers of CCI patients discharged to an extended care facility. One group will be exposed to the ASSIST intervention and will wear the sensor-based technology for 30 days and receive a daily dose of MMT. Biophysical sensor data (blood pressure, heart-rate variability, pedometry, and actigraphy) will be continuously acquired and analyzed using anomaly detection and machine learning techniques to vary the dose intensity (number of doses per day) of the two components of ASSIST adding a real-time, adaptive feature to promote caregiver self-management. The other group will wear the sensor-based technology for 30 days but will not receive the daily dose of MMT. The investigators will randomly assign participants to each group.
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Detailed Description
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The investigators aim to:
1. Determine whether there are differences in the distal outcomes \[psychological burden (anxiety, depression, caregiver burden, HRQoL), cardiovascular health (BP and HRV) and economic costs\] between subjects who were exposed to ASSIST compared to those exposed to the attention control condition.
2. Examine whether decentering, self-efficacy, decision-making, motivation, caregiver activation, and perceived stress mediate the relationship between exposure to a self-management condition (ASSIST vs. attention control) and the proximal (self-management) outcomes (stress reduction behaviors, sleep hygiene behaviors, and physical activity).
3. Determine if social support and demographics (gender and age) moderate the proximal outcomes \[emotional distress, sleep quality, and physical activity\] or distal outcomes \[psychological burden (anxiety, depression, caregiver burden, HRQoL), cardiovascular health (BP and HRV) and economic costs\].
4. Explore the differences in brain activation (structural and fMRI scans) and HPA function and stress response (hair cortisol, inflammation panel) between subjects exposed to ASSIST compared to those exposed to the attention control condition.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SUPPORTIVE_CARE
DOUBLE
Study Groups
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ASSIST
The ASSIST intervention will deliver daily doses of MMT and vary dose intensity of all components each day based on the subject's biophysical data. Across a 30-day period, the ASSIST intervention will capture and analyze data to deliver on-demand MMT, guided practices to promote sleep hygiene and physical activity. Each day, subjects will receive at least one prompt to practice MMT (about 5 minutes at a time). However, based on the subject's biophysical sensor data, subjects could receive a maximum of 5 alerts or prompts per day from the device to enhance stress reduction, sleep hygiene, or physical activity.
ASSIST
Wearable sensor technology delivering mindfulness meditation training (MMT) and health promotion (sleep hygiene and physical activity) .
Attention-Control
This intervention exposes subjects to the wearable technology without the self-management components to minimize novelty effects. Subjects assigned to this condition will wear the device for 30 days, which offers them an opportunity to experientially learn to self-monitor and employ self-regulatory skills by viewing the display biophysical data. Subjects in this condition will not receive any prompts from the device.
Attention-Control
Wearable sensor technology only viewing biophysical sensor data.
Interventions
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ASSIST
Wearable sensor technology delivering mindfulness meditation training (MMT) and health promotion (sleep hygiene and physical activity) .
Attention-Control
Wearable sensor technology only viewing biophysical sensor data.
Eligibility Criteria
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Inclusion Criteria
* recognized as the family member who will assume the caregiver role for a critically ill adult requiring at least 72 hours of mechanical ventilation and scheduled for a discharge to an extended care facility
* speak and comprehend English
Exclusion Criteria
* require psychotherapy or required psychotherapy within the last three months
* have a history of dementia or major neurological illness
* pregnant
* history of medical conditions or procedures that is contraindicated for fMRI scanning
* claustrophobia requiring anxiolytics or sedation
* expected to relocate from Northeast Ohio within two months
18 Years
ALL
Yes
Sponsors
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National Institutes of Health (NIH)
NIH
National Institute of Nursing Research (NINR)
NIH
Case Western Reserve University
OTHER
Responsible Party
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Ronald Hickman
Associate Professor
Principal Investigators
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Ronald L. Hickman, PhD, RN
Role: PRINCIPAL_INVESTIGATOR
Case Western Reserve University
Locations
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University Hospitals Case Medical Center
Cleveland, Ohio, United States
Countries
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References
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Moore SM, Musil CM, Alder ML, Pignatiello G, Higgins P, Webel A, Wright KD. Building a Research Data Repository for Chronic Condition Self-Management Using Harmonized Data. Nurs Res. 2020 Jul/Aug;69(4):254-263. doi: 10.1097/NNR.0000000000000435.
Other Identifiers
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11-15-11
Identifier Type: -
Identifier Source: org_study_id
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