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| ID | Type | Description | Link |
|---|---|---|---|
| P30NR015326 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institutes of Health (NIH) | NIH |
| National Institute of Nursing Research (NINR) | NIH |
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For family members of chronically critically ill (CCI) patients, an ICU admission marks a significant milestone in the patient's illness trajectory that highlights the onset of end of-life issues and an abrupt need for family members to assume the caregiver role for the first time. Assuming the caregiver role can have devastating and longstanding health consequences for family members, which can impair their ability to sustain caregiving behaviors for a CCI patient. The unrelenting psychological distress perceived by caregivers of CCI patients is linked to significant reductions in their self-management and health outcomes.
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.
The investigators will conduct a randomized controlled trial to examine the ASSIST intervention compared to an attention control condition among 20 first time caregivers of CCI patients discharged to an extended care facility. The investigators will collect mixed methods data at baseline (T1) on Day 15 (T2) and Day 30 (T3) after subject enrollment to describe changes in proximal and distal outcomes. We have chosen our time points to capture neural and behavioral changes associated with the intervention.
The investigators aim to:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ASSIST | Experimental | 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. |
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| Attention-Control | Experimental | 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ASSIST | Behavioral | Wearable sensor technology delivering mindfulness meditation training (MMT) and health promotion (sleep hygiene and physical activity) . |
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| Measure | Description | Time Frame |
|---|---|---|
| Repeated Measures | ANCOVA Model (F-Statistic) | Baseline to 30 days |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Active Living Protocol (captured on wearable device) | Measure of Caregiver Sleep Activity | From Baseline to up to 30 days |
| Change in Daily Diary of Physical Activity (captured on wearable device) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Ronald L. Hickman, PhD, RN | Case Western Reserve University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospitals Case Medical Center | Cleveland | Ohio | 44106 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32205788 | Derived | 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. |
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| ID | Term |
|---|---|
| D016638 | Critical Illness |
| ID | Term |
|---|---|
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D007316 | Insemination, Artificial, Heterologous |
| ID | Term |
|---|---|
| D007315 | Insemination, Artificial |
| D027724 | Reproductive Techniques, Assisted |
| D012099 | Reproductive Techniques |
| D013812 | Therapeutics |
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Our model posits that effective caregiver self-management depends on analytic and emotional processing. The investigators hypothesize the ASSIST intervention will improve analytic processing by improving self-monitoring. ASSIST will expose subjects to mindfulness meditation training and promote self-awareness, which will aid the regulation of their emotional processing and improve proximal outcomes. The investigators expect proximal self-management outcomes to influence the distal outcomes of caregiver health. Our model will also test the mediating effects of decentering, processing, the hypothalamic-pituitary axis (HPA), inflammatory stress response, and cognitive mediators. The influence of potential moderators will be assessed for their effect on the relationship between the self-management intervention and the proximal and distal outcomes.
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| Attention-Control | Behavioral | Wearable sensor technology only viewing biophysical sensor data. |
|
Measure of Caregiver Physical Activity
| From Baseline to up to 30 days |
| Change in Perceived Stress Scale | Measure of Caregiver Stress | From Baseline to up to 30 days |
| Change in PROMIS-29 Scale | Measure of Caregiver Anxiety and Depression | From Baseline to up to 30 days |
| Change in Zarits Burden Interview | Measure of Caregiver Burden | From Baseline to up to 30 days |
| Change in Health Behaviors Questionnaire | Measure of Caregiver Health Related Quality of Life | From Baseline to up to 30 days |
| Change in Heart Rate Variability (captured on wearable device) | Measure of Caregiver Heart Rate Variablity | From Baseline to up to 30 days |
| D008919 | Investigative Techniques |
| D007314 | Insemination |
| D012098 | Reproduction |
| D055703 | Reproductive Physiological Phenomena |
| D012101 | Reproductive and Urinary Physiological Phenomena |