Clinical trial NCT04536701: Learning and Improving Alzheimer's Patient-Caregiver Relationships Via Smart Healthcare Technology
Official title: Collaborative Research: Learning and Improving Alzheimer's Patient-Caregiver Relationships Via Smart Healthcare Technology
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Alzheimer Disease
Caregiver Stress Syndrome
Keywords: Alzheimer Disease
Dementia
Caregiving
Smart Health Technology
Lead sponsor: Ohio State University
Sponsor class: OTHER
Collaborators: name: University of Virginia
name: The University of Tennessee, Knoxville
First posted: 2020-09-03
Enrollment: 22
Sex: ALL
Minimum age (years): 21
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Longitudinal descriptive
Primary purpose: OTHER

Brief summary: The purpose of this project is to develop a monitoring, modeling, and interactive recommendation solution (for caregivers) for in-home dementia patient care that focuses on caregiver-patient relationships. This includes monitoring for mood and stress and analyzing the significance of monitoring those attributes to dementia patient care and subsequent behavior dynamics between the patient and caregiver. In addition, novel and adaptive behavioral suggestions at the right moments aims at helping improve familial interactions related to caregiving, which over time should ameliorate the stressful effects of the patient's illness and reduce strain on caregivers. The technical solution consists of a core set of statistical learning based techniques for automated generation of specialized modules required by in-home dementia patient care. There are three main technical components in the solution. The first obtains textual content and prosody from voice and uses advanced machine learning techniques to create classification models. This approach not only monitors patients' behavior, but also caregivers', and infers the underlying dynamics of their interactions, such as changes in mood and stress. The second is the automated creation of classifiers and inference modules tailored to the particular patients and dementia conditions (such as different stages of dementia). The third is an adaptive recommendation system that closes the loop of an in-home behavior monitoring system.

Detailed description: The purpose of this project is to develop a monitoring, modeling, and interactive recommendation solution (for caregivers) for in-home dementia patient care that focuses on caregiver-patient relationships. This includes monitoring for mood and stress and analyzing the significance of monitoring those attributes to dementia patient care and subsequent behavior dynamics between the patient and caregiver. In addition, novel and adaptive behavioral suggestions will be provided to family caregivers via text messages on project Smart phones at the right moments aimed to help improve familial interactions related to caregiving, which over time should ameliorate the stressful effects of the patient's illness and reduce strain on caregivers. The technical solution consists of a core set of statistical learning based techniques for automated generation of specialized modules required by in-home dementia patient care. There are three main technical components in the solution. - The first obtains textual content and prosody from voice and uses advanced machine learning techniques to create classification models. This approach not only monitors patients' behavior, but also caregivers', and infers the underlying dynamics of their interactions, such as changes in mood and stress. - The second is the automated creation of classifiers and inference modules tailored to the particular patients and dementia conditions (such as different stages of dementia). - The third is an adaptive recommendation system that closes the loop of an in-home behavior monitoring system.

Eligibility criteria: Inclusion Criteria for persons with dementia:

* Females and males
* Age 60-90 years
* Physician documentation of dementia: Alzheimer's disease, vascular, mixed or unspecified type
* Community-dwelling (living in the home)
* Fluent in English

Inclusion criteria for family caregivers:

* Age 21 years or older
* Informal, unpaid caregiver who resides with the care recipient
* Fluent in English
* Functioning home Wifi
* Scoring above a 3 on the Revised Memory and Behavior Problems Checklist, a clinical cut-off point used to determine caregiver stress.

Exclusion Criteria for persons with dementia:

* Presence of acute illness as this could lead to delirium
* Alcohol abuse or dependence within the past 2 years (DSM-IV criteria)
* History of significant psychiatric illness (e.g., schizophrenia).

Primary outcomes:
measure: Depression Anxiety Stress Scale (DASS)
timeFrame: Baseline, 4 months
measure: Revised Memory and Behavior Problems Checklist (RMBPC)
timeFrame: Baseline, 4 months
measure: Change in Caregiver Emotional Reactivity
timeFrame: Baseline, 4 months
measure: Five Facet Mindfulness Questionnaire
timeFrame: Baseline, 4 months
measure: Change in Caregiver Strain
timeFrame: Baseline, 4 months
measure: Family Assessment Device (FAD)
timeFrame: Baseline, 4 months
Secondary outcomes:
Other outcomes:
Locations:
city: Columbus
country: United States
facility: The Ohio State University
state: Ohio
Study officials:
affiliation: Ohio State University
name: Karen M Rose, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Rose KM, Coop Gordon K, Schlegel EC, Mccall M, Gao Y, Ma M, Lenger KA, Ko E, Wright KD, Wang H, Stankovic J. Smarthealth technology study protocol to improve relationships between older adults with dementia and family caregivers. J Adv Nurs. 2021 May;77(5):2519-2529. doi: 10.1111/jan.14714. Epub 2021 Feb 11.