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.
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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
22
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 Ohio State University
Columbus, Ohio, United States
Depression Anxiety Stress Scale (DASS)
The DASS is a set of three self-report scales designed to measure the negative emotional states of depression, anxiety and stress in 3 subscales of 14 items each. The scores of each subscale range from 0-42. These subscales are scored by the addition of the total item scores. Total score is obtained by summing all subscores. Total minimum score: 0; Total maximum score: 126; A higher score indicates higher levels of emotional distress, depression, anxiety and stress. Total: Normal - 0-32; Mild - 33-39; Moderate - 40-49; Severe - 50-57; Extremely severe - 58+ Depression: Normal - 0-9; Mild -10-12; Moderate -13-20; Severe - 21-27; Extremely severe - 28-42 Anxiety: Normal - 0-6; Mild - 7-9; Moderate -10-14; Severe -15-19; Extremely severe - 20-42 Stress: Normal - 0-10; Mild - 11-18; Moderate -19-26; Severe - 27-34; Extremely severe - 35-42
Time frame: Baseline, 4 months
Revised Memory and Behavior Problems Checklist (RMBPC)
RMBPC 24-item, caregiver-report of observable behavioral problems in dementia patients AND the caregiver's stress reactions to these disturbances. It provides a total score and 3 subscale scores (memory, depression, and disruptive behaviors) and scores for caregiver reactions. Score ranges - Frequency: Total 0-96; Disruptive 0-32; Depressive 0-36; Memory 0-24. Sum items with scores of 0 to 4 on subscales and total. If question score is 9, exclude it from the sum and item count. Sum items for each subscale, compute the mean item score for each subscale by dividing by the number of items included in the sum. Score ranges - Reaction Total 1-96; Disruptive 1-36; Depressive 1-36; Memory 1-24. Include only items with frequency scores of 1 to 4 in the reaction scoring. Compute the mean reaction score by summing reaction scores of these items and then dividing by the number of items included in the sum. A higher score indicates worse outcomes.
Time frame: Baseline, 4 months
Change in Caregiver Emotional Reactivity
The 16-item, Difficulties in Emotion Regulation Scale (DERS-16) will be used to measure caregivers' ability to regulate emotions at baseline and end of study. The scale used is the brief version of a theoretically-driven, valid, and reliable self-report tool used to measure difficulties with emotion regulation. The brief version will be more easily administered with the study population and has been shown to be valid and reliable \[41\]. Minimum score: 16; Maximum score: 80. A higher score indicates higher levels of caregiver emotional reactivity.
Time frame: Baseline, 4 months
Five Facet Mindfulness Questionnaire
Five Facet Mindfulness Questionnaire 39-item to measure capacity for five different domains of mindfulness practice at baseline and end of study. The five facets include non-reactivity to the inner experience, non-judgment of the inner experience, acting with awareness, observing, and describing internal states. All items are scored with a scale of 1-5. Some items are marked to be reverse scored. All items are scored and summed then divided by the total in each category by the number of items in that category to get an average category score. Each category is summed to calculate the Total then divided by the number of items to get an average item score for each subscale. A higher score indicates higher levels of caregiver capacity for mindfulness practices and better outcomes. Score ranges: Total 1-5; Observing 1-5; Describing 1- 5; Acting with Awareness 1-5; Non-judging 1-5; Nonreactivity 1-5
Time frame: Baseline, 4 months
Change in Caregiver Strain
Modified Caregiver Strain Index (MCSI): It is a 13-item self-report measure that examines both subjective and objective elements of caregiver strain. The MCSI showed excellent inter-item and test-retest reliability and was correlated in expected directions with relevant criteria \[32\]. It has excellent reliability and validity, displays adequate clinical sensitivity, has an established cut-off for determining functional/dysfunctional systems, and has been used successfully on a variety of mental health outcomes \[28\]. We will use a practice tracking worksheet to assess how much the caregivers practice the exercises over the course of the study. Minimum score: 0; Maximum score: 26. High scores indicates higher caregiver strain.
Time frame: Baseline, 4 months
Family Assessment Device (FAD)
The FAD is a self-report measure that is given as a set of seven subscales measuring a different dimension of family function. Scores for each dimension (problem solving, communication, roles, affective responsiveness, affective involvement, behavior control, and general functioning) are calculated separately as the mean of the items in that subscale. Scored by summing the endorsed responses (1-4) for each subscale (negatively worded statements are reversed) and dividing by the number of items in each scale. A higher score indicates greater levels of family functioning on all subscales Score Ranges: Total 1-4; Problem Solving 1-5; Communication 1-4; Roles 1-4; Affective Responsiveness 1-6; Affective Involvement 1-7; Behavior Control 1-4; General Functioning 1-4
Time frame: Baseline, 4 months
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