A Digital Memory Notebook to Support Everyday Functioning, Decrease Caregiver Burden, and Track Health Status
Abstract
The number of individuals suffering from Alzheimer’s disease and other disorders (ADRDs) that cause progressive decline in memory and thinking abilities will triple by 2050. Because the cognitive changes associated with these disorders can impact a person’s ability to accurately manage everyday tasks, such as managing finances and medications, there is an urgent need for interventions that will help to delay this disability and reduce demand on caregivers. Prior research has shown that training individuals with memory loss to use compensatory aids, such as calendars and note-taking systems, can improve their quality of life and independence with everyday activities. Although recent advances in technology can improve the effectiveness of compensatory aids like calendars, these aids are not widely being adopted by the growing population of older individuals with memory loss. This is partly because these technologies were not designed with this population in mind. Working with older individuals with memory loss, we developed the Digital Memory Notebook (DMN) app, an “all-in-one” memory aid and organizational tool that is user-friendly for older individuals with cognitive impairment and limited comfort with technology. In the proposed application, we will pair computer science approaches with the DMN to improve the capabilities of the DMN. We believe that many individuals with ADRDs who need support with everyday activities can lead more independent and higher-quality lives with the aid of enhanced DMN features and personalized learning support. Traditional training approaches often are not easily adaptable to the cognitive level of the learner and fail to take advantage of trainable situations when they occur in the real-world environment. Our work will use computer science methods to adapt and personalize learning of the DMN to the cognitive level of the user. These methods will also allow us to monitor DMN usage and provide automated “booster” training in real time when an individual is struggling with a DMN feature as well as provide prompting for use of the DMN as needed. We will also use computer science methods to create models that will identify trends and changes in DMN usage and collected healthcare data that may be related to changes in cognition or health status. In Aim 1, we will work with older individuals with memory loss and their caregivers to improve the capabilities of the DMN to better meet their needs. In Aim 2, we will introduce a novel, video-based personalized DMN training system to improve DMN training efficiency and increase effective long-term use of the DMN. In Aim 3, we will evaluate whether our adaptive learning system for training use of the DMN is better than a standard, non-adaptive video-based learning platform. We will also determine whether the DMN intervention improves the ability of persons with memory loss to complete everyday tasks (e.g., remembering to attend an appointment) and if it reduces demand on caregivers. In Aim 4, we will evaluate whether the DMN health tracking capabilities and DMN use metrics can be used to monitor and predict health status. This work is significant because it will demonstrate that intelligent technologies can improve the helpfulness of traditional compensation tools and intervention training methods. This work will have an important, positive impact on the surging Veterans’ population and civilian communities with cognitive impairment because it will offer a valuable tool with an adaptive learning platform and health tracking capabilities that can be used to improve the quality of life of individuals with memory impairment and their caregivers.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010654
Entities
People
- Maureen Schmitter-Edgecombe
Organizations
- United States Army
- Washington State University