Mild Behavioral Impairment

How to ensure adherence to computerized cognitive training in unsupervised circumstances (e.g., at-home, self-administered) in older adults at risk for Alzheimer's disease (AD) or AD related dementia (AD/ADRD) is understudied. The objective of the R33 study is to test a novel facial expression-based personalization engine (FPE) for monitoring and modulating real-time effective engagement, with an ultimate goal of enhancing long-term adherence in unsupervised cognitive training in older adults at risk for AD/ADRD. Here, Effective engagement is defined as the extent to which someone is actively engaged and performing with significant attention and enjoyment while training, addressing a balance between adherence and cognitive gains/plasticity from the training. Based on previous work, the hypotheses include that (1) mental fatigue revealed in facial expressions will reflect a trainee's degree of effective engagement, which can be modified by modulating task novelty; (2) the proposed FPE will ensure the effective engagement in cognitive training by monitoring trainee facial expressions and modulating training in response, promoting the trainee's long-term adherence to the training and cognitive plasticity. A Stage II intervention efficacy study will be conducted to compare effective engagement and adherence in unsupervised cognitive training between training programs with vs. without FPE in older adults at risk for AD/ADRD. The proposed FPE may assist in monitoring and improving effective engagement and adherence in older adults with unsupervised cognitive training. In the current application, FPE in a cognitive training program called speed of processing training will be tested. However, such FPE may be embedded to any computerized cognitive training in future studies to help address adherence related issues.

The goal of this study is to objectively test one's sense of smell, called olfaction, in participants with Subjective Cognitive Concerns (SCC), Mild Cognitive Impairment, Mild Behavioral Impairment (MBI), and age-matched controls. The main question it aims to answer is whether the AROMHA Brain Health Test could serve as a predictive biomarker of neurodegenerative disorders. This understanding will aid in the development of a noninvasive, cost-effective diagnostic tool that reliably and specifically distinguishes disease and normal aging populations. Participants will take the approximately 45-minute AROMHA Brain Health Smell Test where they will peel and sniff labels on the physical smell cards and answer questions on the web-based app relating to what they smelled. Participants will undergo tests for odor intensity, odor identification, odor discrimination, and episodic olfactory memory, but will not be provided the results of these tests.