The aging of the U.S. population, combined with health care workforce shortages and insufficient access to effective fall prevention and exercise programs, has contributed to a high burden of fall-related injuries in older adults, especially in those with Mild Cognitive Impairment (MCI), a precursor of Alzheimer's dementia (AD) and related dementias (ADRD). There is an urgent need for scalable, evidence-based interventions that can be delivered efficiently in the home setting. This study aims to evaluate the efficacy and impact of a comprehensive digital fall prevention program (Digital STEADI) delivered through a technology platform with two conversational agents that leverage generative artificial intelligence (gen-AI) with human oversight to increase program access, enhance adherence to clinical fall prevention protocols and best practices, and reduce fall risk among community-dwelling older adults.
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Inclusion Criteria: * Montreal Cognitive Assessment (MoCA) score between 26 and 30 * Able to walk independently with or without an assistive device. * Able to rise independently from a standard desk or dining room chair without arms. * Live independently in a non-institutional or senior community setting. * Able to speak, hear and understand English * Have 20/40 vision from 10 ft with or without correction (e.g., glasses) * Willing to participate in the requirements of the research program. * Able to meet in a physical study location on Emory campus. * Screen positive for fall risk per the Stay Independent screener. Exclusion Criteria: * acute medical illness requiring hospitalization. * hospitalized in the past 1 month. * diagnosed with dementia (ADRD) or a neurodegenerative disease other than MCI (e.g., Parkinson's, multiple sclerosis). * uncontrolled congestive heart failure (requiring hospitalization in the past year and/or unable to the equivalent of one city block). * history of hospitalization for stroke in the past 1 year. * inability to perform study procedures.