PROJECT SUMMARY / ABSTRACT: Background: There are currently more than five million Americans living with Alzheimer’s disease and related dementias, a number expected to increase to nearly 14 million by 2050. Among the most common symptoms of persons living with dementia (PLWD) are behavioral and psychological disturbances. PLWD require care partners who themselves face challenges including guilt, depression, and emotional and physical stress due to the behavioral and psychological symptoms of dementia (BPSD). Guidelines by the American Geriatrics Society currently discourage antipsychotic prescriptions to treat BPSD, instead encouraging non-pharmacological approaches. While some non-pharmacologic strategies for addressing BPSD have shown to be effective, adherence is challenging. Novel concepts from behavioral economics (BE), a field that combines insights from economics and psychology to recognize that humans often make predictable decision errors, has shown promise in promoting appropriate disease management in a variety of healthcare settings. Mobile health (mHealth) technology is one mechanism for delivering non-pharmacologic care; however, no strategies to date have incorporated BE principles to improve adherence to non-pharmacologic strategies for managing BPSD. Research: This study will leverage the power of BE with mHealth to develop, user-test, and pilot a digital health tool aimed at improving adherence to non-pharmacologic strategies for BPSD. A thorough review of the literature, stakeholder interviews, and a design-thinking workshop will aid in the development of the BE nudges. Visits with PLWD-care partner dyads and semi-structured telephone interviews will be conducted to user-test and refine the BE-mHealth digital tool prototype. The culmination of this work will be an intervention ready for testing via a single-arm, 6-month pilot study within the New York University Langone Health (NYULH) system. The primary study outcome will be adherence to the non-pharmacologic strategies, and secondary outcomes will include changes in BPSD, care partner burden, and prescriptions for anti-psychotic medications. Socio- demographic, clinical, and primary/secondary study outcomes will be measured using care partner reported outcomes and patient electronic health records embedded within the BE-mHealth tool for ease of data capture. Training: The candidate’s proposed training plan builds upon prior research in the design and testing of BE digital health interventions via embedded pragmatic clinical trials. The candidate will receive training in the fields of dementia, digital health innovation, implementation science, and mixed-methods research through one-on- one mentorship, coursework, seminars, workshops, and conferences in disciplines of high relevance to the proposed research. The mentorship team is composed of discipline-specific experts with a history of working together and with the candidate on NIH funded grant proposals and peer-reviewed p...