# Resilient Together for Dementia: A live video resiliency dyadic intervention for persons with dementia and their care-partners early afterdiagnosis > **NIH NIH K23** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $196,342 ## Abstract PROJECT SUMMARY In this K23 proposal, I outline a comprehensive 5-year training program that will support my transition towards an independent investigator focused on the development and rigorous testing of interventions for dyads (i.e., pairs) of persons living with dementia (PWDs) and their informal care-partners, with an emphasis on early intervention. In this application, I propose a significant and innovative proposal that is directly tied with my proposed training and career development goals. Background: Alzheimer's disease and related dementias (ADRD) produce a host of stressors for PWDs and their spousal care-partners (SPs), who both experience substantial emotional distress after diagnosis. Emotional distress is interdependent within dyads and – without treatment—becomes chronic and negatively impacts both partners' health, quality of life, and their ability to navigate the short and long-term challenges associated with ADRDs. Addressing emotional distress early, when PWDs can still meaningfully participate, is an unexplored opportunity to prevent chronic emotional distress and preserve quality of life for both partners. Specific aims and research design: I aim to develop the first version of the live video Resilient Together for Dementia (RT-D) intervention and methodology via 1) interviews and quantitative surveys (N=20) of PWD-SP dyads, with additional feedback from 2) focus groups with ADRD medical stakeholders (N=4) (Aim 1). Next, I will explore, via an open pilot (N=5 dyads) with exit interviews and pre-post self- report assessments, the initial feasibility, acceptability, and credibility of the live video RT-D and procedures, and to further refine RT-D as needed (Aim 2). Finally, I will establish, via a pilot feasibility RCT of the RT-D versus control (N= up to 50 dyads), the feasibility, acceptability and credibility of RT-D following predetermined benchmarks (Aim 3). Findings will inform a hybrid efficacy-effectiveness trial through the R01 mechanisms and future studies extending this work to include additional family members and other care-partners. Training and mentoring: My aims are supported by 3 training goals to develop expertise in: 1) qualitative and mixed methods assessment to inform intervention adaptation; 2) specialty training in geriatrics and ADRD clinical care; 3) clinical trial methodology to facilitate dyadic intervention development and refinement. I will obtain mentorship from an exemplary team led by my primary mentor Dr. Ana-Maria Vranceanu, a clinical health psychologist with expertise in mixed-methods research and live video dyadic intervention development, and my co-mentor Dr. Christine Ritchie, a geriatrician and palliative care physician with decades of work improving the treatment of ADRD. My training goals are supported by 1) a team of expert mentors, 2) a rich institutional environment at Massachusetts General Hospital and Harvard Medical School, and 3) targeted coursework, scientific meetings, semi... ## Key facts - **NIH application ID:** 10898004 - **Project number:** 5K23AG075188-04 - **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI - **Principal Investigator:** Sarah Bannon - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $196,342 - **Award type:** 5 - **Project period:** 2022-09-01 → 2027-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10898004 ## Citation > US National Institutes of Health, RePORTER application 10898004, Resilient Together for Dementia: A live video resiliency dyadic intervention for persons with dementia and their care-partners early afterdiagnosis (5K23AG075188-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10898004. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*