Lee Ann Lindquist

Background: Family caregivers experience conflicts in caring for people with Alzheimer's dementia (PWD; e.g., siblings disagreeing, advocating with providers, PWD refusing assistance). Subsequently, family caregivers experience frustration, burden, and stress. Furthermore, these caregivers rarely receive formal conflict resolution training to ameliorate these concerns. We developed NegotiAge—an artificial intelligence (AI)‐based negotiation training intervention that teaches caregivers how to resolve conflicts and provides the opportunity to practice negotiating with online avatars in real‐world conflicts. We sought to optimize the potency and test the early effect of NegotiAge on family caregivers following the multiphase optimization strategy (MOST). Participants, Design, Setting: National randomized factorial trial of NegotiAge with family caregivers of PWD (> 65 years). Caregivers were randomized to one of eight conditions and variables/outcomes assessed at baseline and 1 month following NegotiAge. The mixed methods project used dependent sample t ‐tests (quantitative) and constant comparative analysis (qualitative). Results: Across 23 states, 125 family caregivers (mean‐age 54 years, 77% female) completed the study. Participants experienced significantly less caregiver burden (−3.24, p < 0.002) and negative affect (−2.1, p < 0.0001) between baseline and 1 month following. Those receiving two or more exercises experienced further significant burden reduction (−5.28, p < 0.04). Qualitative analyses supported these findings: “There was a time when my mother was crying. Because of the training I was able to calm her.”; “When we have a conflict, I focus on the interest of both of us–helped tremendously.” In the month following, 54% ( n = 67) of participants experienced conflicts and 74% ( n = 93) applied skills learned. Among utilizers, there was a significant decrease in forcing behaviors (−1.24, p < 0.0001). Conclusions: NegotiAge, an AI‐based negotiation training intervention, significantly reduced burden and improved negative affect among family caregivers. Engaging in more negotiation exercises further reduced burden. NegotiAge has the potential to improve the lives of caregivers and PWD. Further testing is needed to determine the direct impact on older adults and long‐term effects. Trial Registration: ClinicalTrials.gov identifier: NCT04837937

Background: Virtual reality (VR) has the potential to improve the quality of life for older adults. Most studies use proprietary VR programs, specifically designed for one goal, which vastly limits the generalizability and use by the older adult population. We sought to identify out of the box (OOTB) VR applications—available to the general population—that have applicability to geriatric care and potential value in improving quality of life. Methods: We convened and provided VR headsets to an interdisciplinary group of geriatricians, geriatric advanced practice nurses, health services researchers, older adults, and VR advanced users. Panelists were explained the goal of the study and tasked with independently searching and compiling applications that had applicability to geriatrics care or older adults, preferencing those that were cost‐free or low‐cost (< $20). Panel members regularly met to perform constant comparative qualitative analysis in discussions of the identified VR programs. Between meetings, panelists tested the apps that were identified and re‐convened with further information. Results: Of the over 200 OOTB VR applications examined, panel members identified 44 VR applications that had potential geriatric applicability and value. Potential applications were organized based on price, category, ease of use, and usefulness/applicability to older adults. Panel members reviewed potential negative attributes and applications were ranked/eliminated on perceived usability and utility for older adults. Applications were then thematically analyzed and included (1.) Cognitive support, (2.) Functional Loss/Exercise, (3.) Anti‐anxiety/agitation—relaxation, (4.) Depression alleviating entertainment, and (5.) Isolation‐relieving entertainment. Conclusion: Out of the box VR experiences can have geriatric applicability and potential value for older adults. Identifying OOTB VR through a consensus panel is the first step to generalizing use in this population. Future research will include testing with older adults, across various settings and levels of physical and cognitive function.

Patients with Alzheimer disease commonly rely on family caregivers for daily functioning. Research shows that relationships between caregivers and persons with memory loss have important effects on the health and well-being of both caregivers and persons with memory loss. However, most studies rely on a single caregiver-person with memory loss dyad as the unit of analysis, thereby neglecting the broader network of caregivers who collectively shape care experiences and outcomes. This study develops a conceptual and methodological framework for studying caregiver networks and investigates how the properties of caregiver networks relate to health and well-being outcomes for both persons with memory loss and caregivers. It measures and maps the social networks of caregivers of persons with memory loss while examining population heterogeneity in caregiver relationships and identifying network-based predictors of well-being for both caregivers and persons with memory loss. Our team is conducting a large multilocation (Illinois, Indiana, and Hawaii) study comprising 200 caregiver networks of persons with memory loss, supported by data from persons with memory loss and their caregivers. Networks will be collected using cutting-edge Network Canvas software tools, developed by members of our team within the Complex Data Collective, and analyzed using both quantitative and mixed methods. This study was funded in August 2023 by the National Institutes of Health (R01AG083034), with an expected end date of July 2028. This study protocol was approved by the institutional review board of Northwestern University (STU00219675) and was piloted internally before participant recruitment began in January 2025. As of March 2026, a total of 155 participants have been enrolled. Enrollment is planned to end by April 2027, with results expected between August 2027 and November 2027. This study advances research on caregivers of persons with memory loss by operationalizing a scalable and replicable approach to measuring caregiver networks. The ability to easily measure and identify structural features of caregiver systems helps in identifying predictors of caregiver experiences and outcomes and provides large benefits for the caregiver-person with memory loss research community.

BACKGROUND Patients with Alzheimer’s disease (AD) commonly rely on family caregivers for daily function. Research shows caregiver-person with memory loss (PWML) relationships have important effects on health and well-being for both caregivers and PWML. However, most studies rely on a single caregiver-PWML dyad as the unit of analysis, thereby neglecting the broader network of caregivers who collectively shape care experiences and outcomes. OBJECTIVE This protocol paper describes the conceptual and methodological framework for a study of caregiver networks. Study aims are to measure and map the social networks of caregivers of PWML while examining population heterogeneity in caregiver relationships and identify network-based predictors of well-being for both caregivers and PWML. METHODS Our team will conduct a large multi-location (IL, IN, HI) study of 200 PWML caregiver networks supported by data from PWML and their caregivers. Networks will be collected using our team’s cutting edge Network Canvas software tools and analyzed using both quantitative and mixed methods. RESULTS This study was awarded in August 2023 and is currently in its second year of data collection. CONCLUSIONS This project advances PWML caregiver research by operationalizing a scalable and replicable approach to measuring caregiver networks. The ability to easily measure and identify structural features of caregiver systems helps identify predictors of caregiver experiences and outcomes, and provides large benefits for the caregiver-PWML research community.

Background: As individuals experience age‐related changes, such as cognitive decline or hospitalizations, their ability to live independently at home may be impacted. Decision‐making and planning are essential in order to support successful aging‐in‐place (AIP), which is defined as continuing to live in one's home and community. Despite making plans at one single time‐point, prior research has demonstrated that decision‐making among older adults is not stagnant. Aims: The objective of this qualitative study was to understand what influences older adults to change their plans about AIP versus living in long‐term care (LTC) settings. Methods: We analyzed a subset of the PlanYourLifespan study subjects (a longitudinal cohort study of community dwelling older adults) who have shown a fluctuation in their AIP/LTC decisions over a 6‐month period and surveyed what influenced their decisions to change. Decisions related to support needed in the case of a hospitalization and Alzheimer's disease/memory loss (rehabilitation preferences, caregiver support, living preferences, and LTC facilities) were assessed. Three investigators individually coded open‐ended survey responses to identify emerging themes using constant comparative analysis with triangulation of themes. Results: Of the 293 PYL study subjects, 134 expressed a change to at least one of their decisions. Through a qualitative analysis of survey responses, five overarching themes emerged that influenced fluctuating decision‐making: (1) personal health experience, (2) health experience of a loved one, (3) increased contemplation, (4) social support network influences, and (5) denying change. Discussion: This study was the first to examine the factors that influence fluctuating AIP/LTC decision‐making among older adults. The key influencers identified highlight the importance of ongoing discussions to revisit AIP/LTC planning in the case of changing or unexpected life events. Having a strong understanding of what influences seniors in their AIP/LTC decision‐making processes will enable us to include these factors and people in decision‐making discussions.