Caregiver Networks of Older Adults With Alzheimer Disease: Design and Protocol for a Multisite Study Using Network...

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.