Using Clustering Methods to Map the Experience Profiles of Dementia Caregivers

Abstract

Abstract Background and Objectives Caregivers of persons living with dementia report wide-ranging lived experiences, including feelings of burden and frustration but also positivity about caregiving. This study applies clustering methodology to novel survey data to explore variation in caregiving experience profiles, which could then be used to design and target caregiver interventions aimed at improving caregiver well-being. Research Design and Methods The k-means clustering algorithm partitioned a sample of 81 caregivers from the Midwest region of the United States on the basis of 8 variables capturing caregiver emotions, attitudes, knowledge, and network perceptions (adversity: burden, anxiety, network malfeasance; network nonfeasance; positivity: positive aspects of caregiving, preparedness and confidence in community-based care, knowledge about community services for older adults, and network uplift). The experience profile of each segment is described qualitatively and then regression methods were used to examine the association between (a) experience profiles and caregiver demographic characteristics and (b) experience profiles and study attrition. Results The clustering algorithm identified 4 segments of caregivers with distinct experience profiles: Thriving (low adversity, high positivity); Struggling with Network (high network malfeasance); Intensely Struggling (high adversity, low positivity); Detached (unprepared, disconnected, but not anxious). Experience profiles were associated with significantly different demographic profiles and attrition rates. Discussion and Implications How caregivers respond to support interventions may be contingent on caregivers’ experience profile. Research and practice should focus on identifying public health strategies tailored to fit caregiver experiences. Clinical Trial Registration NCT03932812