To develop and test the direct and indirect associations between caregiver distress and its many contributing factors and covariates.Analysis using data from a national, cross-sectional survey of Canadian caregivers.A total of 6502 respondents of the 2012 General Social Survey-Caregiving and Care-receiving who self-identified as a caregiver.We used exploratory structural equation modeling to achieve our aims. Based on literature review, we hypothesized a structural model of 5 caregiving factors that contribute to distress: caregiving burden, caregiving network and support, disruptions of family and social life, positive emotional experiences, and caregiving history. Survey items hypothesized to measure each latent factor were modeled using exploratory factor analysis (EFA). After establishing a well-fit EFA model, structural equation modeling was performed to examine the relationships between caregiving factors and caregiver distress while controlling for covariates such as caregiver's and care-recipient's sociodemographic characteristics and kinship.EFA established a well-fit model that represented caregiver distress and its 5 contributing factors as hypothesized. Although all 5 had significant effects on caregiver distress, disruptions of family and social life contributed the most (β = 0.462), almost 3 times that of caregiving burden (β = 0.162). Positive emotional experiences also substantially reduced distress (β = -0.310).Understanding the multifaceted nature of caregiver distress is crucial for developing effective strategies to support caregivers. In addition to reducing caregiving burden, having flexible resources and policies to minimize disruptions to caregivers' families (eg, flexible work policies; family-oriented education, training, and counseling) and enhance the positive aspects of caregiving may more effectively reduce distress.