Decomposing the association between caregiver burden and depressive symptoms in family caregivers of older adults: A network analysis

BACKGROUND: Caregiver burden is a well-established risk factor for depressive symptoms in family caregivers of older adults. However, previous research has predominantly relied on global sum scores, which may obscure specific patterns of association between distinct components of caregiver burden and depression. Network analysis offers a promising approach to reveal more granular insights by examining interactions between specific components of the constructs. METHOD: This study employed an integrative data analysis approach, pooling baseline data of family caregivers of older adults from three randomized controlled trials (N = 681). A regularized Gaussian Graphical Model was estimated, incorporating 10 caregiver burden components (SCQ-AV) and 15 depressive symptoms (CES-D). Bridge node centrality and significant edges were examined to identify key components linking caregiver burden to depressive symptoms. RESULTS: The network analysis identified mood deterioration, social isolation, constant worrying, and health strain as key bridge nodes within the caregiver burden cluster. Notable associations of these bridge nodes with depressive symptoms included mood deterioration with depressed mood, social isolation with loneliness and anhedonia, constant worry with fearfulness, and health strain with fatigue. LIMITATIONS: Cross-sectional design precludes inferences about directionality or causality. CONCLUSION: The findings suggest several unique component-level pathways between caregiver burden and depressive symptoms. Conceptualizing caregiver burden and depression as a network of interacting components provides important insights beyond global sum scores.