The network structure of childhood adversities and adult depressive symptoms in rural Uganda

PROJECT SUMMARY Adverse childhood experiences (ACEs), including abuse, household dysfunction, and neglect, are pervasive in resource-limited settings and exert consequences on mental and behavioral health across the lifespan. Preliminary data from rural Uganda, the site of the proposed research, are consistent with this literature, demonstrating robust associations between ACEs and adult depression symptom severity, major depressive disorder, and suicidality. Yet researchers have raised concerns about the accuracy with which ACEs are retrospectively reported. The theory of mood congruent memory biases suggests that individual factors at the time of assessment (e.g., affective states) may influence reporting. A second limitation of this literature is that the cumulative disadvantage operationalization of ACEs obscures our understanding of the pathways linking ACEs and depression. Without this information, the field lacks the empirical scaffolding needed for the design of targeted intervention programs that can effectively address the mechanisms through which ACEs influence depression. The fellowship candidate of this proposed F31 award seeks to achieve the long-term goal of becoming an independent investigator with expertise in identifying risk and protective factors for mental health and in developing novel peer-delivered and social network interventions that harness positive social and cultural dynamics to increase access to evidence-based mental health care in low resource settings. Three training objectives are proposed: (1) psychometric and longitudinal data analysis, (2) advanced social network analysis, and (3) psychological symptom network analysis. This training will be consolidated through secondary analyses of sociocentric social network data from the co-sponsor’s population-based cohort study in a rural region of southwestern Uganda (N=1,772). Three specific aims, tightly linked to the training objectives, are proposed: (1) determine the test-retest reliability of retrospectively-reported ACEs and estimate correlates of changes in reporting over time; (2) estimate the co-symptomatology network of depression symptoms and ACEs; and (3) assess the extent to which individual social network characteristics are associated with the structure of the co-symptomatology network. The key innovation of this F31 application is that it proposes the first study to integrate a psychological symptom network analysis with rich sociocentric social network data. The fellowship candidate will receive individualized mentorship by a team of sponsors and consultants with complementary expertise—paired with focused coursework, workshops, meetings, and readings—thereby ensuring acquisition of the statistical skills needed to accomplish these aims. The findings are expected to have significant public health impact by informing the design of accessible, resource-efficient interventions that target central ACEs and depression symptoms.