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Gender specific associations between potentially traumatic life events and mental health
Martha Schneider1, Claudia Traunmüller1, Christian Rominger1
1Institute of Psychology, University of Graz, Graz, Austria.
Abstract:
Background: Research consistently shows that gender influences both the likelihood of encountering potentially traumatic events (PTEs) and their psychological consequences. Exposure to PTEs, defined as life-threatening or severely harmful situations, can accumulate over time and undermine an individual's ability to cope with stress. Based on these assumptions, the current study examined the co-occurrence of PTEs separately in women and men and explored their specific associations with mental health.Methods: A cross-sectional, group-level network analysis was used to empirically cluster PTEs based on their co-occurrence, in a sample of 782 women and 401 men (n = 1183). Psychological distress was measured using the Depression, Anxiety and Stress Scale 21 (DASS 21), event-related distress was assessed with the Impact of Event Scale - Revised (IES-R) and Resilience Scale 11 (RS-11).Results: Both men and women networks exhibited similar overall connectivity, with four distinct clusters emerging from the network analysis in each sample. In women, a cluster related to assault-related trauma showed a strong connection to higher levels of depression, anxiety, and stress. Additionally, the relationships between trauma exposure and resilience in women revealed both positive and negative associations, highlighting the complexity of their interplay. In men, a cluster related to physical assault was associated with higher levels of anxiety, whereas resilience was positively associated with exposure to accidental trauma.Discussion: Overall, the study suggests gender-related patterns, with trauma-related clusters significantly linked to mental health outcomes. Future research should aim to replicate these findings in larger samples, explore a broader range of mental health indicators, and examine longitudinal dynamics to better understand gender-specific patterns and inform targeted interventions.
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