Abstract

Both Childhood Adversity (CA) and resilience are heterogeneous constructs that are differently conceptualized and operationalized across studies. CA in any operationalization is associated with mental and physical health problems across the lifespan, but some individuals fare quite well after CA exposure. The large body of studies investigating CA and its consequences includes a growing number of studies on resilience following CA exposure. However, large heterogeneity in study design and conceptualization of resilience hampers integration of findings and our understanding of positive outcomes after CA. Collaborative efforts to move the field forward have been valuable yet insufficient, as a consensus on the conceptualization and study of resilience in the context of CA is still lacking. Therefore, we postulate the need for the practical implementation of a comprehensive multilevel dynamic framework of resilience after CA, which aims to guide the integration of I) the contextual diversity of CA, II) the heterogeneity of resilience operationalization in the context of CA, and III) time dynamics of resilience after CA. We build upon earlier frameworks and postulate that CA occurs in and is impacted by different contexts, such as the direct family environment and the broader community context. Second, we show that studies on resilience following CA measure outcomes across different functional levels (inflammatory, endocrine, brain structure and function, cognitive/emotional/behavioral/social functioning, and health, well-being, and quality of life), adhere to numerous definitions, and are inconsistent in referring to the integral dynamic nature of resilience. In addition, we present a multilevel dynamic framework reporting checklist to encourage practical implementation of our framework and facilitate an explicit conceptualization and assessment of resilience during or after CA exposure. Our framework and corresponding checklist could promote transparency, facilitating the synthesis of research findings, aiding in the identification of gaps for future research, and enabling multilevel modeling on the dynamic interplay between various domains of our framework.

Full Text
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