From childhood trauma to complex PTSD: a network analysis

<b>Background:</b> Network analysis enables the understanding of complex posttraumatic stress disorder (CPTSD) as interconnected symptoms, with Bayesian networks allowing causal inference. However, existing network studies have included populations with varied trauma types and durations, yielding mixed results, and have rarely incorporated trauma histories into the analyses, despite their etiological significance.<b>Objective:</b> This study examines the structural relationships and potential pathways between childhood trauma types and CPTSD symptoms in individuals with interpersonal childhood trauma, aiming to identify possible key variables that could guide intervention targets.<b>Method:</b> The analysis included 249 adults with histories of interpersonal childhood trauma. Childhood trauma histories were assessed through the Childhood Trauma Questionnaire (CTQ), and CPTSD symptoms were measured by the International Trauma Questionnaire (ITQ). Network analysis comprised complementary methodologies: a regularized partial correlation network using graphical LASSO with centrality and bridge centrality, and a directed acyclic graph (DAG) using a Bayesian hill-climbing algorithm. Additional methodologies included exploratory graph analysis, unique variable analysis, predictability, and bootstrapped stability metrics to enhance methodological rigour.<b>Results:</b> The analysis suggested a potential pathway from emotional neglect to emotional abuse, with negative self-concept bridging trauma experiences and subsequent symptoms; however, supplementary analyses warrant caution in interpretation. Accordingly, rather than pinpointing individual symptoms, the findings highlight upstream variables - particularly negative self-concept and disturbances in relationships - as potential intervention targets. Notably, incorporating trauma experiences into the DAG analysis revealed directional patterns that contrasted with symptom-only networks, suggesting that trauma experiences serve as crucial reference points.<b>Conclusions:</b> This exploratory study demonstrates the value of integrating trauma variables and complementary network methodologies in understanding the CPTSD network. The findings suggest the potential significance of emotional trauma and upstream variables in symptom development, while highlighting how trauma context can anchor symptom relationships in the Bayesian network.

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Publication Details

Journal
European Journal of Psychotraumatology
Published
2025-10-28
DOI
https://doi.org/10.1080/20008066.2025.2571365
Primary Topic
Mental Health Research Topics
Type
article
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article

From childhood trauma to complex PTSD: a network analysis

Eunhye Kim, Young-gun Ko
European Journal of Psychotraumatology
Mental Health Research Topics
article

From childhood trauma to complex PTSD: a network analysis

Eunhye Kim, Young-gun Ko
article en

Abstract

<b>Background:</b> Network analysis enables the understanding of complex posttraumatic stress disorder (CPTSD) as interconnected symptoms, with Bayesian networks allowing causal inference. However, existing network studies have included populations with varied trauma types and durations, yielding mixed results, and have rarely incorporated trauma histories into the analyses, despite their etiological significance.<b>Objective:</b> This study examines the structural relationships and potential pathways between childhood trauma types and CPTSD symptoms in individuals with interpersonal childhood trauma, aiming to identify possible key variables that could guide intervention targets.<b>Method:</b> The analysis included 249 adults with histories of interpersonal childhood trauma. Childhood trauma histories were assessed through the Childhood Trauma Questionnaire (CTQ), and CPTSD symptoms were measured by the International Trauma Questionnaire (ITQ). Network analysis comprised complementary methodologies: a regularized partial correlation network using graphical LASSO with centrality and bridge centrality, and a directed acyclic graph (DAG) using a Bayesian hill-climbing algorithm. Additional methodologies included exploratory graph analysis, unique variable analysis, predictability, and bootstrapped stability metrics to enhance methodological rigour.<b>Results:</b> The analysis suggested a potential pathway from emotional neglect to emotional abuse, with negative self-concept bridging trauma experiences and subsequent symptoms; however, supplementary analyses warrant caution in interpretation. Accordingly, rather than pinpointing individual symptoms, the findings highlight upstream variables - particularly negative self-concept and disturbances in relationships - as potential intervention targets. Notably, incorporating trauma experiences into the DAG analysis revealed directional patterns that contrasted with symptom-only networks, suggesting that trauma experiences serve as crucial reference points.<b>Conclusions:</b> This exploratory study demonstrates the value of integrating trauma variables and complementary network methodologies in understanding the CPTSD network. The findings suggest the potential significance of emotional trauma and upstream variables in symptom development, while highlighting how trauma context can anchor symptom relationships in the Bayesian network.

European Journal of PsychotraumatologyVol. 16(1)
Korea University (KR)
Openalex Percentile: Top 68%
Mental Health Research Topics
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