Dynamic networks of complex posttraumatic stress disorder and depression among college students with childhood trauma: insights from cross-sectional and cross-lagged panel network analysis

<b>Background and Objective:</b> There is a current research gap regarding the symptom structure and underlying causal relationships between complex posttraumatic stress disorder (CPTSD) and depressive symptoms. This longitudinal study used a cross-sectional network and cross-lag panel network (CLPN) to examine how CPTSD and depression symptoms interact over time in Chinese college students with childhood trauma.<b>Methods:</b> From 18,933 college students who took part in 2 surveys 12 months apart, 4006 participants (mean age: 20.07 ± 2.04) who reported childhood trauma were screened. Within this sample, there were 2354 (58.8%) males and 1652 (41.2%) females.<b>Results:</b> In the one-year interval CLPN model, it was found that depressive symptoms may precede other symptoms. Specifically, negative emotions and negative self-evaluations are more likely to predict subsequent symptoms. Conversely, in CPTSD, symptoms related to fear and anxiety, such as avoidance, intrusion, and hyperarousal, are more frequently activated by other symptoms, including negative emotions<b>Conclusions:</b> This finding offers a novel perspective on the interplay between CPTSD and depression, extending the existing theory. From a clinical standpoint, the points of intervention for comorbidity between depression and CPTSD who have experienced childhood trauma differ across different stages.

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Publication Details

Journal
European Journal of Psychotraumatology
Published
2024-09-17
DOI
https://doi.org/10.1080/20008066.2024.2391656
Citations
8
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
4.06

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article

Dynamic networks of complex posttraumatic stress disorder and depression among college students with childhood trauma: insights from cross-sectional and cross-lagged panel network analysis

Mingxiao Liu, Aiyi Liu, Yizhen Ren, Lake Mozi Zhang et al.
8 citations
European Journal of Psychotraumatology
Mental Health Research Topics
4.06
article

Dynamic networks of complex posttraumatic stress disorder and depression among college students with childhood trauma: insights from cross-sectional and cross-lagged panel network analysis

Mingxiao Liu, Aiyi Liu, Yizhen Ren, Lake Mozi Zhang, Yu Peng
article en
8 citations

Abstract

<b>Background and Objective:</b> There is a current research gap regarding the symptom structure and underlying causal relationships between complex posttraumatic stress disorder (CPTSD) and depressive symptoms. This longitudinal study used a cross-sectional network and cross-lag panel network (CLPN) to examine how CPTSD and depression symptoms interact over time in Chinese college students with childhood trauma.<b>Methods:</b> From 18,933 college students who took part in 2 surveys 12 months apart, 4006 participants (mean age: 20.07 ± 2.04) who reported childhood trauma were screened. Within this sample, there were 2354 (58.8%) males and 1652 (41.2%) females.<b>Results:</b> In the one-year interval CLPN model, it was found that depressive symptoms may precede other symptoms. Specifically, negative emotions and negative self-evaluations are more likely to predict subsequent symptoms. Conversely, in CPTSD, symptoms related to fear and anxiety, such as avoidance, intrusion, and hyperarousal, are more frequently activated by other symptoms, including negative emotions<b>Conclusions:</b> This finding offers a novel perspective on the interplay between CPTSD and depression, extending the existing theory. From a clinical standpoint, the points of intervention for comorbidity between depression and CPTSD who have experienced childhood trauma differ across different stages.

European Journal of PsychotraumatologyVol. 15(1)
Kunming University of Science and Technology (CN), Beijing Normal University (CN), UCSI University (MY)
Science Research Foundation of Yunnan Education Bureau
Openalex Percentile: Top 6%
Mental Health Research Topics
4.06
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