Post-traumatic stress disorder and depressive symptoms among firefighters

A network analysis

Datos Bibliográficos

ID22079725
AutoresPeng Cheng (0000-0002-0949-9819, Central South University), Lirong Wang (0000-0002-9092-6282, Central South University), Ying Zhou (0000-0001-7335-5601, Central South University), Wenjing Ma (0000-0001-8757-651X, Central South University), Guangju Zhao (0000-0002-4233-9403, Central South University), Li Zhang (0000-0002-4441-5131, Central South University), Weihui Li (0000-0001-5257-6122, Central South University, autor de correspondencia)
Año2023
Volumen11
Páginas1096771-1096771
Fecha de publicación2023-05-04
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1096771
PMID37213609
OpenAlexW4377221146
IdiomaEN
Citas recibidas7
Referencias citadas60

Background: Firefighters, as first responders with a high risk of occupational exposure to traumatic events and heavy working stress, have a high prevalence of PTSD symptoms and depressive symptoms. But no previous studies analyzed the relationships and hierarchies of PTSD and depressive symptoms among firefighters. Network analysis is a novel and effective method for investigating the complex interactions of mental disorders at the symptom level and providing a new understanding of psychopathology. The current study was designed to characterize the PTSD and depressive symptoms network structure in the Chinese firefighters. Method: The Primary Care PTSD Screen for DSM-5 (PC-PTSD-5) and the Self-Rating Depression Scale (SDS) were applied to assess PTSD and depressive symptoms, respectively. The network structure of PTSD and depressive symptoms was characterized using "expected influence (EI)" and "bridge EI" as centrality indices. The Walktrap algorithm was conducted to identify communities in the PTSD and depressive symptoms network. Finally, Network accuracy and stability were examined using the Bootstrapped test and the case-dropping procedure. Results: A total of 1,768 firefighters were enrolled in our research. Network analysis revealed that the relationship between PTSD symptoms, "Flashback" and "Avoidance," was the strongest. "Life emptiness" was the most central symptom with the highest EI in the PTSD and depression network model. Followed by "Fatigue" and "Interest loss." Bridge symptoms connecting PTSD and depressive symptoms in our study were "Numb," "High alertness," "Sad mood," and "Compunction and blame," successively. The data-driven community detection suggested the differences in PTSD symptoms in the clustering process. The reliability of the network was approved by both stability and accuracy tests. Conclusion: To the best of our knowledge, the current study first demonstrated the network structure of PTSD and depressive symptoms among Chinese firefighters, identifying the central and bridge symptoms. Targeting interventions to the symptoms mentioned above may effectively treat firefighters suffering from PTSD and depressive symptoms

Major depressive disorder · Mood · Psychiatry · Psychopathology · Clinical Psychology · Health, Environment, Cognitive Aging · Medicine · Mental Health Research Topics · Posttraumatic Stress Disorder Research · Psychology