Network analysis of posttraumatic stress disorder in a treatment-seeking sample of US firefighters and emergency medical technicians

Emily Beattie, Katharine Thomas, Warren N. Ponder, Eric C. Meyer, Nathan A. Kimbrel, Claire Cammarata, Elizabeth Coe, Michelle L. Pennington, Angelo Sacco, Brian Nee, Frank Leto, William Ostiguy, R. Andrew Yockey, Jose Carbajal, Donna L. Schuman, Suzy B. Gulliver

Research output: Contribution to journalArticlepeer-review


BACKGROUND: First responders, like firefighters and EMTs, face high stress due to regular exposure to traumatic events. To provide effective treatment, understanding the relationship between PTSD symptoms is essential.

METHOD: A study with 342 treatment-seeking firefighters/EMTs was done using a partial correlation network analysis of an eight-factor model. A Bayesian directed acyclic graph was utilized to estimate the causal relationships between symptom clusters.

RESULTS: About 37% of the participants showed probable PTSD signs. The strongest connections were between internal and external re-experiencing. The Bayesian graph indicated that internal re-experiencing might predict other PTSD symptoms such as external re-experiencing, negative feelings, dysphoric arousal, and avoidance.

LIMITATIONS: The study's participants were seeking treatment, so the results might not be applicable to all firefighters/EMTs.

CONCLUSIONS: The findings reinforce previous research highlighting the significant role of re-experiencing in PTSD development and persistence. Further studies should explore non-treatment-seeking first responders and consider firefighters and EMTs separately.
Original languageEnglish
Pages (from-to)686-693
Number of pages8
JournalJournal of Affective Disorders
StatePublished - Nov 1 2023

ASJC Scopus Subject Areas

  • Clinical Psychology
  • Psychiatry and Mental health


  • Emergency medical service
  • Emergency medical technicians
  • Firefighters
  • First responder
  • Network analysis
  • Posttraumatic stress

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