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

Abstract

Background: First responders, including firefighters and emergency medical technicians (EMTs), are under extreme stress from repeated exposure to potentially traumatic events. To optimize treatment for this population, it is critical to understand how the various posttraumatic stress disorder (PTSD) symptom factors are associated with one another so these relations may be targeted in treatment.

Method: Using a sample of treatment-seeking firefighters/EMTs (N = 342), we conducted a partial correlation network analysis of the eight-factor model. A Bayesian directed acyclic graph (DAG) was used to estimate causal associations between clusters.

Results: Approximately 37 % of the sample screened positive for probable PTSD. Internal re-experiencing and external re-experiencing had the strongest edges. In the DAG, internal re-experiencing was the parent node and was potentially predictive of external re-experiencing, negative affect, dysphoric arousal, and avoidance.

Limitations: Data were drawn from a treatment-seeking sample that may not generalize to all firefighters/EMTs.

Conclusions: The current findings are consistent with prior research suggesting re-experiencing plays a critical role in developing and maintaining PTSD symptoms. Future research should investigate non-treatment-seeking first responders, as well as EMTs and firefighters as individual populations.

Keywords: Emergency medical service; Emergency medical technicians; Firefighters; First responder; Network analysis; Posttraumatic stress.