First Responder Resilience: A Cross-Sectional Network Analysis

First responders experience intense and continuous stress because of their occupational duties. This stress has led to an increase in rates of posttraumatic stress disorder, depression, generalized anxiety, and suicidality among first responders, relative to the general population. Research suggests that psychological resilience is a buffer against these negative outcomes among first responders. However, there are dozens of validated resilience assessments that have different theoretical foundations. Another analytic approach, network analysis, offers a framework for investigating which constructs (nodes) may have the greatest influence on understanding the process of resilience. In this study, we used the Response to Stressful Experiences Scale-22 (RSES-22) assessment, which has been validated on first responders, and estimated two models: a regularized partial correlation network and a directed acyclic graph (DAG). Item-level question six (find opportunity for growth) started the cascade in the DAG and had direct effects on seven questions on the RSES-22. Results indicate that the process of resilience might be consistent with posttraumatic growth (PTG). Two item-level responses (find opportunities for growth and lean on my faith in God or a Higher Power) were highest in predictability, although their node strength did not significantly differ. These results are consistent with existing conceptualizations of PTG: the Janus-face model, action-based model, and meaning-making and religious faith. Though the DAG helps theorize causation, these data are cross-sectional. Given the findings of this study, researchers should model resilience longitudinally among first responders to ascertain if intervention length or treatment modality impacts resilience in different ways.