Ashes2Art: Mitigation Strategies for Short-and Long-term Distress in Emergency Services Personnel During COVID-19

Network analysis of distress, suicidality, and resilience in a treatment seeking sample of first responders

INTRODUCTION

First responders are routinely and regularly exposed to traumatic events that can clinically manifest with a symptom constellation of posttraumatic stress disorder (PTSD), generalized anxiety, depression, and suicidality.

METHODS

We used network analysis to examine baseline data from treatment seeking first responders (n = 308) to examine the interrelatedness of those constructs, including a measure of resilience. We estimated two models: a regularized partial correlation network and a Bayesian Directed Acyclic Graph (DAG).

RESULTS

The models reveal converging evidence highlighting the central role of negative alterations in cognitions and mood PTSD cluster along with affective depression. These nodes did not significantly differ, though they were among the strongest in the partial correlation network and shared the most variance with the other nodes. The DAG results suggested that the negative alterations in cognitions and mood PTSD cluster predicted downstream constructs of affective depression; intrusion, hyperarousal, and avoidance PTSD clusters; and resilience. Only resilience and affective depression exhibited direct effects on suicidality. Both somatic depression and suicidality were endogenous endpoints in the DAG. Resilience exhibited an inverse path to suicide. However, resilience was relatively independent of the other constructs in the models and the DAG suggested that it was a consequence of PTSD related distress.

LIMITATIONS

The data is cross-sectional in nature that should be followed up in longitudinal studies.

CONCLUSION

Findings are discussed in respect to the role of distress and emotional dysregulation as common factors underlying a broad range of internalizing problems.

The Work Interevention Network (WIN): Foundations of a Holistic Vocational Intervention

The aim of the current study was to examine whether the key constructs targeted in the Work Intervention Network (WIN) intervention uniquely predicted well-being outcomes and mediated relations between un/underemployment and these outcomes. Using data from a sample of 462 adults in the U.S., we positioned employment status as a predictor of life satisfaction, well-being, and psychological distress. We also tested four mediators of these relations that operationalized targets in the WIN intervention – career engagement, social support, self-care, and self-blame. Employment status indirectly predicted life satisfaction, life meaning, and psychological distress via self-care and self-blame. Career engagement mediated the relation between employment status and psychological distress but in an unexpected direction. Social support was not directly predicted by employment status but predicted life satisfaction and life meaning. Results provided initial support for the WIN intervention and corroborate the contention that employment status is an important predictor of well-being.