Addressing Stress and Rhythm Dysregulation among Health Workers in the Post-Pandemic Context: An Italian Study and a Proposal for a Preventive Psychoeducational Intervention

During the COVID-19 pandemic, healthcare workers (HCWs) faced intense and prolonged stress. This exposure increased their risk of burnout and mood disorders. The Dysregulation of Mood, Energy, and Social Rhythms (DYMERS) hypothesis suggests that instability in biological and social rhythms may precede the onset of mood dysregulation. This study examined rhythm disturbances among HCWs and explored the potential role of a rhythm-focused psychoeducational intervention.

Ninety-seven HCWs from the University Hospital of Cagliari, Italy, participated in a cross-sectional study. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), and rhythm regulation was evaluated through the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN). Data were compared with published findings from mood disorders, psychotic disorders, and community samples.

A current depressive episode with PHQ-9 score was identified in 35.1% of HCWs participants, with significantly higher prevalence (p= 0.01) among women (42.7%) than men (14.7%). Mean BRIAN scores were 46.1 ± 11.0, significantly higher than those observed in psychotic disorder (p = 0.04) and community samples (p< 0.0001). Rhythm dysregulation scores approached values reported in bipolar disorder samples. Elevated BRIAN scores were also observed among non-depressed participants.

HCWs displayed pronounced rhythm dysregulation and high rates of depressive symptoms, highlighting occupational stress as a potential major risk factor and further supporting the DYMERS hypothesis. From both clinical and research perspectives, it could be essential to promote psychoeducational programs that target rhythm regulation, such as adaptations of Interpersonal and Social Rhythm Therapy, which may offer effective preventive strategies to enhance resilience and mental well-being in this population. However, the cross-sectional design, convenience sampling, limited socio-demographic data, and reliance on self-reported measures constrain generalizability and causal inference, underscoring the need for larger longitudinal studies to validate and extend these findings.