An integrated neurophenomenological framework for naturalistic assessment of work-related stressors in healthcare professionals: a pilot study in neuro-surgery - Crivelli, Davide; Pellencin, Elisa; Perin, Alessandro; Balconi, Michela (Frontiers in Psychology, 2025)
Work-related stress and burnout are pervasive challenges in healthcare, particularly in high-stakes specialties like neurosurgery. Neurosurgeons face unique demands, including prolonged cognitive and physical strain, emotionally charged patient interactions, and ethical dilemmas. These stressors significantly impact individual wellbeing, patient safety, and organizational efficiency. However, traditional stress assessment methods, such as self-reports and retrospective surveys, fail to capture the dynamic and context-specific nature of stress in real-world clinical environments. This paper introduces an integrated neurophenomenological framework for assessing stress in neurosurgeons, combining continuous physiological monitoring with real-time phenomenological assessments using experience sampling methods (ESM). Wearable devices enable the collection of granular physiological data—heart rate, heart rate variability, electrodermal activity, and skin temperature—while ESM provides real-time subjective insights, reducing recall biases. Synchronizing these data streams offers a holistic understanding of stress dynamics. A pilot study is introduced to discuss the feasibility of this approach. Participants engaged in ward-based and surgical tasks while their physiological data were continuously recorded. Structured interviews and psychometric tools complemented these measures, revealing context-specific stress responses: higher electrodermal activity during emotionally demanding ward shifts and elevated heart rate during physically intense surgical procedures. Discrepancies between physiological activation and subjective stress perception highlighted the importance of interoceptive awareness in modulating stress responses. This framework offers a replicable model for advancing stress research in healthcare. By integrating physiological and phenomenological data, it provides actionable insights into stress dynamics, paving the way for targeted interventions to enhance resilience and optimize patient care.