Selected determinants of occupational stress and burnout in physiotherapists and IT professionals

Abstract

Introduction Occupational stress and burnout have a statistically significant negative impact on learning and work in the professional groups studied, but the exact manner and strength of the impact and the neurophysiological mechanisms underlying the aforementioned phenomena are not yet well understood. The main reason for this is the paucity of research, both on the neurobiological basis and on the incidence and impact on the lives of different professional groups. Aim of the study The main objective of the study is to determine the clinical and neurophysiological determinants of occupational stress and burnout, and in particular to investigate whether: - occupational stress and burnout are related to occupational group, - the start of professional work already during studies is a significant differentiating factor, - the nature of work, gender and seniority affect work-related musculoskeletal problems. Materials and methods Two groups were recruited for the study: study group (physiotherapists, n = 50), reference group (IT professionals, n = 50). Five clinimetric scales were used in the study: PSS10, MBI, SWLS, MSQ-SF, NMQ. Results Clinical and neurophysiological determinants of occupational stress and burnout relate to statistically significant effects: occupation, age, length of work, mode of employment, combination of study and work, and multi-work/multi-job. Conclusions Stress and burnout are related to the occupational group, with physiotherapists' occupational group experiencing them with greater severity than the IT occupational group. Starting a career already during studies is an important differentiating factor: it increases the risk of stress and professional burnout. The mode of employment, gender and seniority influence work-related musculoskeletal problems: they are experienced more often by the self-employed, men, older people and those with longer work experience.

Keywords

• acute stress
• burnout
• biomarkers
• adaptive model