Attention indicators as markers of fatigue in ambulance workers

Author:

Bolobonkina TA1,Dementiev AA1,Minaeva NV1

Affiliation:

1. Pavlov Ryazan State Medical University, Ryazan, Russia

Abstract

Medical care at the pre-hospital stage requires concentration of attention from ambulance workers and induces stress on the functional systems of their bodies. The spread of COVID-19 has increased the workload on mobile ambulance teams and worsened functional state of the team members' central nervous systems. This study aimed to investigate the impact of professional activity on changes in the indicators reflecting attention capacity, allocation and switching in mobile ambulance healthcare workers in the context of the COVID-19 pandemic. We used the Number Square method to assess these indicators. The participants were divided into groups with the help of standard tens, through standardization of the number of digital symbols, correct answers, mistakes made and time spent. The clear signs of fatigue by the end of the work shift are the decreased attention capacity, registered in 40.48% (p < 0.0001) of participants, and deteriorating attention allocation, registered in 64.29% (p < 0.05). The dynamics of the indicators were revealed to be associated (negative trends) with length of service and age. The registered values did not decrease at each subsequent shift, which proves the rest period between the shifts ensures a sufficient recovery. Decreased attention capacity and allocation by the end of the shift, as objective signs of fatigue, depend on age and length of service. Lack of negative dynamics shift-to-shift shows that the functional resources of the body are restored during the prescribed rest period even in the intense conditions of mobile ambulance teams' work during the COVID-19 pandemic.

Publisher

Federal Medical Biological Agency

Subject

Literature and Literary Theory,Cultural Studies,Developmental and Educational Psychology,Immunology and Allergy,Immunology,Immunology and Allergy,Computer Science Applications,Instrumentation,Chemical Engineering (miscellaneous),Analytical Chemistry,Artificial Intelligence,Computational Theory and Mathematics,Software,Clinical Biochemistry,Information Systems,Control and Systems Engineering,Software,Artificial Intelligence,Signal Processing,Control and Systems Engineering,Pharmacology,General Neuroscience

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