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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Burnout and anxiety levels in Human Medicine teachers, COVID-19 context

Authors: Morales Ramos, Jorge Guillermo; Picón Pérez, María Susana; Manayay LLaguento, Freddy Albaro; Reynosa Navarro, Enaidy;

Burnout and anxiety levels in Human Medicine teachers, COVID-19 context

Abstract

Introduction: In the COVID-19 context, university teachers have had to face the most complex educational demands, psychosocial risks, and the anxiety of responding to limitations in terms of connectivity and fulfillment of academic objectives. Objective: To identify the levels of burnout and anxiety in the COVID-19 context and determine how these levels are manifested in the participating teachers. Methodology: Analytical-type study; non-experimental, cross-sectional design. The population was 150 teachers of the Human Medicine Program of the University of San Martín de Porres, Chiclayo, Peru; sample: 66 teachers. The survey consisted of three sections: 1. Informed consent, 2. Maslach's Burnout Inventory, 3. Beck's Anxiety Inventory. Data processing was performed using the SPSS V.27 statistical software. All citations and bibliographical references were processed using Mendeley Desktop 1.19.8. Results: in the variable burnout syndrome, 25% of the participants are in the high level downwards; they present anxiety in 30.30% of the total. It was found that 50% of teachers presented mild to moderate anxiety. Conclusions: the largest number of teachers surveyed present anxiety due to burnout syndrome in the COVID-19 context. Finally, it is found that there is a correlation between anxiety and the sociodemographic variables sex, age, and marital status.

Keywords

Distance education, Burnout Syndrome, COVID-19, Anxiety, E-learning

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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