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Preditores cognitivos da fadiga do zoom
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Abstract(s)
O objetivo desse estudo foi analisar o potencial explicativo do modelo teórico de Riedl
(2022), considerando cada hipótese como um preditor cognitivo para a fadiga do Zoom.
Participaram da pesquisa 598 trabalhadores de uma instituição pública brasileira. Para a
coleta de dados foram utilizadas a Escala Zoom Exhaustion & Fatigue Scale (ZEF) e um
questionário sobre os preditores cognitivos da fadiga do Zoom. Os resultados
demonstraram que o modelo em sua totalidade foi significativo para prever a fadiga do
Zoom, sendo capaz de explicar 46.55% da variação no nível de fadiga do Zoom pela
análise da Regressão Linear e 37.10% pela Modelagem de Equações Estruturais (MEE).
Entre as hipóteses, aquelas que se correlacionaram mais fortemente com a fadiga do
Zoom foram o Esforço cognitivo somado ao Stress, a Interação com múltiplas faces; a
Falta de contato visual e a Assincronicidade da comunicação. Além disso, algumas
alterações no modelo foram apontadas com objetivo de aumentar seu potencial
explicativo. Isso inclui a (1) remoção da mediação da Interrupção da automaticidade da
comunicação ente a Autoconsciência e o Esforço cognitivo, (2) reconhecer o efeito direto
entre a falta de contato visual sobre o Esforço cognitivo, (3) direcionar o efeito da
Assincronicidade e Autoconsciência para o Stress, e por fim, considerar outras dimensões
a fadiga do Zoom que não passam necessariamente pelo Esforço cognitivo e pelo Stress.
Essas sugestões visam aprimorar o modelo teórico para uma compreensão mais completa
do fenómeno.
The objective of this study was to analyze the explanatory potential of theoretical model Riedl (2022), considering each hypothesis as a cognitive predictor for Zoom fatigue, un a sample of 598 employees from a Brazilian public institution. For data collection, we used the Zoom Exhaustion & Fatigue Scale (ZEF) and a questionnaire about cognitive predictors of Zoom fatigue. The results suggest that the model was significant in predicting Zoom fatigue, capable of explaining 46.55% of the variance in Zoom fatigue levels through Linear Regression analysis and 37.10% through Structural Equation Modeling (SEM). Among the hypotheses, those most strongly correlated with Zoom fatigue were Cognitive effort combined with Stress, Interaction with multiple faces, Lack of eye contact, and Asynchronicity of communication. Furthermore, some changes in the model were suggested to enhance its explanatory potential. These include (1) removing the mediation of the Interruption of communication automaticity between Self-awareness and Cognitive effort, (2) acknowledging the direct effect of the lack of eye contact on Cognitive effort, (3) directing the effect of Asynchronicity and Self-awareness to Stress, and finally, considering other dimensions of Zoom fatigue in addition to Cognitive effort and Stress. These suggestions aim to improve the theoretical model for a more comprehensive understanding of the phenomenon.
The objective of this study was to analyze the explanatory potential of theoretical model Riedl (2022), considering each hypothesis as a cognitive predictor for Zoom fatigue, un a sample of 598 employees from a Brazilian public institution. For data collection, we used the Zoom Exhaustion & Fatigue Scale (ZEF) and a questionnaire about cognitive predictors of Zoom fatigue. The results suggest that the model was significant in predicting Zoom fatigue, capable of explaining 46.55% of the variance in Zoom fatigue levels through Linear Regression analysis and 37.10% through Structural Equation Modeling (SEM). Among the hypotheses, those most strongly correlated with Zoom fatigue were Cognitive effort combined with Stress, Interaction with multiple faces, Lack of eye contact, and Asynchronicity of communication. Furthermore, some changes in the model were suggested to enhance its explanatory potential. These include (1) removing the mediation of the Interruption of communication automaticity between Self-awareness and Cognitive effort, (2) acknowledging the direct effect of the lack of eye contact on Cognitive effort, (3) directing the effect of Asynchronicity and Self-awareness to Stress, and finally, considering other dimensions of Zoom fatigue in addition to Cognitive effort and Stress. These suggestions aim to improve the theoretical model for a more comprehensive understanding of the phenomenon.
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Keywords
Fadiga Videoconferências Fadiga zoom Modelo explicativo Preditores Home office Stress