Association between voice symptoms and college professors’ home working conditions during online classes in times of COVID-19 pandemic

Introduction. Due to the COVID-19 pandemic, teaching conditions changed around the world from in-person classes to online classes, which also determined changes on teachers’ working conditions. Method: Exploratory cross-sectional study with the aim of determining the association between two voice symptoms (vocal fatigue and throat pain) with home working conditions during online classes in times of COVID-19 pandemic. Professors answered an online survey including 27 questions about four components: sociodemographic factors, characteristics of home working, quarantine characteristics, and health conditions (including voice functioning). Results: 177 college professors from Argentina, Colombia, and Chile participated in this study. First, incidence of vocal fatigue, during online classes in times of COVID-19 pandemic, represented around 50%. Although throat pain had a smaller incidence, it was also important (35%). Second, days in quarantine, number of classes per week, people living with during quarantine, and history of vocal fatigue before quarantine were important associated factors of vocal fatigue. Third, important associated factors of throat pain were number of classes per week, level of stress, years of experience, and history of throat pain before quarantine. Conclusion: Similar to pre-COVID-19, vocal fatigue and throat pain were frequently reported voice symptoms among college professors. Associated factors of these symptoms included years of experience, number of classes per week, stress, people living with during quarantine due to COVID-19, and history of voice symptoms. Workplace Health Promotion programs should include activities that facilitate a healthy occupational voice use during and post-COVID-19 pandemic, considering the implications of online teaching on teachers’ health and safety.

Abstract licence: CC BY-NC-ND

20 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.