The Impact of Distance Learning and COVID-19 Lockdown on Students' Physical Activity and Musculoskeletal Health

Purpose: During the past two years, in most institutions worldwide, educational activities were remodeled for remote delivery, due to the COVID-19 pandemic. The purpose of this study is to assess the effects of two-year distance learning on the physical activity and musculoskeletal health of university students.

Methods: This was a national, cross-sectional study using data collected via an online questionnaire distributed through university communication platforms, which included questions on online education routines, musculoskeletal health, and physical activity of university students.

Results: In total, 1,366 students (65% female, 35% male) from 11 universities took part in the survey. The most common sites of reported pain were the neck (59.5%), shoulders (22.8%), back (29%), and low back (66.7%). Musculoskeletal pain significantly increased during the lockdown, according to the visual analog scale (VAS) for pain (before: 2.7 ± 1.6; during: 5.5 ± 2.2, p<0.001). Everyday pain was referred by significantly more students during the lockdown (4.5% vs 36.1 %, p<0.001), while the percentage of asymptomatic students was significantly decreased (40.5% vs 6.1%, p<0.001). Concerning physical activity, the percentage of students who did not exercise significantly increased during the lockdown (15.1% vs 23.2%, p<0.001). Distance learning and total screen time were positively correlated with VAS for pain scores. On the contrary, an increased frequency of ergonomic position, walking intervals, and physical activity was associated with significantly decreased VAS for pain scores.

Conclusions: Distance learning and limited physical activity led to a significant increase in musculoskeletal pain in university students, while exercise and ergonomic body position were considered protective factors. Interventions to encourage physical activity and healthy studying habits should be developed by universities, since distance learning may be again necessary for the future.