Abstract:
Computers and mobile devices are becoming the primary instruments used by students worldwide in all facets of their working and learning activities. This study aimed to investigate the relationship between the use of electronic devices, the characteristics of learning properties, and the potential predictors of work-related musculoskeletal disorders (WMSDs) among Thai undergraduate students. In this cross-sectional study, data were collected using Microsoft Forms with an online self-administered scale. The research instrument comprised four categories: demographic and health history characteristics, online learning properties, psychological health, and perceived WMSDs. Using multistage sampling, 4,618 samples were collected from 18 schools nationwide. A total of 3,705 respondents were eligible for the analysis. Descriptive statistics, chi-square, and binary logistic regression analyses were used for the data analysis. The results showed that the majority of the respondents had online learning only in some semesters/subjects (67.3%), used mobile phones for learning (43.3%), had an appropriate desk workstation (66.1%), used non-office chairs (76.0%), spent prolonged periods sitting (91.6%), had a bent posture while sitting (78.2%), had a private working space/room (92.4%), had proper lighting (85.4%), and experienced normal levels of stress (81.1%). Overall, 42.1% of Thai university students experienced WMSDs in any area of the body in the prior 6 months. Six significant predictors (p = 0.05) of WMSDs were obtained from the multivariate analysis, including stress, use of electronic devices, bent posture, prolonged sitting, year of study, and online learning classes (The adjusted odds ratio ranged from 1.43 to 3.67). High-risk students who mostly used mobile learning devices should be prescribed interventions to reduce stress, develop postural awareness and skills, emphasize positioning solutions, and reduce extended sitting time. The results indicated that preventive measures are warranted and required because the risk predictors were identified as preventable.
