A Regression Analysis Study on the Presence of Pain in Specific Body Regions Based on Smartphone Usage Posture, Smartphone Addiction, Smartphone Usage Patterns

Background: The increasing prevalence of smartphone use has been associated with musculoskeletal pain; however, the specific roles of demographic factors, smartphone usage time, posture, contents and state of addiction on pain in the upper-body regions remain unclear. Objects: This study investigated the influence of smartphone usage characteristics, including age, occupation, visual condition, duration, content, and posture, as well as smartphone addiction, on musculoskeletal pain in upper-body regions. This study aimed to comprehensively elucidate the factors contributing to the pain associated with smartphone use. Methods: A cross-sectional survey was conducted with 316 participants aged 20-59 years. Data on personal characteristics, smartphone use patterns, state of addiction (measured using the Smartphone Addiction Scale-Short Version), and musculoskeletal discomfort (Cornell Musculoskeletal Discomfort Questionnaire and Cornell Hand Discomfort Questionnaire) were collected. Binary logistic regression analysis identified significant predictors of pain in different body regions. Results: Younger age (20-30 years), being housewives or students, and vision impairment (shortsightedness) significantly increased the likelihood of neck, shoulder, and hand pain. Prolonged smartphone use (7-10 hours daily) and gaming were strongly associated with elevated pain risk, whereas moderate usage (1-4 hours daily) may be protect against lumbar pain. Non-neutral postures, especially side lying, have emerged as critical risk factors, with left-side lying linked to hand pain and right-side lying linked to upper back pain. Smartphone addiction consistently predicted pain across all regions by amplifying physical strain through prolonged engagement and poor posture. Conclusion: This study highlighted the multifactorial nature of smartphone-related musculoskeletal pain, emphasizing the roles of demographic characteristics, usage patterns, and addiction. These findings provide a foundation for developing tailored ergonomic and behavioral interventions to mitigate pain risks, particularly in high-use populations. Future research should validate these findings through longitudinal studies and objective measures.