Association of Smartphone and Digital Game Addiction With Physical Activity, Sleep Quality, Stress, Fatigue, and Musculoskeletal Pain in University Students: A Cross-Sectional Study
Association of Smartphone and Digital Game Addiction With Physical Activity, Sleep Quality, Stress, Fatigue, and Musculoskeletal Pain in University Students: A Cross-Sectional Study
This study aims to examine the relationship between smartphone and digital game addiction and various health indicators, including physical activity level, sleep quality, stress, fatigue, and musculoskeletal pain among young people. University students often spend prolonged time on digital devices, which may affect their mental and physical well-being. By collecting self-reported data through validated questionnaires, the study will explore how these addictive behaviors are associated with lifestyle and health outcomes. The findings may help guide future interventions to promote healthier technology use among youth.
This cross-sectional, observational study investigates the associations between smartphone and digital game addiction and physical activity level, sleep quality, perceived stress, fatigue, and musculoskeletal pain among undergraduate students in the Department of Physiotherapy and Rehabilitation at Istanbul University-Cerrahpaşa. The study targets a minimum of 193 participants, with sample size determined via G*Power analysis. Data will be collected using online survey forms distributed to students who provide informed consent.
The study employs a range of validated assessment tools including the Smartphone Addiction Scale-Short Form (SAS-SF), Digital Game Addiction Scale for University Students (DGAS-U), International Physical Activity Questionnaire-Short Form (IPAQ-SF), Pittsburgh Sleep Quality Index (PSQI), Perceived Stress Scale (PSS), Multidimensional Fatigue Inventory (MFI-20), Cornell Musculoskeletal Discomfort Questionnaire (CMDQ), and the Numerical Rating Scale (NRS) for pain intensity. Sociodemographic data and screen usage patterns will also be gathered.
Statistical analysis will be conducted using IBM SPSS Statistics (Version 24). Appropriate statistical tests such as correlation analysis, independent samples t-test or Mann-Whitney U test, ANOVA or Kruskal-Wallis test, and multiple regression analysis will be applied to assess relationships and differences among subgroups. Comparisons will be made based on variables such as gender, academic year, screen time, and addiction severity.
This study is expected to reveal important links between digital addiction and decreased physical activity, poor sleep quality, elevated stress levels, fatigue, and increased musculoskeletal pain, particularly in the neck, back, shoulder, elbow, and wrist. It offers a comprehensive evaluation of both psychosocial and physical health outcomes related to digital addiction in physiotherapy students, a population with future responsibilities in musculoskeletal health care.
By highlighting the potential occupational health risks associated with students' digital habits, the study underscores the importance of preventive strategies, including ergonomics education, digital health literacy, and self-care practices. It also contributes uniquely to the literature by addressing how prolonged device use relates to musculoskeletal symptoms and by examining how daily step counts and physical activity levels may be influenced by digital addiction. Ultimately, the findings are expected to inform future interventions aimed at promoting healthier digital behaviors and supporting the well-being of students in health-related academic programs.