Identification and Ranking of Digital Lifestyle Components in the Formation of Sleep Disorders - Seyed Ebrahimi, Seyed Alireza; Momeni Fini, Seyed Mohammadjavad (Mental Health and Lifestyle Journal, 2024)
This study aimed to identify and rank the key components of digital lifestyle that contribute to the development of sleep disorders. This research employed a sequential exploratory mixed-methods design. In the qualitative phase, data were collected exclusively through a comprehensive literature review of peer-reviewed articles, academic reports, and authoritative scientific sources related to digital behavior and sleep health. The extracted data were coded and analyzed using NVivo 14 until theoretical saturation was achieved. In the quantitative phase, a structured questionnaire derived from the qualitative results was administered to 200 participants residing in Tehran. A five-point Likert scale measured the perceived influence of each identified component on sleep disturbance. Data analysis was conducted using SPSS-26, applying descriptive statistics and the Friedman test to rank digital lifestyle components. The Friedman analysis revealed significant differences in the influence of the seven identified components on sleep disorders (p < .05). Digital Engagement Intensity received the highest ranking (M = 4.52), followed by Sleep Hygiene Disruption (M = 4.41) and Physiological Arousal (M = 4.38). Mid-level components included Emotional and Psychological Factors (M = 4.29) and Behavioral Lifestyle Patterns (M = 4.17). Lower-ranked components were Social–Digital Interaction (M = 4.05) and Digital Content Exposure (M = 3.98). These results indicate that behavioral and physiological digital mechanisms exert stronger influences on sleep disturbance than content-related factors. Digital lifestyle significantly contributes to sleep disturbance through behavioral, psychological, physiological, and environmental pathways. The study highlights that high engagement intensity, poor digital–sleep boundaries, and digital-induced physiological arousal are the most critical predictors of sleep disorders. These findings provide a structured framework for designing preventive strategies, digital-wellness programs, and sleep-health interventions tailored to high-risk populations.