ASSESSING SCREEN TIME ADDICTION AND ITS IMPACT ON SLEEP QUALITY AMONG NURSING STUDENTS: A CROSS-SECTIONAL STUDY DESIGN

Abstract

Background: Modern lifestyle factors, irregular work hours, and daily cognitive burdens heavily influence sleep quality. Poor sleep hygiene is linked to decreased productivity, daytime fatigue, and long-term health complications. Understanding the precise components of sleep disruption in specific demographics is essential for designing targeted wellness interventions. Objective: This study aims to evaluate the prevalence of sleep disturbances, assess overall sleep quality, and identify common qualitative factors contributing to sleep disruptions among a surveyed cohort. Method: A cross-sectional survey design was utilised to collect data from a sample extrapolated to N=150 participants. Demographic information (age, gender) and behavioural data (such as frequency of specific daily routines) were collected alongside standard measures of sleep habits (bedtime, sleep latency, sleep efficiency, and frequency of night-time awakenings). Qualitative data regarding specific sleep struggles (e.g., racing thoughts, work- related stress, and physiological restlessness) were also recorded and categorised. Results: “Descriptive and Inferential statistical analysis revealed a high prevalence of problematic technology use and its profound threat to sleep hygiene among the sample population (N=150). Reliability analysis demonstrated robust internal consistency for the behavioural measurement scale (Cronbach’s α = 0.842). Pearson correlation and multiple regression models indicated a statistically significant, strong positive relationship between elevated screen time addiction scores and poor subjective sleep quality (p < .001). Mediation analysis utilizing Hayes’ PROCESS Model 4 further confirmed that severe digital addiction directly drives sleep architecture disruption, while simultaneously operating through an indirect pathway that exacerbates secondary sleep disorders. Ultimately, severe screen dependency was shown to significantly predict prolonged sleep- onset latency, reduced total sleep duration, and acute daytime dysfunction”. Conclusion: Sleep disturbances and sub- optimal sleep quality are highly prevalent within the studied population, largely driven by a combination of bedtime cognitive arousal (racing thoughts) and lifestyle- induced stress. The findings highlight an urgent need for targeted sleep hygiene education and stress- management interventions to improve overall sleep health and mitigate daytime fatigue.