Smartphone addiction, bedtime procrastination, and sleep quality among medical students: an observational study

Medical students, owing to academic pressure and extensive digital device use, are particularly vulnerable to poor sleep quality. As smartphone addiction and bedtime procrastination are increasingly recognized as important behavioral factors influencing sleep, evaluating their interrelationship with sleep quality among Indian medical students may provide insights for developing targeted interventions to promote healthier digital and sleep behaviors. A cross-sectional observational study was conducted among 180 medical students aged 18–25 years at a tertiary care Centre in Greater Noida, India, using a convenience sampling method after obtaining Institutional Ethics Committee approval. Smartphone addiction was assessed using the Smartphone Addiction Scale: Short Version (SAS-SV), sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and bedtime procrastination using the Bedtime Procrastination Scale (BPS). Data was analyzed using SPSS version 28.0. Pearson correlation analysis was performed and p -value < 0.05 was considered statistically significant. The mean global PSQI score was 6.78 ± 2.40 with 72.2% (130/180) indicating poor sleep quality (PSQI > 5) in the majority of participants. Based on the validated SAS-SV cut-off scores (≥ 31 for males and ≥ 33 for females), smartphone addiction was present in 56.5% of males and 40.3% of females. Bedtime procrastination showed no significant gender difference ( p = 0.976). Smartphone addiction correlated strongly with poor sleep quality ( r = 0.66, p < 0.01) and moderately with bedtime procrastination ( r = 0.56, p < 0.01). Bedtime procrastination was also moderately associated with poor sleep quality ( r = 0.52, p < 0.01). Multiple linear regression analysis demonstrated that higher smartphone addiction (β = 0.54, p < 0.001) and bedtime procrastination (β = 0.21, p = 0.002) were significant independent predictors of poor sleep quality, whereas age and sex were not significant predictors. Early identification and targeted interventions focusing on digital hygiene and sleep education are essential to improve sleep health and overall well-being in this population. Not applicable.