Abstract
BACKGROUND: Although previous studies have examined the relationship between smartphone usage and sleep disorders, research on demographic differences in smartphone usage and nocturnal smartphone inactivity patterns remains limited. This study introduces "nocturnal smartphone inactivity duration" as a proxy indicator to address the limitation of lacking direct sleep data and to further investigate the association between smartphone usage patterns and sleep characteristics. OBJECTIVE: This study aimed to investigate demographic differences and relationships between daily smartphone usage and nocturnal smartphone inactivity patterns. METHODS: We conducted a retrospective analysis of data collected from the Murmuras app from January 1, 2022, to December 31, 2022. A total of 1074 participants were included, categorized by gender, age, highest degree, employment status, and smartphone usage purpose. All participants consented to participate in the study through the app. To explore the relationship between smartphone usage and nocturnal smartphone inactivity, we first calculated each participant's daily smartphone usage duration (including app usage) and duration of nocturnal smartphone inactivity; then, we assessed the normality and homogeneity of variance tests within each demographic category. Based on the results, the Kruskal-Wallis tests were applied to potentially identify differences between groups. Finally, correlation and regression analyses were conducted to explore associations between smartphone usage and nocturnal smartphone inactivity. RESULTS: The findings revealed distinct patterns of smartphone use across demographics. Participants predominantly used smartphones for social contact (average daily usage duration=1.52 h) and recreational activities (average daily usage duration=1.08 h) through apps like Facebook and YouTube. Frequent users, especially of social media and entertainment, often increased their phone usage at night. Female participants used their phones more frequently, mainly for digital shopping and social interactions, whereas male participants used phones more at nighttime (P<.001). Both younger users and non-full-time employees engaged more in activities such as gaming and chatting (P<.01 for those comparisons). Higher education was correlated with lower use (P<.001). Those using smartphones for work-related purposes generally decreased their phone usage after work (P<.05 for those comparisons). Correlation and regression analyses of smartphone usage duration and nighttime inactivity across groups indicated that only a small subset of groups exhibited significant positive correlations, a moderate number displayed significant negative correlations, and the majority showed no significant correlation. CONCLUSIONS: This study underscores the significant association between demographic factors and smartphone usage patterns, including nocturnal inactivity patterns. Female individuals, young people, individuals with lower educational qualifications, and those who were unemployed demonstrated higher smartphone usage. Frequent engagement with social media and leisure apps was particularly pronounced during nighttime hours, a behavior that may contribute to disruptions in sleep patterns. These findings underscore the need for targeted interventions addressing excessive smartphone use, particularly at night, to mitigate its potential adverse effects on sleep.