Wang Ting, Seiger Anja, Markowetz Alexander, Andone Ionut, Błaszkiewicz Konrad, Penzel Thomas
Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Department of Computer Science, University of Bonn, Bonn, Germany.
J Med Internet Res. 2025 Jul 3;27:e60423. doi: 10.2196/60423.
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.
This study aimed to investigate demographic differences and relationships between daily smartphone usage and nocturnal smartphone inactivity patterns.
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.
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.
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.
尽管先前的研究已经探讨了智能手机使用与睡眠障碍之间的关系,但关于智能手机使用的人口统计学差异以及夜间智能手机不活动模式的研究仍然有限。本研究引入“夜间智能手机不活动时长”作为替代指标,以解决缺乏直接睡眠数据的局限性,并进一步调查智能手机使用模式与睡眠特征之间的关联。
本研究旨在调查人口统计学差异以及日常智能手机使用与夜间智能手机不活动模式之间的关系。
我们对2022年1月1日至2022年12月31日从Murmuras应用程序收集的数据进行了回顾性分析。共纳入1074名参与者,按性别、年龄、最高学历、就业状况和智能手机使用目的进行分类。所有参与者均通过该应用程序同意参与本研究。为了探索智能手机使用与夜间智能手机不活动之间的关系,我们首先计算了每位参与者的每日智能手机使用时长(包括应用程序使用)和夜间智能手机不活动时长;然后,我们评估了每个人口统计类别内方差检验的正态性和同质性。根据结果,应用Kruskal-Wallis检验来潜在地识别组间差异。最后,进行相关性和回归分析以探索智能手机使用与夜间智能手机不活动之间的关联。
研究结果揭示了不同人口统计学特征的智能手机使用模式存在差异。参与者主要通过Facebook和YouTube等应用程序将智能手机用于社交联系(平均每日使用时长=1.52小时)和娱乐活动(平均每日使用时长=1.08小时)。频繁使用者,尤其是社交媒体和娱乐应用的使用者,经常在夜间增加手机使用量。女性参与者使用手机更频繁,主要用于数字购物和社交互动,而男性参与者在夜间使用手机更多(P<0.001)。年轻用户和非全职员工都更多地参与游戏和聊天等活动(这些比较的P<0.01)。高等教育与较低的手机使用量相关(P<0.001)。那些将智能手机用于工作相关目的的人通常在下班后减少手机使用量(这些比较的P<0.05)。对各组智能手机使用时长和夜间不活动情况的相关性和回归分析表明,只有一小部分组呈现出显著的正相关,中等数量的组呈现出显著的负相关,而大多数组没有显著相关性。
本研究强调了人口统计学因素与智能手机使用模式(包括夜间不活动模式)之间的显著关联。女性、年轻人、教育程度较低的人和失业者的智能手机使用量较高。在夜间,频繁使用社交媒体和休闲应用程序的情况尤为明显,这种行为可能会导致睡眠模式紊乱。这些发现强调了需要针对性地干预过度使用智能手机的情况,尤其是在夜间,以减轻其对睡眠的潜在不利影响。