Multidimensional analysis of smartphone overuse in insomnia: Integrating digital phenotyping with clinical assessment

초록

AbstractBackground and aimsThis study aimed to identify the differences in characteristics between high- and low-risk smartphone users among individuals with insomnia symptoms using digital phenotyping and clinical assessments.MethodsA total of 246 participants with insomnia symptoms (M = 31.14, SD = 10.09) were monitored for four weeks using the smartphone application and wearable devices. The participants were divided into high-(n = 141) and low-risk (n = 105) smartphone overuse groups based on a Smartphone Overuse Screening Questionnaire. Clinical scale results and wearable data were analyzed using ANCOVA and logistic regression, controlling for age, sex, and BMI.ResultsAfter covariate adjustment, the high-risk group showed significantly greater biological rhythm disruption (K-BRIAN: LS-mean difference = 6.86, p < 0.000), more severe insomnia (ISI index: aOR: 2.63, p = 0.0005), and poorer sleep quality (PSQI-K: aOR: 2.41, p = 0.0015). Psychological distress, including depression (PHQ-9 index: aOR: 2.77, p = 0.0001) and anxiety (GAD-7 index: aOR: 1.59, p = 0.0059), was more pronounced in the high-risk group. Bedtime procrastination (BPS index: aOR: 1.96, p = 0.0173) and stress reactivity to insomnia (FIRST index: aOR: 1.67, p = 0.0574) were significantly elevated. Digital phenotyping revealed persistent differences in minimum daytime heart rate and exercise intensity patterns, while many activity-related measures lost significance after adjustment.Discussion and conclusionsSmartphone overuse is independently associated with severe circadian disruption, insomnia, and psychological distress. The integrated assessment approach revealed critical biomarkers and behavioral patterns. Targeted interventions focused on circadian stabilization and behavioral sleep patterns may improve sleep quality and mental health outcomes in this population. Longitudinal research is needed to establish causality. © 2025 The Author(s). Open Access statement. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

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