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

🥉 Top 5% JournalJan 6, 2026Journal of behavioral addictions

Smartphone overuse and insomnia: Combining digital tracking with clinical evaluation

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Abstract

The high-risk smartphone user group exhibited a 6.86 point greater disruption in biological rhythms compared to low-risk users.

High-risk smartphone users showed more severe insomnia, with an odds ratio of 2.63, indicating a strong association.
Poor sleep quality was significantly linked to high-risk users, with an odds ratio of 2.41.
Psychological distress, including depression and anxiety, was more pronounced in the high-risk group, with odds ratios of 2.77 and 1.59, respectively.
Bedtime procrastination was significantly higher in high-risk users, with an odds ratio of 1.96.
Digital phenotyping indicated persistent differences in minimum daytime heart rate and exercise intensity patterns between the two groups.

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BACKGROUND AND AIMS: This 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.

METHODS: A 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.

RESULTS: After 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 CONCLUSIONS: Smartphone 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.

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