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<p>Sleep disturbance frequently co-occurs with problematic mobile phone use (PMPU), yet evidence regarding their bidirectional relationship is inconsistent. One explanation is that specific symptoms within each construct may show distinct cross-links, which have rarely been examined. This study used network analysis to explore symptom-level associations between sleep disturbance and PMPU. Two network models, based on different samples and measures, were constructed to assess replicability. In the first model, daytime dysfunction emerged as the most influential bridge symptom, strongly connecting with loss of control and negative consequences—core aspects of PMPU. In contrast, the second model revealed a broader pattern, with withdrawal and nomophobia linking to multiple sleep symptoms. These findings highlight daytime dysfunction, uncontrollable smartphone use, and concrete sleep problems as key to understanding the sleep–PMPU relationship. Future work should incorporate these symptoms into assessment tools to enhance measurement precision and the reliability of research outcomes.</p>

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Cross-Sample Validation of Symptom-Level Links Between Sleep Disturbance and Problematic Mobile Phone Use Using Network Analysis

  • 期刊论文

  • 发表日期：

    2026年1月29日

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  • Yidan Yuan,
  • Manyuan Li,
  • Man Li,
  • Tour Liu

摘要

Sleep disturbance frequently co-occurs with problematic mobile phone use (PMPU), yet evidence regarding their bidirectional relationship is inconsistent. One explanation is that specific symptoms within each construct may show distinct cross-links, which have rarely been examined. This study used network analysis to explore symptom-level associations between sleep disturbance and PMPU. Two network models, based on different samples and measures, were constructed to assess replicability. In the first model, daytime dysfunction emerged as the most influential bridge symptom, strongly connecting with loss of control and negative consequences—core aspects of PMPU. In contrast, the second model revealed a broader pattern, with withdrawal and nomophobia linking to multiple sleep symptoms. These findings highlight daytime dysfunction, uncontrollable smartphone use, and concrete sleep problems as key to understanding the sleep–PMPU relationship. Future work should incorporate these symptoms into assessment tools to enhance measurement precision and the reliability of research outcomes.