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<p>This study was to examine distinct latent profiles of smartphone addiction among university students. Moreover, it elucidates how these profiles correlate to differences in important health outcomes like sleep quality, physical activity and depression. A total of 2,361 Chinese university students completed validated questionnaires Distinct groups was identified by latent profile analysis, while the Bolck-Croon-Hagenaars method assessed differences in health outcomes across these groups. Three profiles were identified: regular, low and high smartphone addiction. Compared to the regular group, the high addiction group is significantly associated with poorer sleep quality (<i>M</i> = 6.10 vs. 2.92, χ2 = 322.89, <i>p</i> &lt; 0.001), lower physical activity (<i>M</i> = 2.02 vs. 2.36, χ2 = 55.27, <i>p</i> &lt; 0.001), and higher depression (<i>M</i> = 6.39 vs. 1.29, χ2 = 362.32, <i>p</i> &lt; 0.001). Smartphone addiction is not a uniform condition; rather, it has various profiles associated with different health outcomes. These findings indicate the efficacy of employing person-centered approaches to identify subgroups, which can support designing targeted interventions aimed at encouraging healthier digital habits.</p>

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Associations between smartphone addiction profiles and health outcomes among university students: A latent profile analysis

  • 期刊论文

  • 发表日期：

    2026年6月26日

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  • He Sun,
  • Weiyan Yan,
  • Zhoujie Zeng,
  • Ke Zhou,
  • Gaoxia Wei

摘要

This study was to examine distinct latent profiles of smartphone addiction among university students. Moreover, it elucidates how these profiles correlate to differences in important health outcomes like sleep quality, physical activity and depression. A total of 2,361 Chinese university students completed validated questionnaires Distinct groups was identified by latent profile analysis, while the Bolck-Croon-Hagenaars method assessed differences in health outcomes across these groups. Three profiles were identified: regular, low and high smartphone addiction. Compared to the regular group, the high addiction group is significantly associated with poorer sleep quality (M = 6.10 vs. 2.92, χ2 = 322.89, p < 0.001), lower physical activity (M = 2.02 vs. 2.36, χ2 = 55.27, p < 0.001), and higher depression (M = 6.39 vs. 1.29, χ2 = 362.32, p < 0.001). Smartphone addiction is not a uniform condition; rather, it has various profiles associated with different health outcomes. These findings indicate the efficacy of employing person-centered approaches to identify subgroups, which can support designing targeted interventions aimed at encouraging healthier digital habits.