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<p>Adverse childhood experiences (ACEs) pose significant mental health risks, and the greater the number of ACEs one has, the more pronounced the subsequent mental health issues become. In today’s world, the widespread application of artificial intelligence raises questions about its role in mediating the impact of ACEs on mental health, which remains unclear. Data were collected through questionnaire surveys from April to May 2025. Participants’ psychosocial characteristics were assessed using validated scales measuring stress, anxiety, depression, ACEs status, loneliness, sleep quality, and suicidal ideation. Data analysis incorporated propensity score matching and causal mediation analysis. Among participants, 794 (29%) reported ACE exposure. ACEs significantly impact loneliness, stress, anxiety, suicidal ideation, and depressive symptoms, with mediation of AI usage. Specifically, the total effect on loneliness is 0.24 (95% CI 0.18–0.31; <i>P</i> &lt; 0.001), with a mediating effect proportion of 5.2%; the total effect on stress is 0.71 (95% CI 0.56–0.88; <i>P</i> &lt; 0.001), with a mediating effect proportion of 4.4%; the total effect on anxiety symptoms is 0.65 (95% CI 0.51–0.81; <i>P</i> &lt; 0.001), with a mediating effect proportion of 4.9%; the total effect on suicidal ideation is 0.07 (95% CI 0.06–0.09; <i>P</i> &lt; 0.001), with a mediating effect proportion of 2.6%; and the total effect on depressive symptoms is 0.60 (95% CI 0.46–0.76; <i>P</i> &lt; 0.001), with a mediating effect proportion of 5.4%. Findings highlight the critical mediating role of social AI in mental health outcomes among ACE-affected individuals.</p>

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Mediation role of artificial intelligence exposure in adverse childhood experiences: related mental health risks among college students

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月27日

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  • Yuanyi Wang,
  • Mingxuan Lv,
  • Rong Huang,
  • Jinyan Zhang,
  • Xinfang Huang,
  • Yidi Yu,
  • Man Luo,
  • Zhizhou Duan,
  • Wenqun Luo

摘要

Adverse childhood experiences (ACEs) pose significant mental health risks, and the greater the number of ACEs one has, the more pronounced the subsequent mental health issues become. In today’s world, the widespread application of artificial intelligence raises questions about its role in mediating the impact of ACEs on mental health, which remains unclear. Data were collected through questionnaire surveys from April to May 2025. Participants’ psychosocial characteristics were assessed using validated scales measuring stress, anxiety, depression, ACEs status, loneliness, sleep quality, and suicidal ideation. Data analysis incorporated propensity score matching and causal mediation analysis. Among participants, 794 (29%) reported ACE exposure. ACEs significantly impact loneliness, stress, anxiety, suicidal ideation, and depressive symptoms, with mediation of AI usage. Specifically, the total effect on loneliness is 0.24 (95% CI 0.18–0.31; P < 0.001), with a mediating effect proportion of 5.2%; the total effect on stress is 0.71 (95% CI 0.56–0.88; P < 0.001), with a mediating effect proportion of 4.4%; the total effect on anxiety symptoms is 0.65 (95% CI 0.51–0.81; P < 0.001), with a mediating effect proportion of 4.9%; the total effect on suicidal ideation is 0.07 (95% CI 0.06–0.09; P < 0.001), with a mediating effect proportion of 2.6%; and the total effect on depressive symptoms is 0.60 (95% CI 0.46–0.76; P < 0.001), with a mediating effect proportion of 5.4%. Findings highlight the critical mediating role of social AI in mental health outcomes among ACE-affected individuals.