Artificial intelligence usage mediates the relationship between adverse childhood experiences and mental health outcomes including loneliness, stress, anxiety, suicidal ideation, and depressive symptoms among college students, though the mediating effect proportions are small (2.6–5.4%).
Among college student participants, 794 (29%) reported exposure to adverse childhood experiences (ACEs).
ACEs significantly increased loneliness, with AI usage mediating a small portion of this effect.
ACEs significantly increased stress symptoms, with AI usage mediating a small portion of this effect.
ACEs significantly increased anxiety symptoms, with AI usage mediating a small portion of this effect.
ACEs significantly increased suicidal ideation, with AI usage mediating a small portion of this effect.
ACEs significantly increased depressive symptoms, with AI usage mediating a small portion of this effect.
The greater the number of ACEs one has, the more pronounced the subsequent mental health issues become.
Social AI was identified as having a critical mediating role in mental health outcomes among ACE-affected individuals.
This research suggests that college students who experienced adverse childhood experiences (ACEs) — such as abuse, neglect, or household dysfunction during childhood — are at significantly greater risk for a range of mental health problems, including loneliness, stress, anxiety, thoughts of suicide, and depression. The study, conducted in spring 2025, surveyed college students and found that about 29% had experienced at least one ACE. Importantly, the researchers examined whether artificial intelligence use played any role in the pathway between childhood adversity and these mental health outcomes. The findings suggest that AI usage acts as a small but statistically significant mediator between ACEs and all five mental health outcomes studied. In other words, part of the reason ACEs are linked to worse mental health may be explained by differences in how affected individuals engage with AI tools. The mediating proportions were modest, ranging from about 2.6% for suicidal ideation to 5.4% for depressive symptoms, meaning that AI exposure accounts for a small but detectable share of the total effect of ACEs on mental health. This research matters because it highlights a potentially novel pathway through which technology — specifically AI — intersects with the long-term consequences of childhood trauma. As AI becomes more embedded in daily life, understanding how its use relates to mental health in vulnerable populations like ACE-affected individuals could inform how AI tools are designed or integrated into mental health support systems. The study relied on self-reported questionnaire data and used advanced statistical techniques (propensity score matching and causal mediation analysis) to try to account for confounding factors.
Wang Y, Lv M, Huang R, Zhang J, Huang X, Yu Y, et al.. (2026). Mediation role of artificial intelligence exposure in adverse childhood experiences: related mental health risks among college students.. Scientific reports. https://doi.org/10.1038/s41598-026-37352-x