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Introduction: Diagnosis of Attention Deficit/Hyperactivity Disorder (ADHD) is based on clinical evaluation of symptoms by a psychiatrist, referencing results of psychological tests. When diagnosing ADHD, the child's behavior and functionality in real-life situations are critical components. However, direct observation by a clinician is often not feasible in practice. Therefore, such information is typically gathered from primary caregivers or teachers, which can introduce subjective elements. To overcome these limitations, we developed AttnKare-D, an innovative digital diagnostic tool that could analyze children's behavioral data in Virtual Reality using Artificial Intelligence. The purpose of this study was to explore the utility and safety of AttnKare-D for clinical application. Method: A total of 21 children aged between 6 and 12 years were recruited for this study. Among them, 15 were children diagnosed with ADHD, 5 were part of a normal control group, and 1 child was excluded due to withdrawal of consent. Psychological assessments, including K-WISC, Conners CPT, K-ARS, and K-CBCL, were conducted for participants and their primary caregivers. Diagnoses of ADHD were confirmed by child and adolescent psychiatrists based on comprehensive face-to-face evaluations and results of psychological assessments. Participants underwent VR diagnostic assessment by performing various cognitive and behavioral tasks in a VR environment. Collected data were analyzed using an AI model to assess ADHD diagnosis and the severity of symptoms. Results: AttnKare-D demonstrated diagnostic performance with an AUC of 0.893 when compared to diagnoses made by child and adolescent psychiatrist, showing a sensitivity of 0.8 and a specificity of 1.0 at a cut-off score of 18.44. AttnKare-D scores showed a high correlation with K-ARS scores rated by parents and experts, although the correlation was relatively low for inattention scores. Conclusion: Results of this study suggest that AttnKare-D can be a useful tool for diagnosing ADHD in children. This approach has potential to overcome limitations of current diagnostic methods, enhancing the accuracy and objectivity of ADHD diagnoses. This study lays the groundwork for further improvement and research on diagnostic tools integrating VR and AI technologies. For future clinical applications, it is necessary to conduct clinical trials involving a sufficient number of participants to ensure reliable use.
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BACKGROUND: Early life traumatic events and recent stressful events are known to have especially strong effects on emotional wellbeing. However, little is known about the interaction of early and recent stressors on emotions. We aimed to examine the interactive effects of early trauma and recent stressors on depression, anxiety, and anger. METHODS: One hundred and seventy adults were recruited and asked to complete the Center for Epidemiological Studies Depression Scale (CES-D), the state anxiety subscale of the State-Trait Anxiety Inventory (STAI-S), and the state anger subscale of the State-Trait Anger Expression Inventory (STAXI-S). Early traumas and recent stressors were assessed during face-to-face interviews. Multiple regression analysis was performed to test whether early trauma, recent stressors, and the interaction of the two would predict CES-D, STAI-S, and STAXI-S scores. RESULTS: In the multiple regression models, STAI-S scores were predicted only by recent stressors (R2 = 0.063, p = 0.001). In contrast, CES-D and STAXI-S scores were predicted only by the synergistic interaction of early trauma with recent stressors (R2 = 0.075, p < 0.001; R2 = 0.039, p = 0.01, respectively). CONCLUSIONS: A synergistic interaction effect between early trauma and recent stressful events on current depression and anger was observed, indicating that the combined effects of early trauma and recent stressors are stronger than their individual effects. In contrast, anxiety was affected mainly by recent stressors. Our findings suggest that the form that emotional disturbance takes can vary depending on the timing of stressors.
