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Hirosawa, T., Harada, Y., Yokose, M., Sakamoto, T., Kawamura, R., & Shimizu, T. (2023). Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints: A Pilot Study. International Journal of Environmental Research and Public Health, 20, Article No. 3378. https://doi.org/10.3390/ijerph20043378

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• TITLE: Revolutionizing Peer Support for Children with Chronic Illness Leveraging Technology

  AUTHORS: Mahima Gyamlani

  KEYWORDS: Mental Health, Chronic Illness, Digital Mental Health Intervention, Artificial Intelligence, Peer Support, Children, Starfly

  JOURNAL NAME: Psychology, Vol.14 No.10, October 24, 2023

  ABSTRACT: Children with chronic health conditions face an increased risk for mental health issues compared to their healthy peers. These mental health conditions can negatively impact disease management and medical outcomes. Digital mental health interventions (DMHIs), such as computerized Cognitive Behavioral Therapy and conversational AI, may help address this need. This paper describes an in-progress DMHI using generative AI called Starfly. Starfly connects children with chronic illness with peers to facilitate positive interactions without stigma. The app offers a secure platform for social support and community building among young people managing chronic illness. By leveraging AI and thoughtful design, Starfly aims to promote mental well-being and improve disease outcomes in this vulnerable population.