Shiming, Ivy HUANG

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Research Topic: Research on Negative Bias Modification among Greater Bay Area youth: Design and Applications

Depression and anxiety are crucial public health issues, and the identification of effective intervention is globally imperative. While the efficacy of interpretation bias modification (CBM-I) in preventing and reducing depression has been indicated, the evidence of the effects is debatable. It is particularly unclear from the aspects of its long term effects and conducting CBM-I over the internet. With the increasing awareness of the challenged of existing CBM-Is such as insufficient incentives, and dysfunction within depressed individuals to engage in the training materials and the workload to tailor them. My study aims to develop and test a variant of CBM-I with AI Robot and enable it as a long-term support for the depressed youth. My study is the first to incorporate robot aids in interpretation bias modification. The AI-enhanced implementation during intervention and material preparation would provide insights into the AI-assisted mental therapy. In addition, given little research on CBM-I for the Chinese, especially under multi-session interventions, our study targeted at Chinese people can provide promising adaptability in the social context of China.

Key publication:

Hoorn, J. F., Huang, I. S., Konijn, E. A., & van Buuren, L. (2021). Robot tutoring of multiplication: Over one-third learning gain for most, learning loss for some. Robotics, 10(1), 16. https://doi.org/10.3390/robotics10010016

Huang, I. S., & Hoorn, J. F. (2018). Having an einstein in class - teaching maths with robots is different for boys and girls. 2018 13th World Congress on Intelligent Control and Automation (WCICA). https://doi.org/10.1109/wcica.2018.8630584

Huang, S. I., & Hoorn, J. F. (2021). Does the robot show empathy with me? Talking vs. musical robot. Proceedings of the 9th Congress of the International Association of Societies of Design Research (IASDR ’21)

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