Key points are not available for this paper at this time.
Adolescents face much psychological stress in the current social environment, and effective emotional regulation is crucial to their mental health. This article introduces a paradigm of product-oriented psychological dialogue, that is, to study psychological problems first, determine user needs and the most effective way of action, and then develop tools based on this paradigm. We use the above paradigm to build an artificial intelligence-based adolescent emotion adjust the con-versational bot. Specifically, to explore adolescents' emotional regulation needs, this study collected the required data (n=317, 5,543 questionnaires) through the intensive tracking method. It revealed the mechanism of user needs and emotion regulation. Emotion regulation strategy weighting mechanism, and using the collected raw data and existing emotion support dialogue datasets (ESConv), a Chinese adolescent emotion regulation dia-logue dataset was constructed. After that, this paper fine-tunes the existing dialogue model (GPT-2 chitchat). Through these improvements, the dialogue model has dramatically improved its performance and can also provide more personalized and effective emotional regulation support according to the actual needs of adolescents. In summary, this study provides new ideas and methods for mental health support, and promotes the research and development of emotional regulation support for adolescents.
Ni et al. (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: