运用深度学习技术驱动青少年心理健康服务

Utilizing Deep Learning Technology to Propel Adolescent Mental Health Services

目的为解决当前青少年心理健康服务供需失衡和质量良莠不齐等问题,研究应用深度学习技术,实现青少年心理问题早期的智能咨询、筛查、评估及初步干预。方法通过对心理学理论及案例进行解析,构建基于因果关系的认知事理图谱和策略驱动的心理咨询对话大模型,实现自动生成回复、评估和简单干预等。结果经过对随机抽取的100例数据进行测试,表明该模型能够更好地理解和处理心理咨询问题,完成部分筛查、咨询和科普工作。结论本研究验证了深度学习技术在青少年心理健康领域的应用价值,特别是构建的大模型在当前青少年心理服务支持资源不足的情况下,提供了一种可推广、可复制的线上心理服务新模式。

Objective In order to address the existing disparities in the provision of adolescent mental health services and the variability in quality,this study explores the application of deep learning technology to facilitate early intelligent counseling,screening,assessment,and initial intervention for adolescent mental health issues.Methods By analyzing psychological theories and cases,the project will construct a causal knowledge graph and attempt to build a strategy-driven conversational large model for psychological counseling.This model aims to achieve automatic response generation,assessment,and basic intervention.Results After testing 100 random cases,the model demonstrates a better understanding and performance in handling psychological counseling tasks,including screening,counseling,and providing information.Conclusion This research validates the application value of deep learning technology in the field of adolescent mental health.In the current context of inadequate resources for adolescent mental health services,it offers a scalable and replicable online mental health service model.