发表机构
Ghazi University（加齐大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对巴基斯坦大学生，提出基于随机森林（准确率89.09%）和文化感知大语言模型聊天机器人的压力检测与健康支持系统，识别关键压力因素。
AI 中文摘要
现有的数字心理健康工具主要针对西方环境开发，而巴基斯坦学生面临着由学业、经济、家庭和人际关系等压力源组成的独特且复合的大学压力情境，这已成为影响巴基斯坦大学生学业和心理发展的严重问题。本文介绍了一种新的、由人工智能驱动且具有文化敏感性的压力检测与健康支持系统，专门针对巴基斯坦大学生的情境量身定制。该系统基于一种名为随机森林的机器学习模型，该模型使用一个经过验证的学生压力数据集进行训练，该数据集包含 1100 份响应，涵盖心理、生理、学业、环境和社会等 20 个特征，在三个压力严重程度级别上达到了 89.09% 的准确率和 0.89 的宏 F1 分数。分类输出通过 OpenRouter API 传递给一个开源大语言模型，其中经过精心设计的、具有文化感知的系统提示词使模型能够以英语、乌尔都语和罗马乌尔都语进行关于健康的对话。通过特征重要性分析，该人群中预测力第二强的压力因素是师生关系，这是一个具有文化重要性的压力因素，凸显了区域感知心理健康系统的必要性。未来研究将涉及使用经过验证的 DASS-21 工具，从巴基斯坦大学不同学业阶段的学生（特别是从 FSc 过渡到本科阶段的学生，这一阶段在心理上较为脆弱且研究不足）中收集原始数据。
英文摘要
With the existing digital mental health tools specifically developed for Western settings, Pakistani students are exposed to a uniquely compounded stress situation in their university that includes academic, financial, familial, and relational stressors, which have become a serious concern for academic and psychological development of students in Pakistani universities. This paper introduces a new, AI-driven and culturally sensitive stress detection and wellness support system that is tailored to the context of Pakistani university students. The system is based on a machine learning model called Random Forest which is trained using a validated student stress data set of 1100 responses on 20 features from psychological, physiological, academic, environmental and social aspects, with an accuracy of 89.09% and a macro F1-score of 0.89, in three stress severity levels. The classification outputs are passed on to an open-source large language model through OpenRouter API, where an appropriately crafted system prompt, culturally aware, gives the model a conversation about wellness, in English, Urdu and Roman Urdu. The second most predictive stress factor in this population identified by feature importance analysis was teacher-student relationship, which is a culturally important stress factor highlighting the need for region-aware mental health systems. Future research will involve primary data collection from students at various academic levels of Pakistani Universities with the validated DASS-21 instrument focusing on the students who are moving from FSc to undergraduate studies, which is a time of being psychologically vulnerable which is under-researched.
