{"title":"大学生的心理健康状况及影响因素","authors":"Liangqun Yang","doi":"10.4018/ijfsa.334233","DOIUrl":null,"url":null,"abstract":"This study aims to address the mental health challenges brought about by the diversified development and rapid changes in society, with special attention to the psychological status of the student population. By using the SCL-90 mental health testing tool, collecting students' mental health data, and applying the fuzzy comprehensive evaluation method to analyze and evaluate students' mental health and its influencing factors in depth, the study aims to provide more effective countermeasures for students' mental health education as well as targeted teaching assistance for teachers. This study combines the BP neural network prediction model, which is committed to improving the accurate prediction of students' mental health status. The results of the study will help to assess the mental health level of students, detect and intervene in psychological crises in a timely manner, provide schools with more comprehensive mental health management and services, and promote the overall healthy growth of students.","PeriodicalId":38154,"journal":{"name":"International Journal of Fuzzy System Applications","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mental Health Status and Influencing Factors of College Students\",\"authors\":\"Liangqun Yang\",\"doi\":\"10.4018/ijfsa.334233\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to address the mental health challenges brought about by the diversified development and rapid changes in society, with special attention to the psychological status of the student population. By using the SCL-90 mental health testing tool, collecting students' mental health data, and applying the fuzzy comprehensive evaluation method to analyze and evaluate students' mental health and its influencing factors in depth, the study aims to provide more effective countermeasures for students' mental health education as well as targeted teaching assistance for teachers. This study combines the BP neural network prediction model, which is committed to improving the accurate prediction of students' mental health status. The results of the study will help to assess the mental health level of students, detect and intervene in psychological crises in a timely manner, provide schools with more comprehensive mental health management and services, and promote the overall healthy growth of students.\",\"PeriodicalId\":38154,\"journal\":{\"name\":\"International Journal of Fuzzy System Applications\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fuzzy System Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijfsa.334233\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy System Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijfsa.334233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
摘要
本研究旨在应对社会多元化发展和快速变化带来的心理健康挑战,特别关注学生群体的心理状况。通过使用 SCL-90 心理健康测试工具,收集学生的心理健康数据,运用模糊综合评价法对学生的心理健康及其影响因素进行深入分析和评价,为学生的心理健康教育提供更有效的对策,也为教师的教学提供有针对性的帮助。本研究结合 BP 神经网络预测模型,致力于提高对学生心理健康状况的准确预测。研究结果将有助于评估学生的心理健康水平,及时发现和干预心理危机,为学校提供更全面的心理健康管理和服务,促进学生全面健康成长。
Mental Health Status and Influencing Factors of College Students
This study aims to address the mental health challenges brought about by the diversified development and rapid changes in society, with special attention to the psychological status of the student population. By using the SCL-90 mental health testing tool, collecting students' mental health data, and applying the fuzzy comprehensive evaluation method to analyze and evaluate students' mental health and its influencing factors in depth, the study aims to provide more effective countermeasures for students' mental health education as well as targeted teaching assistance for teachers. This study combines the BP neural network prediction model, which is committed to improving the accurate prediction of students' mental health status. The results of the study will help to assess the mental health level of students, detect and intervene in psychological crises in a timely manner, provide schools with more comprehensive mental health management and services, and promote the overall healthy growth of students.