利用机器学习分析大学生心理健康问题

Ankita Satapathy, Saumendra Pattnaik, Sangappa Ramachandra Biradar, Saurav Kumar
{"title":"利用机器学习分析大学生心理健康问题","authors":"Ankita Satapathy, Saumendra Pattnaik, Sangappa Ramachandra Biradar, Saurav Kumar","doi":"10.47893/ijcct.2023.1449","DOIUrl":null,"url":null,"abstract":"Currently, mental health concerns pose a significant issue in Odisha. Generally, mental health problems affect a person's thoughts, feelings, actions, and communication. As per the 2017 National Health and Morbidity Survey (NHMS), one in five individuals in Odisha suffer from depression, two have anxiety, and one out of ten experiences stress. Additionally, students in higher education are at an elevated risk of developing mental health problems. However, helping a person with mental health concerns can be challenging due to difficulties in identifying the root causes of their condition. The main objectives of this study are to: 1. Explore mental health issues among higher education students. 2. Investigate the factors that contribute to these issues. 3. Assess the effectiveness of machine learning techniques in analyzing and predicting mental health problems among higher education students. Using computational modeling, this paper's findings will contribute to the ongoing discussion on mental health concerns in future research.","PeriodicalId":220394,"journal":{"name":"International Journal of Computer and Communication Technology","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Mental Health Problems Among Higher Education Students using Machine Learning\",\"authors\":\"Ankita Satapathy, Saumendra Pattnaik, Sangappa Ramachandra Biradar, Saurav Kumar\",\"doi\":\"10.47893/ijcct.2023.1449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, mental health concerns pose a significant issue in Odisha. Generally, mental health problems affect a person's thoughts, feelings, actions, and communication. As per the 2017 National Health and Morbidity Survey (NHMS), one in five individuals in Odisha suffer from depression, two have anxiety, and one out of ten experiences stress. Additionally, students in higher education are at an elevated risk of developing mental health problems. However, helping a person with mental health concerns can be challenging due to difficulties in identifying the root causes of their condition. The main objectives of this study are to: 1. Explore mental health issues among higher education students. 2. Investigate the factors that contribute to these issues. 3. Assess the effectiveness of machine learning techniques in analyzing and predicting mental health problems among higher education students. Using computational modeling, this paper's findings will contribute to the ongoing discussion on mental health concerns in future research.\",\"PeriodicalId\":220394,\"journal\":{\"name\":\"International Journal of Computer and Communication Technology\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47893/ijcct.2023.1449\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47893/ijcct.2023.1449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目前,心理健康问题是奥里萨邦的一个重大问题。一般来说,心理健康问题会影响一个人的思想、感觉、行为和沟通。根据2017年全国健康和发病率调查(NHMS),奥里萨邦五分之一的人患有抑郁症,两人患有焦虑症,十分之一的人有压力。此外,接受高等教育的学生出现心理健康问题的风险较高。然而,由于难以确定其状况的根本原因,帮助有精神健康问题的人可能具有挑战性。本研究的主要目的是:1。探讨高等教育学生的心理健康问题。2. 调查导致这些问题的因素。3.评估机器学习技术在分析和预测高等教育学生心理健康问题方面的有效性。利用计算模型,本文的研究结果将有助于在未来的研究中对心理健康问题的持续讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Mental Health Problems Among Higher Education Students using Machine Learning
Currently, mental health concerns pose a significant issue in Odisha. Generally, mental health problems affect a person's thoughts, feelings, actions, and communication. As per the 2017 National Health and Morbidity Survey (NHMS), one in five individuals in Odisha suffer from depression, two have anxiety, and one out of ten experiences stress. Additionally, students in higher education are at an elevated risk of developing mental health problems. However, helping a person with mental health concerns can be challenging due to difficulties in identifying the root causes of their condition. The main objectives of this study are to: 1. Explore mental health issues among higher education students. 2. Investigate the factors that contribute to these issues. 3. Assess the effectiveness of machine learning techniques in analyzing and predicting mental health problems among higher education students. Using computational modeling, this paper's findings will contribute to the ongoing discussion on mental health concerns in future research.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信