[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126686-en":3,"doc-seo-126686-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},126686,962084925502,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",8,"Research & Report","Analysis of Mental Health Problems Among Higher Education Students using Machine Learning","Study focuses on mental health concerns affecting higher education students, where difficulties in identifying root causes hinder timely support. It highlights Odisha’s burden using NHMS 2017 indicators: depression affects one in five, anxiety affects two, and stress affects one out of ten. The paper explores prevalent mental health issues, examines contributing factors, and evaluates machine learning methods for analyzing and predicting mental health problems among students, supporting future research directions.","International Journal of Computer and Communication Technology  \n\n| Volume 9  Issue 2 | Article 1 |\n| --- | --- |\n| August 2023\u003Cbr>Analysis of Mental Health Problems Among Higher Education Students using Machine Learning\u003Cbr>Ankita Satapathy\u003Cbr>Utkal University, [ankitasatapathy2@gmail.com](ankitasatapathy2@gmail.com)\u003Cbr>Saumendra Pattnaik\u003Cbr>Siksha 'o' Anusandhan University, [saumendrapattnaik@soa.ac.in](saumendrapattnaik@soa.ac.in)\u003Cbr>Sangappa Ramachandra Biradar\u003Cbr>SDM College of Engineering & Technology, [srbiradar@gmail.com](srbiradar@gmail.com)\u003Cbr>Saurav Kumar\u003Cbr>Siksha 'O' Anusandhan University, [sauravkumar@soa.ac.in](sauravkumar@soa.ac.in)\u003Cbr>Follow this and additional works at: [https://www.interscience.in/ijcct](https://www.interscience.in/ijcct)\u003Cbr> Part of the Communication Sciences and Disorders Commons, Engineering Commons, and the Health and Medical Administration Commons |  |\n\nRecommended Citation  \nSatapathy, Ankita; Pattnaik, Saumendra; Biradar, Sangappa Ramachandra; and Kumar, Saurav (2023)\"Analysis of Mental Health Problems Among Higher Education Students using Machine Learning,\"International Journal of Computer and Communication Technology: Vol. 9: Iss. 2, Article 1.  \nDOI: 10.47893/IJCCT.2023.1449  \nAvailable at: [https://www.interscience.in/ijcct/vol9/iss2/1](https://www.interscience.in/ijcct/vol9/iss2/1)  \nThis Article is brought to you for free and open access by the Interscience Journals at Interscience Research Network. It has been accepted for inclusion in International Journal of Computer and Communication Technology by an authorized editor of Interscience Research Network. For more information, please contact [sritampatnaik@gmail.com](sritampatnaik@gmail.com).  \nAnalysis of Mental Health Problems Among Higher Education Students using Machine  \nLearning  \nAnkita Satapathy1, SaumendraPattnaik2, Sangappa Ramachandra Biradar3*, Saurav Kumar4  \n1P. G. Department of Statistics, Utkal University, Vani Vihar, Bhubaneswar, Odisha, [India](India ankitasatapathy2@gmail.com)[ ankitasatapathy2@gmail.com](India ankitasatapathy2@gmail.com)  \n[2](2),[4](4)Department of Computer Science & Engineering, ITER, Siksha ‘O’Anusandhan University, Bhubaneswar, Odisha, India [saumendrapattnaik@soa.ac.in](saumendrapattnaik@soa.ac.in), [sauravkumar@soa.ac.in](sauravkumar@soa.ac.in)  \n3*Department of Information Science & Engineering, SDM College of Engineering & Technology, Dharwad, Karnataka, India  \n[srbiradar@gmail.com](srbiradar@gmail.com)  \nAbstract—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.  \nKeywords—mental health problems, NHMS, higher education, analyzing, predicting  \nI. INTRODUCTION  \nMental illness is a health issue that unquestionably affects a person's emotions, reasoning, and social interactions. These issues have demonstrated that mental illness has severe repercussions across societies and necessitates new prevention and intervention strategies. For these objectives, early detection of mental illness is a crucial procedure. 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