[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117902-en":3,"doc-seo-117902-105":30,"detail-sidebar-cat-0-en-105":91},{"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":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117902,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Machine Learning Approches for Prediction of Mental Health Issues in Adolescents - A Comparative Survey","Mental health is a non-communicable condition that can severely affect individuals, and adolescents are particularly vulnerable due to hormonal changes, study and social pressures. Neglecting symptoms in this phase can lead to serious consequences for families and a country’s young workforce. This survey compiles 22 prior studies using machine learning and statistical analysis to early detect high-risk factors and compares model effectiveness across disorder-specific tasks including depression, anxiety, suicidal prevalence, ASD, and substance abuse. Results indicate that CNN, Random Forest, and XGBoost often achieve stronger performance for classification and prediction.","VFAST Transactions on Software Engineering [http://vfast.org/journals/index.php/VTSE@ 2023](http://vfast.org/journals/index.php/VTSE@ 2023), ISSN(e): 2309-3978, ISSN(p): 2411-6246  \nVolume 11, Number 1, January-March 2023 pp: 37-50  \nMachine Learning Approches for Prediction of Mental Health Issues in Adolescents: A Comparative Survey  \nKinza Haroon 1, Sidra Minhas 1, Nosheen Sabahat 1, Samson Nassrani2  \n1Department of Computer Science, Forman Christian College University, Lahore, 54000, Pakistan  \n2 MBBS, College of Medicine and Dentistry (University of Lahore), Lahore, 54000, Pakistan [Corresponding Author: kinzaharoon@gmail.com](Corresponding Author: kinzaharoon@gmail.com)  \nABSTRACT  \nMental health is recognized as a non-communicable disease that impairs human lives, sometimes beyond recovery. While everyone is at risk of developing a mental illness, adolescents are more prone to it due to various factors like hormonal changes, study pressure, social pressure, etc. If mental health goes ignored at this stage, it can cause serious, even fatal problems later on in life, which not only impacts a family but also the young workforce of a country. Hence, constant efforts are being made for the early detection of mental disorders so they can be treated better. Early prediction of mental health issues is a classic machine learning problem relying on patient history and data. In this survey, we discuss a total of 22 previous research papers based on machine learning algorithms and other statistical analysis tools employed for the said task and compare their efficacy. The research papers are categorized into different mental health disorders such as 1) Methods for predicting Depression and Anxiety 2) Methods for Suidial Prevalence 3) Methods for Predicting Autism Spectrum Disorder (ASD) 4) Methods for Predicting Substance Abuse among adolescents. On the basis of accuracy, the performance of machine learning prediction models was compared. CNN models, Random Forest, and XGBoost generally performed better than other models. There is centralized research in Pakistan on mental health based on machine learning so SPSS and other tools are mostly used for data analysis. The findings suggest that Machine learning algorithms can be effective for classifying and early predicting high-risk factors among adolescents.  \nKEYWORDS  \nMental health, machine learning, adolescents, and early prediction  \nJOURNAL INFO  \nHISTORY: Received: January 9, 2023 Accepted: March 8, 2023 Published: March 18, 2023  \n1. INTRODUCTION  \nMental Health is an important aspect of overall health. The term ―Mental Health‖ refers to the cognitive, behavioral, and emotional well-being of people. It is all about how people think, feel, and act. Mental disorders are on the rise around the world, one in every four individuals will be impacted by mental and neurological disorders at some point in their lives. The evolution of mental disorders, however, has been cyclical rather than linear or progressive. At a time in history, a behavior was considered normal or deviant depending on the environment in which it occurs, and so varies according to time and culture. In the past, there have been three major explanations for mental disorders: supernatural, biological, and psychological. Deviant behavior has been considered a reflection of good and evil behavior. Unexplainable and irrational behavior, people have perceived as evil. Although people having physical health problems are at an increased risk of having mental health problems, cases of mental health issues despite being physically healthy to have been reported as well.  \nAll humans possess a brain, hence all genders and ages are prone to develop a mental disorder. In developing countries, 10-14% of the population suffer from mental disorders, with only 35% receiving treatment, and an  \nestimated 50.8 million people suffering from severe mental illness [1] . Types and Severity of mental disorders depend upon a variety of fact","cbCaiiWZxeHYU6eM","https://ap.wps.com/l/cbCaiiWZxeHYU6eM","pdf",417137,1,14,"English","en",105,"# Abstract\n# Keywords\n# Journal Info\n## History\n# Introduction\n## Mental health concepts and prevalence","[{\"question\":\"Why is early prediction of mental health issues important for adolescents?\",\"answer\":\"Adolescents are more prone to mental health problems due to multiple pressures. Early detection supports better treatment and helps prevent serious long-term outcomes.\"},{\"question\":\"How does the survey structure its comparison of machine learning approaches?\",\"answer\":\"It reviews 22 previous research papers and categorizes them by target disorder, then compares model performance based on accuracy.\"},{\"question\":\"Which machine learning models generally performed best in the reviewed studies?\",\"answer\":\"CNN models, Random Forest, and XGBoost generally showed stronger performance than other approaches according to the survey findings.\"}]","Machine Learning Approches for Prediction of Mental Health Issues in Adolescents - A Comparative Survey | PDF",1785680283,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-approches-for-prediction-of-mental-health-issues-in-adolescents-a-comparative-survey","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-approches-for-prediction-of-mental-health-issues-in-adolescents-a-comparative-survey/117902/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is early prediction of mental health issues important for adolescents?","Question",{"text":75,"@type":76},"Adolescents are more prone to mental health problems due to multiple pressures. Early detection supports better treatment and helps prevent serious long-term outcomes.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the survey structure its comparison of machine learning approaches?",{"text":80,"@type":76},"It reviews 22 previous research papers and categorizes them by target disorder, then compares model performance based on accuracy.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning models generally performed best in the reviewed studies?",{"text":84,"@type":76},"CNN models, Random Forest, and XGBoost generally showed stronger performance than other approaches according to the survey findings.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]