Mental health at Nova Sbe

Detalhes bibliográficos
Autor(a) principal: Ahrach, Bilal El
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/156088
Resumo: This research tackles the understanding of the leading drivers affecting mental health amongst Nova SBE students during Covid-19. The objective behind the study is to identify the groups of students with the highest risk of suffering from poor mental health, in order to achieve measures of prevention corresponding to where they may suffer the most. The dataset is composed of three similar surveys forwarded to students in separate times of the academic year 2021-2022. I will be using unsupervised clustering algorithms on the data to fixate newly formed groups of students sharing the same similarity traits based on the frameworks of the surveys. The results will be leveraged using analytical and descriptive techniques to serve the purpose of the study. The main tool used in this research is Python programming language, mainly chosen for the implementation of the material covered during my master’s degree, and for the flexibility of using the different packages and libraries (Pandas, NumPy, Matplotlib, Scikit-learn).
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spelling Mental health at Nova SbeMental healthStudentsClustering algorithmsPreventionDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis research tackles the understanding of the leading drivers affecting mental health amongst Nova SBE students during Covid-19. The objective behind the study is to identify the groups of students with the highest risk of suffering from poor mental health, in order to achieve measures of prevention corresponding to where they may suffer the most. The dataset is composed of three similar surveys forwarded to students in separate times of the academic year 2021-2022. I will be using unsupervised clustering algorithms on the data to fixate newly formed groups of students sharing the same similarity traits based on the frameworks of the surveys. The results will be leveraged using analytical and descriptive techniques to serve the purpose of the study. The main tool used in this research is Python programming language, mainly chosen for the implementation of the material covered during my master’s degree, and for the flexibility of using the different packages and libraries (Pandas, NumPy, Matplotlib, Scikit-learn).Barros, Pedro PitaRUNAhrach, Bilal El2023-08-01T08:47:40Z2023-01-132023-01-122023-01-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/156088TID:203312473enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:13:31Zoai:run.unl.pt:10362/156088Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:43:59.267242Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Mental health at Nova Sbe
title Mental health at Nova Sbe
spellingShingle Mental health at Nova Sbe
Ahrach, Bilal El
Mental health
Students
Clustering algorithms
Prevention
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Mental health at Nova Sbe
title_full Mental health at Nova Sbe
title_fullStr Mental health at Nova Sbe
title_full_unstemmed Mental health at Nova Sbe
title_sort Mental health at Nova Sbe
author Ahrach, Bilal El
author_facet Ahrach, Bilal El
author_role author
dc.contributor.none.fl_str_mv Barros, Pedro Pita
RUN
dc.contributor.author.fl_str_mv Ahrach, Bilal El
dc.subject.por.fl_str_mv Mental health
Students
Clustering algorithms
Prevention
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Mental health
Students
Clustering algorithms
Prevention
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This research tackles the understanding of the leading drivers affecting mental health amongst Nova SBE students during Covid-19. The objective behind the study is to identify the groups of students with the highest risk of suffering from poor mental health, in order to achieve measures of prevention corresponding to where they may suffer the most. The dataset is composed of three similar surveys forwarded to students in separate times of the academic year 2021-2022. I will be using unsupervised clustering algorithms on the data to fixate newly formed groups of students sharing the same similarity traits based on the frameworks of the surveys. The results will be leveraged using analytical and descriptive techniques to serve the purpose of the study. The main tool used in this research is Python programming language, mainly chosen for the implementation of the material covered during my master’s degree, and for the flexibility of using the different packages and libraries (Pandas, NumPy, Matplotlib, Scikit-learn).
publishDate 2023
dc.date.none.fl_str_mv 2023-08-01T08:47:40Z
2023-01-13
2023-01-12
2023-01-13T00:00:00Z
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dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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