Prediction of anxiety and depression among the transgender in Bangladesh

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Bibliographic Details
Main Authors:	Easha, Ishrat Jahan, Faiza, Fairooz Afnad, Sadique, Mohammad Rafiuddin, Tabassum, Fatima, Uddin, Md. Rakib
Other Authors:	Alam, Md. Golam Rabiul
Format:	Thesis
Language:	English
Published:	Brac University 2023
Subjects:	Mental health Transgender NLP Prediction Anxiety Depression Machine learning
Online Access:	http://hdl.handle.net/10361/18310

id	10361-18310
record_format	dspace
spelling	10361-183102023-05-23T21:01:56Z Prediction of anxiety and depression among the transgender in Bangladesh Easha, Ishrat Jahan Faiza, Fairooz Afnad Sadique, Mohammad Rafiuddin Tabassum, Fatima Uddin, Md. Rakib Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Mental health Transgender NLP Prediction Anxiety Depression Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 28-29). Today, mental health is as important as safety. It affects people directly and indirectly. Transgender people with mental health issues are often overlooked and in our nation, especially transgender women, suffer from anxiety, depression, and suicide. This research examines depression and anxiety prediction. Classification models and NLP are used to detect depression and anxiety in 41 Bangladeshi transgender people. The data came from sociodemographic, victimization, social support, interpersonal functioning, depression, anxiety, and self-esteem questionnaires (RSE). We predicted depression and anxiety in transgender people using culturally adapted depression and anxiety scales and a hybrid questionnaire based on minority and resilience. We conducted interviews, analyzed sentiment with TF-IDF, and constructed classification algorithms. We extracted and validated questionnaire data using median, SD, and Cronbach alpha. Correlation between two independent variables. Chi-square and ANOVA examined transgender depression, anxiety, and age. This link was validated using SVM, XGBoost, Naive Bayes, and Logistic Regression where SVM and Naive Bayes had a better accuracy for depression which was 84.6% and for anxiety SVM gave 76.9%. In the case of NLP linear SVC and Random Forest gave the highest F1 score among others which were 92.30% and 76.92% respectively. Using these methods, we determined that depression is comparatively minimal whereas anxiety is severe. This association can be used to minimize the severity of these mental health problems. Ishrat Jahan Easha Fairooz Afnad Faiza Mohammad Rafiuddin Sadique Fatima Tabassum Md. Rakib Uddin B. Computer Science 2023-05-23T05:49:09Z 2023-05-23T05:49:09Z 2022 2022-05 Thesis ID 18101356 ID 18101367 ID 17201011 ID 18101439 ID 17101254 http://hdl.handle.net/10361/18310 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 29 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Mental health Transgender NLP Prediction Anxiety Depression Machine learning
spellingShingle	Mental health Transgender NLP Prediction Anxiety Depression Machine learning Easha, Ishrat Jahan Faiza, Fairooz Afnad Sadique, Mohammad Rafiuddin Tabassum, Fatima Uddin, Md. Rakib Prediction of anxiety and depression among the transgender in Bangladesh
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Alam, Md. Golam Rabiul
author_facet	Alam, Md. Golam Rabiul Easha, Ishrat Jahan Faiza, Fairooz Afnad Sadique, Mohammad Rafiuddin Tabassum, Fatima Uddin, Md. Rakib
format	Thesis
author	Easha, Ishrat Jahan Faiza, Fairooz Afnad Sadique, Mohammad Rafiuddin Tabassum, Fatima Uddin, Md. Rakib
author_sort	Easha, Ishrat Jahan
title	Prediction of anxiety and depression among the transgender in Bangladesh
title_short	Prediction of anxiety and depression among the transgender in Bangladesh
title_full	Prediction of anxiety and depression among the transgender in Bangladesh
title_fullStr	Prediction of anxiety and depression among the transgender in Bangladesh
title_full_unstemmed	Prediction of anxiety and depression among the transgender in Bangladesh
title_sort	prediction of anxiety and depression among the transgender in bangladesh
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/18310
work_keys_str_mv	AT eashaishratjahan predictionofanxietyanddepressionamongthetransgenderinbangladesh AT faizafairoozafnad predictionofanxietyanddepressionamongthetransgenderinbangladesh AT sadiquemohammadrafiuddin predictionofanxietyanddepressionamongthetransgenderinbangladesh AT tabassumfatima predictionofanxietyanddepressionamongthetransgenderinbangladesh AT uddinmdrakib predictionofanxietyanddepressionamongthetransgenderinbangladesh
_version_	1814309059385360384

Prediction of anxiety and depression among the transgender in Bangladesh

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