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A review: PTSD in pre-existing medical condition on social media

Post-Traumatic Stress Disorder (PTSD) is a multifaceted mental health condition, particularly challenging for individuals with pre-existing medical conditions. This review critically examines the intersection of PTSD and chronic illnesses as expressed on social media platforms. By systematically ana...

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Main Authors: Al Hassan Ayon, Zaber, Nur Hafieza, Ismail, Nur Shazwani, Kamarudin
Format: Article
Language:English
Published: The Science and Information (SAI) Organization Limited 2024
Subjects:
QA75 Electronic computers. Computer science
RC Internal medicine
Online Access:http://umpir.ump.edu.my/id/eprint/43560/1/A%20review-PTSD%20in%20pre-existing%20medical%20condition%20on%20social%20media.pdf
http://umpir.ump.edu.my/id/eprint/43560/
https://doi.org/10.14569/IJACSA.2024.0151194
https://doi.org/10.14569/IJACSA.2024.0151194
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spelling my.ump.umpir.435602025-01-10T01:44:56Z http://umpir.ump.edu.my/id/eprint/43560/ A review: PTSD in pre-existing medical condition on social media Al Hassan Ayon, Zaber Nur Hafieza, Ismail Nur Shazwani, Kamarudin QA75 Electronic computers. Computer science RC Internal medicine Post-Traumatic Stress Disorder (PTSD) is a multifaceted mental health condition, particularly challenging for individuals with pre-existing medical conditions. This review critically examines the intersection of PTSD and chronic illnesses as expressed on social media platforms. By systematically analyzing literature from 2008 to 2024, the study explores how PTSD manifests and is managed in individuals with chronic conditions such as cancer, heart disease, and autoimmune disorders, with a focus on online expressions on platforms like X (formally known as Twitter) and Facebook. Findings demonstrate that social media data offers valuable insights into the unique challenges faced by individuals with both PTSD and chronic illnesses. Specifically, natural language processing (NLP) and machine learning (ML) techniques can identify potential PTSD cases among these populations, achieving accuracy rates between 74% and 90%. Furthermore, the role of online support communities in shaping coping strategies and facilitating early interventions is highlighted. This review underscores the necessity of incorporating considerations of pre-existing medical conditions in PTSD research and treatment, emphasizing social media's potential as a monitoring and support tool for vulnerable groups. Future research directions and clinical implications are also discussed, with an emphasis on developing targeted interventions. The Science and Information (SAI) Organization Limited 2024-11 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/43560/1/A%20review-PTSD%20in%20pre-existing%20medical%20condition%20on%20social%20media.pdf Al Hassan Ayon, Zaber and Nur Hafieza, Ismail and Nur Shazwani, Kamarudin (2024) A review: PTSD in pre-existing medical condition on social media. International Journal of Advanced Computer Science and Applications (IJACSA), 15 (11). pp. 1-11. ISSN 2156-5570(Online). (Published) https://doi.org/10.14569/IJACSA.2024.0151194 https://doi.org/10.14569/IJACSA.2024.0151194
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
RC Internal medicine
spellingShingle QA75 Electronic computers. Computer science
RC Internal medicine
Al Hassan Ayon, Zaber
Nur Hafieza, Ismail
Nur Shazwani, Kamarudin
A review: PTSD in pre-existing medical condition on social media
description Post-Traumatic Stress Disorder (PTSD) is a multifaceted mental health condition, particularly challenging for individuals with pre-existing medical conditions. This review critically examines the intersection of PTSD and chronic illnesses as expressed on social media platforms. By systematically analyzing literature from 2008 to 2024, the study explores how PTSD manifests and is managed in individuals with chronic conditions such as cancer, heart disease, and autoimmune disorders, with a focus on online expressions on platforms like X (formally known as Twitter) and Facebook. Findings demonstrate that social media data offers valuable insights into the unique challenges faced by individuals with both PTSD and chronic illnesses. Specifically, natural language processing (NLP) and machine learning (ML) techniques can identify potential PTSD cases among these populations, achieving accuracy rates between 74% and 90%. Furthermore, the role of online support communities in shaping coping strategies and facilitating early interventions is highlighted. This review underscores the necessity of incorporating considerations of pre-existing medical conditions in PTSD research and treatment, emphasizing social media's potential as a monitoring and support tool for vulnerable groups. Future research directions and clinical implications are also discussed, with an emphasis on developing targeted interventions.
format Article
author Al Hassan Ayon, Zaber
Nur Hafieza, Ismail
Nur Shazwani, Kamarudin
author_facet Al Hassan Ayon, Zaber
Nur Hafieza, Ismail
Nur Shazwani, Kamarudin
author_sort Al Hassan Ayon, Zaber
title A review: PTSD in pre-existing medical condition on social media
title_short A review: PTSD in pre-existing medical condition on social media
title_full A review: PTSD in pre-existing medical condition on social media
title_fullStr A review: PTSD in pre-existing medical condition on social media
title_full_unstemmed A review: PTSD in pre-existing medical condition on social media
title_sort review: ptsd in pre-existing medical condition on social media
publisher The Science and Information (SAI) Organization Limited
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/43560/1/A%20review-PTSD%20in%20pre-existing%20medical%20condition%20on%20social%20media.pdf
http://umpir.ump.edu.my/id/eprint/43560/
https://doi.org/10.14569/IJACSA.2024.0151194
https://doi.org/10.14569/IJACSA.2024.0151194
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score 13.235362

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