Chatbot-Based Dialogue for Early Psychosis Detection: Leveraging Global Assessment of Functioning (GAF)

Astria Hijriani, Lailatus Salma, Sulastri, Yohana Tri Utami, Yunda Heningtyas

2023

Abstract

Mental disorders patients often make people restless because they have uncontrollable behavior and need special rehabilitation. Not every patient's family knows how to handle them, and health workers find it difficult to monitor their condition. Early detection of psychosis, specifically schizophrenia, is critical for effective treatment and support. Existing studies have explored expert systems and mobile applications for diagnosing mental disorders and depression. Still, none have concentrated on developing a system or application for the early detection of psychosis based on its severity. This research seeks to significantly contribute to the mental health field by improving the early detection of psychosis, ultimately enhancing the lives of individuals affected by this condition using chatbot-based dialog. The Early detection of psychosis features was developed using the Global Assessment of Functional (GAF) and integrated with the Jiwamuku mobile application. This GAF was categorized into four classifications: not indicated, mild, medium, and serious. This feature was tested on 15 respondents. The application shows that two people are not indicated: 11 are mild, one is medium, and one is severe. Of all the data taken, 14 tests are accurate. The result shows that early detection of psychosis features with Global Assessment of Functioning can be detected with 93% accuracy. This research underscores the critical importance of early detection of mental disorders, particularly psychosis, by harnessing the potential of chatbot-based dialogue and the Global Assessment of Functioning (GAF).

Paper Citation

in Harvard Style

Hijriani A., Salma L., Sulastri., Utami Y. and Heningtyas Y. (2023). Chatbot-Based Dialogue for Early Psychosis Detection: Leveraging Global Assessment of Functioning (GAF). In Proceedings of the 1st International Conference on Medical Science and Health - Volume 1: ICOMESH; ISBN 978-989-758-740-5, SciTePress, pages 271-277. DOI: 10.5220/0013671300003873

in Bibtex Style

@conference{icomesh23,
author={Astria Hijriani and Lailatus Salma and Sulastri and Yohana Tri Utami and Yunda Heningtyas},
title={Chatbot-Based Dialogue for Early Psychosis Detection: Leveraging Global Assessment of Functioning (GAF)},
booktitle={Proceedings of the 1st International Conference on Medical Science and Health - Volume 1: ICOMESH},
year={2023},
pages={271-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013671300003873},
isbn={978-989-758-740-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Medical Science and Health - Volume 1: ICOMESH
TI - Chatbot-Based Dialogue for Early Psychosis Detection: Leveraging Global Assessment of Functioning (GAF)
SN - 978-989-758-740-5
AU - Hijriani A.
AU - Salma L.
AU - Sulastri.
AU - Utami Y.
AU - Heningtyas Y.
PY - 2023
SP - 271
EP - 277
DO - 10.5220/0013671300003873
PB - SciTePress