Rule-based chatbot for early self-depression indication: a promising approach

Depression is a prevalent mental health condition worldwide, often characterized by persistent sadness, loss of interest or pleasure, and feelings of worthlessness. Depression is the leading cause of mental health issues worldwide, and it is becoming more severe without self-awareness, early screen...

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Main Authors: Wan Ab.Rahman, Wan Nurhayati, Abdul Hamid, Nurul Munirah
Format: Article
Language:English
Published: Politeknik Negeri Padang 2024
Online Access:http://psasir.upm.edu.my/id/eprint/115134/1/115134.pdf
http://psasir.upm.edu.my/id/eprint/115134/
https://joiv.org/index.php/joiv/article/view/1628
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spelling my.upm.eprints.1151342025-02-25T08:53:51Z http://psasir.upm.edu.my/id/eprint/115134/ Rule-based chatbot for early self-depression indication: a promising approach Wan Ab.Rahman, Wan Nurhayati Abdul Hamid, Nurul Munirah Depression is a prevalent mental health condition worldwide, often characterized by persistent sadness, loss of interest or pleasure, and feelings of worthlessness. Depression is the leading cause of mental health issues worldwide, and it is becoming more severe without self-awareness, early screening, and further medication. Early detection and intervention are critical in mitigating its adverse effects. Leveraging advancements in Artificial Intelligence (AI), particularly in Natural Language Processing (NLP), chatbots have emerged as potential tools for early depression indication. Chatbots are beneficial tools in the mental health domain, such as in assisting mental health risk users. This paper presents the development of a rule-based chatbot aimed at detecting early signs of depression through conversational interactions by screening symptoms of depression. Predefined rules are developed to ensure the assessment can generate reliable results. The rule-based chatbot is developed to assist in depression indication assessment for mental health-risk individuals at an early stage and provide the risky patient with appropriate support and resources. The chatbot assessment has adopted the Depression Anxiety and Stress Scale 21 (DASS21) instrument. Based on the System Usability Scale (SUS) results, the rule-based chatbot has been accepted by all 30 respondents with good acceptance of an average SUS score of 77.2. Thus, the outcome of this chatbot can be utilized as a professional platform to encourage self-disclosure of mental depression indications for users, and it can be beneficial as the initial reference before recommending further action before the earlier help-seeking. Politeknik Negeri Padang 2024 Article PeerReviewed text en cc_by_sa_4 http://psasir.upm.edu.my/id/eprint/115134/1/115134.pdf Wan Ab.Rahman, Wan Nurhayati and Abdul Hamid, Nurul Munirah (2024) Rule-based chatbot for early self-depression indication: a promising approach. International Journal on Informatics Visualization, 8 (3-2). ISSN 2549-9904 https://joiv.org/index.php/joiv/article/view/1628 10.62527/joiv.8.3-2.1628
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Depression is a prevalent mental health condition worldwide, often characterized by persistent sadness, loss of interest or pleasure, and feelings of worthlessness. Depression is the leading cause of mental health issues worldwide, and it is becoming more severe without self-awareness, early screening, and further medication. Early detection and intervention are critical in mitigating its adverse effects. Leveraging advancements in Artificial Intelligence (AI), particularly in Natural Language Processing (NLP), chatbots have emerged as potential tools for early depression indication. Chatbots are beneficial tools in the mental health domain, such as in assisting mental health risk users. This paper presents the development of a rule-based chatbot aimed at detecting early signs of depression through conversational interactions by screening symptoms of depression. Predefined rules are developed to ensure the assessment can generate reliable results. The rule-based chatbot is developed to assist in depression indication assessment for mental health-risk individuals at an early stage and provide the risky patient with appropriate support and resources. The chatbot assessment has adopted the Depression Anxiety and Stress Scale 21 (DASS21) instrument. Based on the System Usability Scale (SUS) results, the rule-based chatbot has been accepted by all 30 respondents with good acceptance of an average SUS score of 77.2. Thus, the outcome of this chatbot can be utilized as a professional platform to encourage self-disclosure of mental depression indications for users, and it can be beneficial as the initial reference before recommending further action before the earlier help-seeking.
format Article
author Wan Ab.Rahman, Wan Nurhayati
Abdul Hamid, Nurul Munirah
spellingShingle Wan Ab.Rahman, Wan Nurhayati
Abdul Hamid, Nurul Munirah
Rule-based chatbot for early self-depression indication: a promising approach
author_facet Wan Ab.Rahman, Wan Nurhayati
Abdul Hamid, Nurul Munirah
author_sort Wan Ab.Rahman, Wan Nurhayati
title Rule-based chatbot for early self-depression indication: a promising approach
title_short Rule-based chatbot for early self-depression indication: a promising approach
title_full Rule-based chatbot for early self-depression indication: a promising approach
title_fullStr Rule-based chatbot for early self-depression indication: a promising approach
title_full_unstemmed Rule-based chatbot for early self-depression indication: a promising approach
title_sort rule-based chatbot for early self-depression indication: a promising approach
publisher Politeknik Negeri Padang
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/115134/1/115134.pdf
http://psasir.upm.edu.my/id/eprint/115134/
https://joiv.org/index.php/joiv/article/view/1628
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score 13.244413