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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Padang
2024
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/115134/1/115134.pdf |
| _version_ | 1825940619755782144 |
|---|---|
| author | Wan Ab.Rahman, Wan Nurhayati Abdul Hamid, Nurul Munirah |
| author_facet | Wan Ab.Rahman, Wan Nurhayati Abdul Hamid, Nurul Munirah |
| author_sort | Wan Ab.Rahman, Wan Nurhayati |
| collection | UPM |
| 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. |
| first_indexed | 2025-03-07T13:04:32Z |
| format | Article |
| id | upm.eprints-115134 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2025-03-07T13:04:32Z |
| publishDate | 2024 |
| publisher | Politeknik Negeri Padang |
| record_format | dspace |
| spelling | 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 |
| spellingShingle | Wan Ab.Rahman, Wan Nurhayati Abdul Hamid, Nurul Munirah Rule-based chatbot for early self-depression indication: a promising approach |
| title | 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_short | Rule-based chatbot for early self-depression indication: a promising approach |
| title_sort | rule based chatbot for early self depression indication a promising approach |
| url | http://psasir.upm.edu.my/id/eprint/115134/1/115134.pdf |
| work_keys_str_mv | AT wanabrahmanwannurhayati rulebasedchatbotforearlyselfdepressionindicationapromisingapproach AT abdulhamidnurulmunirah rulebasedchatbotforearlyselfdepressionindicationapromisingapproach |