Chen, Chen, Lam, Kok Tai, Yip, Ka Man, So, Hung Kwan, Lum, Terry Yat Sang, Wong, Ian Chi Kei, Yam, Jason C, Chui, Celine Sze Ling and Ip, Patrick (2025). Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial. JMIR human factors, 12 ,
Abstract
BACKGROUND: Artificial intelligence (AI) chatbots have been customized to deliver on-demand support for people with mental health problems. However, the effectiveness of AI chatbots in tackling mental health problems among the general public in Hong Kong remains unclear. OBJECTIVE: This study aimed to develop a local AI chatbot and compare the effectiveness of the AI chatbot with a conventional nurse hotline in reducing the level of anxiety and depression among individuals in Hong Kong. METHODS: This study was a pilot randomized controlled trial conducted from October 2022 to March 2023, involving 124 participants allocated randomly (1:1 ratio) into the AI chatbot and nurse hotline groups. Among these, 62 participants in the AI chatbot group and 41 in the nurse hotline group completed both the pre- and postquestionnaires, including the GAD-7 (Generalized Anxiety Disorder Scale-7), PHQ-9 (Patient Health Questionnaire-9), and satisfaction questionnaire. Comparisons were conducted using independent and paired sample t tests (2-tailed) and the χ2 test to analyze changes in anxiety and depression levels. RESULTS: Compared to the mean baseline score of 5.13 (SD 4.623), the mean postdepression score in the chatbot group was 3.68 (SD 4.397), which was significantly lower (P=.008). Similarly, a reduced anxiety score was also observed after the chatbot test (pre vs post: mean 4.74, SD 4.742 vs mean 3.4, SD 3.748; P=.005), respectively. No significant differences were found in the pre-post scores for either depression (P=.38) or anxiety (P=.19). No statistically significant difference was observed in service satisfaction between the two platforms (P=.32). CONCLUSIONS: The AI chatbot was comparable to the traditional nurse hotline in alleviating participants' anxiety and depression after responding to inquiries. Moreover, the AI chatbot has shown potential in alleviating short-term anxiety and depression compared to the nurse hotline. While the AI chatbot presents a promising solution for offering accessible strategies to the public, more extensive randomized controlled studies are necessary to further validate its effectiveness.
Publication DOI: | https://doi.org/10.2196/65785 |
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Divisions: | College of Health & Life Sciences > Aston Pharmacy School College of Health & Life Sciences Aston University (General) |
Funding Information: | This study was funded by the Collaborative Research Fund, University Grants Committee (reference no. C7149-20GF) and General Research Fund, University Grants Committee (reference no. 17606523). All authors approved the final manuscript as submitted and ag |
Additional Information: | Copyright © Chen Chen, Kok Tai Lam, Ka Man Yip, Hung Kwan So, Terry Yat Sang Lum, Ian Chi Kei Wong, Jason C Yam, Celine Sze Ling Chui, Patrick Ip. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 6.3.2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. |
Uncontrolled Keywords: | AI chatbot,anxiety,depression,effectiveness,artificial intelligence |
Publication ISSN: | 2292-9495 |
Last Modified: | 26 Mar 2025 11:14 |
Date Deposited: | 20 Mar 2025 13:27 |
Full Text Link: | |
Related URLs: |
https://humanfa ... g/2025/1/e65785
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2025-03-06 |
Published Online Date: | 2025-03-06 |
Accepted Date: | 2025-01-15 |
Authors: |
Chen, Chen
Lam, Kok Tai Yip, Ka Man So, Hung Kwan Lum, Terry Yat Sang Wong, Ian Chi Kei ( ![]() Yam, Jason C Chui, Celine Sze Ling Ip, Patrick |