Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial

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
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 (ORCID Profile 0000-0001-8242-0014)
Yam, Jason C
Chui, Celine Sze Ling
Ip, Patrick

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