Development and Evaluation of a Mental Health Chatbot Using ChatGPT 4.0: Mixed Methods User Experience Study With Korean Users.

IF 3.1 3区 医学 Q2 MEDICAL INFORMATICS JMIR Medical Informatics Pub Date : 2025-01-03 DOI:10.2196/63538
Boyoung Kang, Munpyo Hong
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引用次数: 0

Abstract

Background: Mental health chatbots have emerged as a promising tool for providing accessible and convenient support to individuals in need. Building on our previous research on digital interventions for loneliness and depression among Korean college students, this study addresses the limitations identified and explores more advanced artificial intelligence-driven solutions.

Objective: This study aimed to develop and evaluate the performance of HoMemeTown Dr. CareSam, an advanced cross-lingual chatbot using ChatGPT 4.0 (OpenAI) to provide seamless support in both English and Korean contexts. The chatbot was designed to address the need for more personalized and culturally sensitive mental health support identified in our previous work while providing an accessible and user-friendly interface for Korean young adults.

Methods: We conducted a mixed methods pilot study with 20 Korean young adults aged 18 to 27 (mean 23.3, SD 1.96) years. The HoMemeTown Dr CareSam chatbot was developed using the GPT application programming interface, incorporating features such as a gratitude journal and risk detection. User satisfaction and chatbot performance were evaluated using quantitative surveys and qualitative feedback, with triangulation used to ensure the validity and robustness of findings through cross-verification of data sources. Comparative analyses were conducted with other large language models chatbots and existing digital therapy tools (Woebot [Woebot Health Inc] and Happify [Twill Inc]).

Results: Users generally expressed positive views towards the chatbot, with positivity and support receiving the highest score on a 10-point scale (mean 9.0, SD 1.2), followed by empathy (mean 8.7, SD 1.6) and active listening (mean 8.0, SD 1.8). However, areas for improvement were noted in professionalism (mean 7.0, SD 2.0), complexity of content (mean 7.4, SD 2.0), and personalization (mean 7.4, SD 2.4). The chatbot demonstrated statistically significant performance differences compared with other large language models chatbots (F=3.27; P=.047), with more pronounced differences compared with Woebot and Happify (F=12.94; P<.001). Qualitative feedback highlighted the chatbot's strengths in providing empathetic responses and a user-friendly interface, while areas for improvement included response speed and the naturalness of Korean language responses.

Conclusions: The HoMemeTown Dr CareSam chatbot shows potential as a cross-lingual mental health support tool, achieving high user satisfaction and demonstrating comparative advantages over existing digital interventions. However, the study's limited sample size and short-term nature necessitate further research. Future studies should include larger-scale clinical trials, enhanced risk detection features, and integration with existing health care systems to fully realize its potential in supporting mental well-being across different linguistic and cultural contexts.

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使用ChatGPT 4.0开发和评估心理健康聊天机器人:韩国用户的混合方法用户体验研究。
背景:心理健康聊天机器人已经成为一种有前途的工具,可以为有需要的个人提供可访问和方便的支持。在我们之前对韩国大学生孤独感和抑郁症的数字干预研究的基础上,本研究解决了所发现的局限性,并探索了更先进的人工智能驱动的解决方案。目的:本研究旨在开发和评估hometown Dr. CareSam的性能,这是一款先进的跨语言聊天机器人,使用ChatGPT 4.0 (OpenAI)提供英语和韩语上下文的无缝支持。该聊天机器人旨在满足我们之前工作中确定的对更加个性化和文化敏感的心理健康支持的需求,同时为韩国年轻人提供易于访问和用户友好的界面。方法:我们对20名年龄在18至27岁(平均23.3岁,标准差1.96)的韩国年轻人进行了一项混合方法的初步研究。hometown医生CareSam聊天机器人是使用GPT应用程序编程接口开发的,结合了感恩日记和风险检测等功能。通过定量调查和定性反馈来评估用户满意度和聊天机器人的性能,并通过对数据源的交叉验证使用三角测量来确保结果的有效性和稳健性。与其他大型语言模型、聊天机器人和现有数字治疗工具(Woebot [Woebot Health Inc .]和Happify [Twill Inc .])进行了比较分析。结果:用户普遍对聊天机器人表达了积极的看法,在10分量表中,积极和支持得分最高(平均9.0分,SD 1.2分),其次是同情(平均8.7分,SD 1.6分)和积极倾听(平均8.0分,SD 1.8分)。然而,在专业性(平均7.0,SD 2.0)、内容复杂性(平均7.4,SD 2.0)和个性化(平均7.4,SD 2.4)方面指出了需要改进的领域。与其他大型语言模型聊天机器人相比,该聊天机器人表现出统计学上显著的性能差异(F=3.27;P= 0.047),与Woebot和Happify相比差异更显著(F=12.94;结论:hometown的CareSam医生聊天机器人显示出作为一种跨语言心理健康支持工具的潜力,实现了很高的用户满意度,并展示了与现有数字干预措施相比的相对优势。然而,该研究样本量有限,短期性质,需要进一步研究。未来的研究应包括更大规模的临床试验,增强风险检测功能,并与现有的卫生保健系统整合,以充分发挥其在不同语言和文化背景下支持心理健康的潜力。
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来源期刊
JMIR Medical Informatics
JMIR Medical Informatics Medicine-Health Informatics
CiteScore
7.90
自引率
3.10%
发文量
173
审稿时长
12 weeks
期刊介绍: JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
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