⚡ Quick Summary
This study conducted a mixed methods analysis of AI-driven chatbots for mental health support, involving 8 interdisciplinary mental health professionals. The findings revealed significant concerns regarding trust and potential harm to users, emphasizing the need for cautious design and implementation of these technologies.
🔍 Key Details
- 👥 Participants: 8 interdisciplinary mental health professionals
- 🤖 Chatbots analyzed: 2 popular mental health-related chatbots
- 📊 Methods: Mixed methods, including Trust in Automation scale and semistructured interviews
- 📈 Analysis: Thematic analysis and 2-tailed, paired t test
🔑 Key Takeaways
- ⚠️ Concerns raised about chatbot responses potentially causing harm to users.
- 💔 Generic care provided by chatbots risks user dependence and manipulation.
- 🔒 Trust scores were medium to low, with no significant differences between chatbots.
- 🛑 Mental health professionals collectively resist the use of these chatbots for at-risk users.
- ⚙️ Ethical implications of AI in mental health support must be critically assessed.
- 🔄 Ongoing evaluation and refinement of chatbot design are essential for safety.
📚 Background
The rise of AI-driven chatbots as companions for social and mental health support has been notable in recent years. While these tools promise personalized and empathic responses, it is crucial to understand their potential risks, especially for vulnerable populations. The ethical and clinical implications of deploying such technologies require thorough examination to ensure they do not inadvertently harm users.
🗒️ Study
This study aimed to critically assess the implications of using chatbots in mental health support. Conducted with 8 mental health professionals from various fields, the research involved hands-on analysis of two popular chatbots. Participants engaged in profession-specific tasks, providing insights into the chatbots’ data handling, interface design, and response quality.
📈 Results
The qualitative analysis highlighted that mental health professionals had emphatic initial impressions of the chatbots, indicating a likelihood of harm due to their generic care approach. Trust scores from the Trust in Automation scale showed medium to low trust levels for both chatbots, with no statistically significant differences found (t6=-0.76; P=.48). These results underscore the need for caution in the design and deployment of AI-driven mental health solutions.
🌍 Impact and Implications
The findings of this study raise important questions about the integration of AI technologies in mental health support. The potential for harm, particularly for at-risk users, necessitates a careful and ethical approach to chatbot design. As mental health professionals express their concerns, it becomes clear that ongoing critical assessment and iterative refinement are essential to maximize benefits while minimizing risks.
🔮 Conclusion
This study sheds light on the complexities surrounding the use of AI-driven chatbots in mental health support. While these technologies hold promise, the insights from mental health professionals highlight the critical need for ethical considerations and rigorous evaluation. As we move forward, it is vital to ensure that the integration of AI into mental health care prioritizes user safety and well-being.
💬 Your comments
What are your thoughts on the use of AI-driven chatbots in mental health support? Let’s engage in a discussion! 💬 Share your insights in the comments below or connect with us on social media:
Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study.
Abstract
BACKGROUND: Recent years have seen an immense surge in the creation and use of chatbots as social and mental health companions. Aiming to provide empathic responses in support of the delivery of personalized support, these tools are often presented as offering immense potential. However, it is also essential that we understand the risks of their deployment, including their potential adverse impacts on the mental health of users, including those most at risk.
OBJECTIVE: The study aims to assess the ethical and pragmatic clinical implications of using chatbots that claim to aid mental health. While several studies within human-computer interaction and related fields have examined users’ perceptions of such systems, few studies have engaged mental health professionals in critical analysis of their conduct as mental health support tools. This paper comprises, in turn, an effort to assess the ethical and pragmatic clinical implications of using chatbots that claim to aid mental health.
METHODS: This study included 8 interdisciplinary mental health professional participants (from psychology and psychotherapy to social care and crisis volunteer workers) in a mixed methods and hands-on analysis of 2 popular mental health-related chatbots’ data handling, interface design, and responses. This analysis was carried out through profession-specific tasks with each chatbot, eliciting participants’ perceptions through both the Trust in Automation scale and semistructured interviews. Through thematic analysis and a 2-tailed, paired t test, these chatbots’ implications for mental health support were thus evaluated.
RESULTS: Qualitative analysis revealed emphatic initial impressions among mental health professionals of chatbot responses likely to produce harm, exhibiting a generic mode of care, and risking user dependence and manipulation given the central role of trust in the therapeutic relationship. Trust scores from the Trust in Automation scale, while exhibiting no statistically significant differences between the chatbots (t6=-0.76; P=.48), indicated medium to low trust scores for each chatbot. The findings of this work highlight that the design and development of artificial intelligence (AI)-driven mental health-related solutions must be undertaken with utmost caution. The mental health professionals in this study collectively resist these chatbots and make clear that AI-driven chatbots used for mental health by at-risk users invite several potential and specific harms.
CONCLUSIONS: Through this work, we contributed insights into the mental health professional perspective on the design of chatbots used for mental health and underscore the necessity of ongoing critical assessment and iterative refinement to maximize the benefits and minimize the risks associated with integrating AI into mental health support.
Author: [‘Moylan K’, ‘Doherty K’]
Journal: J Med Internet Res
Citation: Moylan K and Doherty K. Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study. Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study. 2025; 27:e67114. doi: 10.2196/67114