Case Study: Augmented Reality Enabled Mental Health Chatbot
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Keywords
Augmented reality, Large language model, Mood score
Abstract
Background and Objective: In recent years, there has been a growing demand for mental health support. This has led to a focus on providing personalized and continuous care. However, traditional mental health systems often have long wait times and limited support for engagements beyond clinical hours. The goal of this project is to create ARden, a digital companion using augmented reality, to help improve mental health for those in need.
Material and Method: This study aims to fine-tune a Large Language Model with domain-specific knowledge, ensuring a personalized and intelligent companion—ARden. The chatbot is integrated with the AR companion using an Application Program Interface (API). The mixed reality companion is accessible via a mobile application, making care available without the additional hardware costs associated with head-mounted displays.
Results: The development of ARden has introduced new possibilities for personalized and interactive mental health support. Early feedback suggests that the chatbot may help improve user engagement and satisfaction, supported by encouraging retention metrics. By combining augmented reality, large language models, and a character-based interface, ARden offers an approach that could contribute positively to mental health support.
Conclusion: ARden aims to help users with emotional regulation during long wait times between mental health interventions, overcome communication barriers, and provide exercises and suggestions to improve mental health wellbeing. This approach offers a promising solution to existing mental health challenges and holds potential for further improvement and scalability.
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References
2. Potts, C., Lindström, F., Bond, R., et al. A multilingual digital mental health and well-being chatbot (ChatPal): pre-post multicenter intervention study. J Med Internet Res. 2023;25:e43051. https://doi.org/10.2196/43051.
3. Farhat, F. ChatGPT as a complementary mental health resource: A boon or a bane. Ann Biomed Eng. 2024;52(5):1111–1114. https://doi.org/10.1007/s10439-023-03326-7.
4. Yang, R., Tan, T.F., Lu, W., et al. Large language models in health care: development, applications, and challenges. Health Care Sci. 2023;2(4):255–263. https://doi.org/10.1002/hcs2.61.
5. Booth F., Potts, C., Bond, R., et al. A mental health and well-being chatbot: user event log analysis. JMIR Mhealth Uhealth. 2023;11:e43052. https://doi.org/10.2196/43052.
6. Roumeliotis, K., Tselikas, N., Nasiopoulos, D. Llama 2: Early adopters’ utilization of Meta's new open-source pretrained model. Preprints. 2023. https://doi.org/10.20944/preprints202307.2142.v1.
7. Yang, K., Ji, S., Zhang, T., et al. Towards interpretable mental health analysis with large language models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapore, 6-10 December, 2023. https://doi.org/10.18653/v1/2023.emnlp-main.370.
8. Wu, C., Lin, W., Zhang, X., et al. PMC-LLaMA: toward building open-source language models for medicine. J Am Med Inform Assoc. 2024;31(9):1833–1843. https://doi.org/10.1093/jamia/ocae045.
9. Shields, R.E., Korol, S., Carleton, R.N., et al. Brief mental health disorder screening questionnaires and use with public safety personnel: a review. Int J Environ Res Public Health. 2021;18(7):3743. https://doi.org/10.3390/ijerph18073743.
10. Singha, R., Singha, S. Mental health treatment: exploring the potential of augmented reality and virtual reality. In Applications of Virtual and Augmented Reality for Health and Wellbeing; Hiran, K.K., Doshi, R., Patel, M., eds. IGI Global: Pennsylvania, USA; 2024; pp.91–110. https://doi.org/10.4018/979-8-3693-1123-3.ch006.
11. Bakır, Ç.N., Abbas, S.O., Sever, E., et al. Use of augmented reality in mental health-related conditions: a systematic review. Digit Health. 2023;9:20552076231203649. https://doi.org/10.1177/20552076231203649.
12. Lecomte, T., Potvin, S., Corbière, M., et al. Mobile apps for mental health issues: meta-review of meta-analyses. JMIR Mhealth Uhealth. 2020;8(5):e17458. https://doi.org/10.2196/17458.
13. Kernkraut, A.M., Diniz Nagem Janot de Matos, L. The impact of negative effects on the high prevalence of anxiety, depression and stress in healthcare professionals. Work. 2024; 79(2), 857–866. Available Online: https://journals.sagepub.com/doi/abs/10.3233/WOR-230257?download=true#:~:text=It%20was%20observed%20that%20a,of%20depression%20and%20stress%20prevalence.
14. May, R., Denecke, K. Security, privacy, and healthcare-related conversational agents: a scoping review. Inform Health Soc Care. 2022;47(2):194–210. https://doi.org/10.1080/17538157.2021.1983578.
15. Sahoo, S.S., Plasek, J.M., Xu, H., et al. Large language models for biomedicine: foundations, opportunities, challenges, and best practices. J Am Med Inform Assoc. 2024;31(9):2114–2124. https://doi.org/10.1093/jamia/ocae074.
16. Boucher, E.M., Harake, N.R., Ward, H.E., et al. Artificially intelligent chatbots in digital mental health interventions: a review. Expert Rev Med Devices. 2021;18(sup1):37–49. https://doi.org/10.1080/17434440.2021.2013200.
17. Touvron, H., Martin, L., Stone, K., et al. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288. 2023.
18. Zhang, R., Han, J., Liu, C, et al. LLaMA-adapter: Efficient fine-tuning of large language models with zero-initialized attention. In the Twelfth International Conference on Learning Representations, Vienna Austria, 7–11 May, 2024. Available Online: https://openreview.net/pdf?id=d4UiXAHN2W.
19. Carlson, C. Virtual and augmented simulations in mental health. Curr Psychiatry Rep. 2023;25(9):365–371. https://doi.org/10.1007/s11920-023-01438-4.
20. Hsu, M.C. The construction of critical factors for successfully introducing chatbots into mental health services in the army: Using a hybrid MCDM approach. Sustainability. 2023;15(10):7905. https://doi.org/10.3390/su15107905.
21. Dosovitskiy, G. and Bunge, E. Development of a chatbot for depression: adolescent perceptions and recommendations. Child Adolesc Ment Health. 2023;28(1):124–127. https://doi.org/10.1111/camh.12627.
22. Furukawa, T.A. Assessment of mood: guides for clinicians. J Psychosom Res. 2010;68(6):581–589. https://doi.org/10.1016/j.jpsychores.2009.05.003.
23. Berryman, C., Ferguson, C.J., Negy, C. Social media use and mental health among young adults. Psychiatry Q. 2018;89(2):307–314. https://doi.org/10.1007/s11126-017-9535-6.
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