Chatbot as a psychological support tool: research review
Psychology
DOI:
https://doi.org/10.17072/2078-7898/2024-2-250-259%20Keywords:
chatbots, artificial intelligence, dialog agent, applied psychology, psychological aid, psychological health, psychological chatbot, digital technology, programs simulating the work of a psychotherapist, ChatGPT, mobile applicationsAbstract
This article is a review of theoretical research on the use of chatbots in applied psychology. It articulates the concept of a chatbot, describes the types of chatbot structure, lists the functions of this technology, and discusses its advantages and disadvantages. The paper provides some recommendations for developers concerning the design of chatbots intended for psychological support. The results of the study show that chatbots have significant possibilities for psychological support of users. Technology can act as virtual friends and assistants, help practice mindfulness, form useful habits, control and regulate emotional state, provide psychoeducation and post-rehabilitation psychological support, diagnose psychological problems. However, at this early stage, technology should not be regarded as an alternative to professional help. It is important to combine psychotherapy through chatbots with professional therapy, communication with a «real» therapist. In developing chatbots, it is important to establish the limits of the technology’s capabilities. Creators of chatbots should clearly indicate the purpose and expected limitations. In addition, technology should have features that schedule professional support and encourage users to seek professional help when needed.References
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References
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Adamopoulou, E. and Moussiades, L. (2020). An overview of chatbot technology. Proceedings of the 16th International Conference on Artificial Intelligence Applications and Innovations, AIAI ‘20 (Neos Marmaras, Greece, June 5–7, 2020). Cham, CH: Springer Publ., pp. 373–383. Available at: https://link.springer.com/chapter/10.1007/978-3-03049186-4_31 (accessed 26.04.2024).
Ahmed, A., Ali, N., Aziz, S., Abd-Alrazaq, A.A. et al. (2021). A review of mobile chatbot apps for anxiety and depression and their self-care features. Computer Methods and Programs in Biomedicine Update. Vol. 1. Available at: https://www.sciencedirect.com/science/article/pii/S26 66990021000112?via%3Dihub (accessed 23.04.2024). DOI: https://doi.org/10.1016/ j.cmpbup.2021.100012
Asensio-Cuesta, S., Blanes-Selva, V., Conejero, J.A., Frigola, A. et al. (2021). A usercentered chatbot (Wakamola) to collect linked data in population networks to support studies of overweight and obesity causes: design and pilot study. JMIR Medical Informatics. Vol. 9, iss. 4. Available at: https://medinform.jmir.org/2021/4/e17503/PDF (accessed 23.04.2024). DOI: https://doi.org/ 10.2196/17503
Bates, M. (2019). Health care chatbots are here to help. IEEE Pulse. Vol. 10, iss. 3, pp. 12–14. DOI: https://doi.org/10.1109/mpuls.2019.2911816
Battineni, G., Chintalapudi, N. and Amenta, F. (2020). AI chatbot design during an epidemic like the novel coronavirus. Healthcare (Basel). Vol. 8, iss. 2. Available at: https://www.mdpi.com/22279032/8/2/154/pdf?version=1591947503 (accessed 26.04.2024). DOI: https://doi.org/10.3390/ healthcare8020154
Denecke, K., Vaaheesan, S. and Arulnathan, A. (2021). A mental health chatbot for regulating emotions (SERMO) — concept and usability test. IEEE Transactions on Emerging Topics in Computing. Vol. 9, iss. 3, pp. 1170–1182. DOI: https://doi.org/10.1109/tetc.2020.2974478
Elmasri, D. and Maeder, A. (2016). A conversational agent for an online mental health intervention. Proceedings of the International Conference on Brain Informatics and Health, BIH ‘16 (Omaha, NE, USA, October 13–16, 2016). Cham, CH: Springer Publ., pp. 243–251. DOI: https://doi.org/10.1007/978-3319-47103-7_24
Fadhil, A. (2018). Can a chatbot determine my diet? Proceedings of the Addressing Challenges of Chatbot Application for Meal Recommendation. Feb. 25. Available at: https://www.researchgate.net/ publication/323410718_Can_a_Chatbot_Determine_ My_Diet_Addressing_Challenges_of_Chatbot_Application_for_Meal_Recommendation (accessed 26.04.2024). Fadhil, A., Schiavo, G., Wang, Y. and Yilma, B.A. (2018). The effect of emojis when interacting with conversational interface assisted health coaching system. Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth ‘18 (New York, USA, May 21–24, 2018). New York, Association for Computing Machinery Publ., pp. 378–83. DOI: https://doi.org/10.1145/3240925.3240965
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Inkster, B., Sarda, S. and Subramanian, V. (2018). An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: real-world data evaluation mixed-methods study. JMIR mHealth and uHealth. Vol. 6, iss. 11. Available at: https://mhealth.jmir.org/2018/11/e12106/PDF (accessed 25.04.2024). DOI: https://doi.org/10.2196/ 12106
Lee, M., Ackermans, S., As, N. van, Chang, H., Lucas, E. and IJsselsteijn, W. (2019). Caring for Vincent: a chatbot for self-compassion. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI ‘19 (Glasgow, Scotland, UK, May 4–9, 2019). Available at: https://minhalee.github.io/files/lee_vincent_chatbot_CHI2019.pdf (accessed 23.04.2024). DOI: https://doi.org/10.1145/3290605.3300932
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Valtolina, S. and Hu, L. (2021). Charlie: a chatbot to improve the elderly quality of life and to make them more active to fight their sense of loneliness. Proceedings of the 14th Biannual Conference of the Italian SIGCHI Chapter, CHItaly ‘21 (Bolzano, Italy, July 11– 13, 2021). New York: Association for Computing Machinery Publ. Available at: https://dl.acm.org/ doi/abs/10.1145/3464385.3464726 (accessed 23.04.2024). DOI: https://doi.org/10.1145/ 3464385.3464726
You, Y. and Gui, X. (2021). Self-diagnosis through AI-enabled chatbot-based symptom checkers: user experiences and design considerations. AMIA Annual Symposium Proceedings. Vol. 2021. Available at: https://arxiv.org/abs/2101.04796 (accessed 28.04.2024). Zhang, J., Oh, Y.J., Lange, P., Yu, Zh. and Fukuoka, Y. (2020). Artificial intelligence chatbot behavior change model for designing artificial intelligence chatbots to promote physical activity and a healthy diet: viewpoint. Journal of Medical Internet Research. Vol. 22, iss. 9. Available at: https://www.jmir.org/ 2020/9/e22845/PDF (accessed 28.04.2024). DOI: https://doi.org/10.2196/22845
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