Чат-бот, как инструмент психологической поддержки: обзор исследований
Психология
DOI:
https://doi.org/10.17072/2078-7898/2024-2-250-259%20Ключевые слова:
чат-бот, искусственный интеллект, диалоговый агент, прикладная психология, психологическая помощь, психологическое здоровье, психологический чат-бот, цифровая технология, программы, имитирующие работу психотерапевта, ChatGPT, мобильные приложенияАннотация
Статья представляет собой обзор теоретических исследований, посвященных использованию чатботов в прикладной психологии. Раскрывается понятие чат-бот, описываются разновидности структуры чат-ботов, перечисляются функции данной технологии, рассматриваются преимущества и недостатки. Сформулированы некоторые рекомендации, которые можно использовать разработчикам в дизайне чат-ботов, направленных на психологическую поддержку. Результаты нашего исследования показывают, что чат-боты обладают значительными возможностями для психологической поддержки пользователей. Технология может выступать в качестве виртуальных друзей и помощников, помогает практиковать осознанность, формировать полезные привычки, контролировать и регулировать эмоциональное состояние, осуществлять психообразование, оказывать постреабилитационную психологическую поддержку, а также заниматься диагностикой психологических проблем. Однако на столь раннем этапе технологию не следует рассматривать как альтернативу профессиональной помощи. Психотерапию посредством чат-бота важно сочетать с профессиональной терапией, общением с психологом-человеком. При разработке чат-ботов важно установить границы возможностей технологии. Создателям чат-ботов необходимо четко указывать цели и предполагаемые ограничения чат-бота. Кроме того, технология должна иметь функции, которые планируют профессиональную поддержку и рекомендуют пользователям обращаться за помощью к профессионалам, когда это необходимо.Библиографические ссылки
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References
Abd-Alrazaq, A.A., Alajlani, M., Alalwan, A.A., Bewick, B.M., Gardner, P. and Househ, M. (2010). An overview of the features of chatbots in mental health: a scoping review. International Journal of Medical Informatics. Vol. 132. Available at: https://pubmed.ncbi.nlm.nih.gov/31622850/ (accessed 24.04.2024). DOI: https://doi.org/10.1016/ j.ijmedinf.2019.103978
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
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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
Fitzpatrick, K.K., Darcy, A. and Vierhile, M. (2017). Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial. JMIR Mental Health. Vol. 4, iss. 2. Available at: https://mental.jmir.org/2017/2/e19/PDF (accessed 26.04.2024). DOI: https://doi.org/10.2196/ mental.7785 Garg, S., Williams, N.L., Ip, A. and Dicker, A.P. (2018). Clinical integration of digital solutions in health care: an overview of the current landscape of digital technologies in cancer care. JCO Clinical Cancer Informatics. Vol. 2. Available at: https://ascopubs.org/doi/pdfdirect/10.1200/CCI.17.00 159 (accessed 28.04.2024). DOI: https://doi.org/10.1200/cci.17.00159
Huang, Ch.-Y., Yang, M.-Ch., Huang, Ch.-Y., Chen, Y.-J., Wu, M.-L. and Chen, K.-W. (2018). A chatbot-supported smart wireless interactive healthcare system for weight control and health promotion. Proceedings of the 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM ‘18 (Bangkok, Thailand, December 16–19, 2018). Bangkok, TH: IEEE Publ., pp. 1791–1795. DOI: https://doi.org/10.1109/ ieem.2018.8607399
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
Martinengo, L., Lum, E. and Car, J. (2022). Evaluation of chatbot-delivered interventions for selfmanagement of depression: content analysis. Journal of Affective Disorders. Vol. 319, pp. 598–607. DOI: https://doi.org/10.1016/j.jad.2022.09.028
Pentina, I., Hancock, T. and Xie, T. (2023). Exploring relationship development with social chatbots: A mixed-method study of replica. Computers in Human Behavior. Vol. 140. Available at: https://www.sciencedirect.com/science/article/abs/pii/ S0747563222004204 (accessed 24.04.2024). DOI: https://doi.org/10.1016/j.chb.2022.107600
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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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