PERCEIVED THERAPEUTIC BOND IN INTERACTIONS WITH MENTAL HEALTH CHATBOTS: A NARRATIVE REVIEW
DOI:
https://doi.org/10.31435/ijitss.3(51).2026.5767Keywords:
Mental Health, Therapeutic Alliance, Therapeutic Bond, Conversational Agents, Digital Mental Health Interventions, Human–AI InteractionAbstract
Background: The rapid development of digital mental health interventions has led to the increasing use of AI-based chatbots as accessible alternatives or complements to traditional psychotherapy. While the therapeutic alliance is a well-established factor influencing treatment outcomes in conventional settings, its applicability to human–chatbot interactions remains unclear.
Objective: This narrative review aims to examine existing evidence regarding the subjective experience of therapeutic bond in interactions with mental health chatbots and to explore its characteristics and potential clinical relevance.
Methods: A narrative review of selected literature was conducted using databases such as PubMed and Google Scholar. Studies focusing on users’ subjective experiences and relational aspects of interaction with conversational agents were included.
Results: Available evidence suggests that users can develop a form of therapeutic bond with mental health chatbots, characterized by perceived empathy, support, and emotional engagement. Both quantitative and qualitative studies indicate that users may attribute human-like qualities to chatbots and describe interactions in relational terms. However, the intensity and nature of this bond vary across individuals, with some users perceiving the interaction as purely instrumental. The bond appears to be limited in depth and may lack key features of traditional therapeutic relationships, such as reciprocity and genuine emotional responsiveness.
Conclusions: Therapeutic bond in chatbot-based interventions may represent a distinct and simplified form of relational engagement shaped by the characteristics of human–AI interaction. Further research is needed to assess its long-term development and its relationship to clinical outcomes.
References
World Health Organization. (2022). World mental health report: Transforming mental health for all. https://www.who.int/publications/i/item/9789240049338
Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt-Jepsen, M., Whelan, P., Carvalho, A. F., Keshavan, M., Linardon, J., & Firth, J. (2021). The growing field of digital psychiatry: Current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry, 20(3), 318–335. https://doi.org/10.1002/wps.20883
Fitzpatrick, K. K., Darcy, A., & 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, 4(2), e19. https://doi.org/10.2196/mental.7785
Xu, Z., Lee, Y. C., Stasiak, K., Warren, J., & Lottridge, D. (2025). The digital therapeutic alliance with mental health chatbots: Diary study and thematic analysis. JMIR Mental Health, 12, e76642. https://doi.org/10.2196/76642
Weizenbaum, J. (1966). ELIZA—A computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45. https://doi.org/10.1145/365153.365168
Bickmore, T., & Picard, R. (2005). Establishing and maintaining long-term human-computer relationships. ACM Transactions on Computer-Human Interaction, 12(2), 293–327. https://doi.org/10.1145/1067860.1067867
Bordin, E. S. (1979). The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy: Theory, Research & Practice, 16(3), 252–260. https://doi.org/10.1037/h0085885
Flückiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy, 55(4), 316–340. https://doi.org/10.1037/pst0000172
Inkster, B., Sarda, S., & Subramanian, V. (2018). An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: Real-world study. JMIR mHealth and uHealth, 6(11), e12106. https://doi.org/10.2196/12106
Hatcher, R. L., & Gillaspy, J. A. (2006). Development and validation of a revised short version of the Working Alliance Inventory. Psychotherapy Research, 16(1), 12–25. https://doi.org/10.1080/10503300500352500
Fulmer, R., Joerin, A., Gentile, B., Lakerink, L., & Rauws, M. (2018). Using psychological artificial intelligence (Tess) to relieve symptoms of depression and anxiety: Randomized controlled trial. JMIR Mental Health, 5(4), e64. https://doi.org/10.2196/mental.9782
Pentina, I., Xie, T., & Hancock, T. (2023). Exploring relationship development with social chatbots: A longitudinal study of Replika. Computers in Human Behavior, 140, 107569. https://doi.org/10.1016/j.chb.2022.107600
Provoost, S., Lau, H. M., Ruwaard, J., & Riper, H. (2017). Embodied conversational agents in clinical psychology: A scoping review. Journal of Medical Internet Research, 19(5), e151. https://doi.org/10.2196/jmir.6553
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Copyright (c) 2026 Wojciech Markiewicz, Maria Marusińska, Michał Karpiński, Michał Parzniewski, Wiktoria Czyż, Sabina Kolawa, Natalia Ostruszka, Arnold Borowiec, Julia Pilecka, Jędrzej Wojciechowski

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