Mind and Machine: Exploring the New Era of Synergetic Care through Artificial Intelligence and Emotional Intelligence
DOI:
https://doi.org/10.31305/rrijm.2026.v11.n09.005Keywords:
Artificial Intelligence, Artificial Emotional Intelligence, Emotional Intelligence, Mental Health Care, Therapeutic Alliance, Human–AI Collaboration, StudentsAbstract
Artificial Intelligence (AI) has transformed daily life across multiple domains, and its emotionally attuned extension, Artificial Emotional Intelligence (AEI), is increasingly reshaping mental health care by supporting symptom tracking, diagnostic pattern recognition, and clinical decision-making. Yet mental health treatment remains fundamentally relational, grounded in therapeutic alliance, empathy, and trust that machines cannot fully replicate. This qualitative descriptive study examined how emerging adult students training in health sciences, psychology, and social work envision the collaboration between AI/AEI tools and human clinicians. Ten purposively sampled participants (5 male, 5 female; aged 18–25) took part in semi-structured, audio-recorded interviews lasting 45–60 minutes, following a pilot with three additional participants. Data were analyzed using Braun and Clarke's (2006) six-phase thematic analysis. Six themes emerged: AI offers clarity and speed; human connection is irreplaceable; shared decision-making feels balanced; emotional safety needs human guidance; synergy is the future; and the role of artificial emotional intelligence is assistive rather than substitutive. Findings supported all four guiding hypotheses: students viewed AI/AEI as enhancing assessment efficiency, regarded human emotional connection as foundational and irreplaceable, favored a collaborative human–AI care model, and expressed ethical concerns regarding privacy, data handling, and algorithmic bias. The results converge on a synergetic model in which AI/AEI augments, rather than replaces, clinician judgment. Implications for AI/AEI literacy, relational training, ethical safeguards, and curriculum development for future mental health professionals are discussed.
References
[1] Ali, M., Ali, S., Abbas, Q., Abbas, Z., & Lee, S. W. (2025). Artificial intelligence for mental health: A narrative review of applications, challenges, and future directions in digital health. Digital Health, 11. https://doi.org/10.1177/20552076251395548 DOI: https://doi.org/10.1177/20552076251395548
[2] Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469–480. https://doi.org/10.1037/0003-066X.55.5.469 DOI: https://doi.org/10.1037/0003-066X.55.5.469
[3] Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa DOI: https://doi.org/10.1191/1478088706qp063oa
[4] Choudhury, M. D., Chhabra, A., & Kumar, N. (2020). The impact of technology on mental health. Journal of Behavioral Informatics, 10(2), 55–72.
[5] Fisher, C. E. (2025). The real ethical issues with AI for clinical psychiatry. International Review of Psychiatry, 37(1), 14–20. https://doi.org/10.1080/09540261.2024.2376575 DOI: https://doi.org/10.1080/09540261.2024.2376575
[6] Ho, M.-T., Mantello, P., & Vuong, Q.-H. (2024). Emotional AI in education and toys: Investigating moral risk awareness in the acceptance of AI technologies from a cross-sectional survey of the Japanese population. Heliyon, 10(15), Article e36251. https://doi.org/10.1016/j.heliyon.2024.e36251 DOI: https://doi.org/10.1016/j.heliyon.2024.e36251
[7] Kumar, N., Sharma, R., & Patel, A. (2020). Advances in AI for mental health. Mental Health Technology Review, 12(1), 12–23.
[8] Meyer, B., Ajchenbrenner, M., & Bowles, D. P. (2021). Emotional intelligence and therapeutic outcomes: A review of the literature. Journal of Clinical Psychology, 77(3), 552–563.
[9] MIT Sloan School of Management. (2026, January 29). Emotion AI, explained. MIT Sloan Ideas Made to Matter. https://mitsloan.mit.edu/ideas-made-to-matter/emotion-ai-explained
[10] Norcross, J. C., & Lambert, M. J. (2018). Relationship in psychotherapy: An integrative approach. American Psychologist, 73(1), 74–89. https://doi.org/10.1037/amp0000257 DOI: https://doi.org/10.1037/amp0000257
[11] Picard, R. W. (1997). Affective computing. MIT Press. DOI: https://doi.org/10.7551/mitpress/1140.001.0001
[12] Putica, A., Khanna, R., Bosl, W., Saraf, S., & Edgcomb, J. (2025). Ethical decision-making for AI in mental health: The Integrated Ethical Approach for Computational Psychiatry (IEACP) framework. Psychological Medicine, 55, Article e213. https://doi.org/10.1017/S0033291725101311 DOI: https://doi.org/10.1017/S0033291725101311
[13] Rony, M. K. K., Numan, S. M., Akter, K., Tushar, H., Debnath, M., Johra, F. T., Akter, F., Mondal, S., Das, M., Uddin, M. J., Begum, J., & Parvin, M. R. (2024). Nurses' perspectives on privacy and ethical concerns regarding artificial intelligence adoption in healthcare. Heliyon, 10(16), Article e36702. https://doi.org/10.1016/j.heliyon.2024.e36702 DOI: https://doi.org/10.1016/j.heliyon.2024.e36702
[14] Sandelowski, M. (2000). Whatever happened to qualitative description? Research in Nursing & Health, 23(4), 334–340. https://doi.org/10.1002/1098-240X(200008)23:4<334::AID-NUR9>3.0.CO;2-G DOI: https://doi.org/10.1002/1098-240X(200008)23:4<334::AID-NUR9>3.0.CO;2-G
[15] Sharp, G. (2025). Perceived barriers and facilitators of use of artificial intelligence in eating disorder care: A commentary on Linardon et al. (2025). International Journal of Eating Disorders. https://doi.org/10.1002/eat.24426 DOI: https://doi.org/10.1002/eat.24426
[16] Topol, E. J. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
