Empowering pediatric, adolescent, and young adult patients with cancer utilizing generative AI chatbots to reduce psychological burden and enhance treatment engagement: a pilot study
Open accessAbstract
Background: Pediatric and adolescent/young adult (AYA) cancer patients face profound psychological challenges, exacerbated by limited access to continuous mental health support. While conventional therapeutic interventions often follow structured protocols, the potential of generative artificial intelligence (AI) chatbots to provide continuous conversational support remains unexplored. This study evaluates the feasibility and impact of AI chatbots in alleviating psychological distress and enhancing treatment engagement in this vulnerable population. Methods: Two age-appropriate AI chatbots, leveraging GPT-4, were developed to provide natural, empathetic conversations without structured therapeutic protocols. Five pediatric and AYA cancer patients participated in a two-week intervention, engaging with the chatbots via a messaging platform. Pre- and post-intervention anxiety and stress levels were self-reported, and usage patterns were analyzed to assess the chatbots’ effectiveness. Results: Four out of five participants reported significant reductions in anxiety and stress levels post-intervention. Participants engaged with the chatbot every 2–3 days, with sessions lasting approximately 10 min. All participants noted improved treatment motivation, with 80% disclosing personal concerns to the chatbot they had not shared with healthcare providers. The 24/7 availability particularly benefited patients experiencing nighttime anxiety. Conclusions: This pilot study demonstrates the potential of generative AI chatbots to complement traditional mental health services by addressing unmet psychological needs in pediatric and AYA cancer patients. The findings suggest these tools can serve as accessible, continuous support systems. Further large-scale studies are warranted to validate these promising results.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Individual studies have investigated generative AI support for pediatric and young adult patients.
“generative AI support for pediatric and young adult patients”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017) · JMIR Mental Health · doi:10.2196/mental.7785 · Cited by 2,730 · see citing works
Fiske, A., Henningsen, P., & Buyx, A. (2019) · Journal of Medical Internet Research · doi:10.2196/13216 · Cited by 857 · see citing works
Large Language Models for Mental Health Applications: Systematic Review
Guo, Z., Lai, A., Thygesen, J. H., Farrington, J., Keen, T., & Li, K. (2024) · JMIR Mental Health · doi:10.2196/57400 · Cited by 269 · see citing works
Epidemiology and genetics of childhood cancer
Stiller, C. A. (2004) · Oncogene · doi:10.1038/sj.onc.1207717 · Cited by 243 · see citing works
Zhong, W., Luo, J., & Zhang, H. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.04.057 · Cited by 204 · see citing works
The now and future of ChatGPT and GPT in psychiatry
Cheng, S., Chang, C., Chang, W., Wang, H., Liang, C., Kishimoto, T., Chang, J. P., Kuo, J. S., & Su, K. (2023) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13588 · Cited by 197 · see citing works
Towards Interpretable Mental Health Analysis with Large Language Models
Yang, K., Ji, S., Zhang, T., Xie, Q., Kuang, Z., & Ananiadou, S. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.370 · Cited by 155 · see citing works
Hokkanen, H., Eriksson, E., Ahonen, O. M., & Salanterä, S. (2004) · Cancer Nursing · doi:10.1097/00002820-200407000-00010 · Cited by 138 · see citing works
Patients' reasons for not presenting emotional problems in general practice consultations.
Cape, J. D., & McCulloch, Y. (1999) · PubMed · Cited by 119 · see citing works
Communication during childhood cancer: Systematic review of patient perspectives
Lin, B., Gutman, T., Hanson, C. S., Ju, A., Manera, K., Butow, P. N., Cohn, R. J., Dalla‐Pozza, L., Greenzang, K. A., Mack, J. W., et al. (2019) · Cancer · doi:10.1002/cncr.32637 · Cited by 118 · see citing works
The Art of Age-Appropriate Care
Fern, L. A., Taylor, R. M., Whelan, J. S., Pearce, S., Grew, T., Brooman, K., Starkey, C., Millington, H., Ashton, J., & Gibson, F. (2013) · Cancer Nursing · doi:10.1097/ncc.0b013e318288d3ce · Cited by 110 · see citing works
Anxiety and sleep disorders in cancer patients
Trill, M. D. (2013) · European Journal of Cancer Supplements · doi:10.1016/j.ejcsup.2013.07.009 · Cited by 107 · see citing works
Conrad, M. M., & Pacquiao, D. F. (2004) · Journal of Transcultural Nursing · doi:10.1177/1043659604271239 · Cited by 87 · see citing works
Strategy for randomised clinical trials in rare cancers
Tan, S. B., Dear, K. B. G., Bruzzi, P., & Machin, D. (2003) · BMJ · doi:10.1136/bmj.327.7405.47 · Cited by 83 · see citing works
van Heerden, A. C., Pozuelo, J. R., & Kohrt, B. A. (2023) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2023.1253 · Cited by 72 · see citing works
Zhou, E., Kyeong, Y., Cheung, C. S.-S., & Michalska, K. J. (2021) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-021-01073-w · Cited by 53 · see citing works
On artificial intelligence and global mental health
Montag, C., Ali, R., Al‐Thani, D., & Hall, B. J. (2023) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2023.103855 · Cited by 40 · see citing works
Ma, Z., Mei, Y., & Su, Z. (2023) · arXiv · doi:10.48550/arxiv.2307.15810 · Cited by 40 · see citing works
Human–Robot Interactions and Affective Computing: The Ethical Implications
Devillers, L. Y. (2021) · Springer eBooks · doi:10.1007/978-3-030-54173-6_17 · Cited by 34 · see citing works
Artificial Intelligence: A Game-Changer for Mental Health Care
Dakanalis, A., Wiederhold, B. K., & Riva, G. (2024) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2023.0723 · Cited by 32 · see citing works
How Can Digital Mental Health Enhance Psychiatry?
Stern, É., Micoulaud‐Franchi, J., Dumas, G., Moreira, J., Mouchabac, S., Maruani, J., Philip, P., Lejoyeux, M., & Geoffroy, P. A. (2022) · The Neuroscientist · doi:10.1177/10738584221098603 · Cited by 31 · see citing works
Adebayo, Y. O., Adesiyan, R. E., Amadi, C. S., Ipede, O., Karakitie, L. O., & Adebayo, K. T. (2024) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2024.23.1.2040 · Cited by 31 · see citing works
Li, X., Hathaway, C. A., Small, B. J., Tometich, D. B., Gudenkauf, L. M., Hoogland, A. I., Fox, R. S., Victorson, D. E., Salsman, J. M., Gonzalez, B. D., et al. (2024) · Cancer · doi:10.1002/cncr.35508 · Cited by 30 · see citing works
Poudel, P. G., Bauer, H. E., Srivastava, D. K., Krull, K. R., Hudson, M. M., Robison, L. L., Wang, Z., & Huang, I. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.21.00044 · Cited by 24 · see citing works
Guțu, S., Cosmoiu, A., Cojocaru, D., Turturescu, D., Popoviciu, C. M., & Giosan, C. (2021) · Annals of Depression and Anxiety · doi:10.26420/anndepressanxiety.2021.1107 · Cited by 14 · see citing works
Artificial intelligence is set to transform mental health services
Pandi-Perumal, S. R., Narasimhan, M., Seeman, M. V., & Jahrami, H. (2023) · CNS Spectrums · doi:10.1017/s1092852923002456 · Cited by 14 · see citing works
Choi, H., Kim, B., Kim, I., Kang, J.-G., Lee, Y., Lee, H. K., & Park, M.-H. (2023) · Journal of korean Academy of Child and Adolescent Psychiatry · doi:10.5765/jkacap.230044 · Cited by 12 · see citing works
ChatGPT, Artificial Intelligence, and Suicide Prevention
Arendt, F., Till, B., Voracek, M., Kirchner, S., Sonneck, G., Naderer, B., Pürcher, P., & Niederkrotenthaler, T. (2023) · Crisis · doi:10.1027/0227-5910/a000915 · Cited by 12 · see citing works
Elyoseph, Z., Gur, T., Haber, Y., Simon, T., Angert, T., Navon, Y., Tal, A., & Asman, O. (2024) · doi:10.2196/preprints.58011 · Cited by 11 · see citing works
Villarino, R. T., & Villarino, M. L. (2023) · International Journal of Psychology and Psychoanalysis · doi:10.23937/2572-4037.1510062 · Cited by 2 · see citing works
What type of information is needed by AYA cancer survivors in Japan?
Yamaki, C., Nakatani, Y., Sato, T., Taniguchi, H., & Takayama, T. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.2019.37.15_suppl.e23165 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [1]Gautam Poudel P Bauer HE Wang Z Huang IC. Social relationships and patient-reported outcomes in adolescent and young adult cancer survivors. medRxiv. (2020):10.30.20223271. 10.1101/2020.10.30.20223271 PMC8812647 34415790 · DOI
- [12]OpenAI, Achiam J Adler S Agarwal S Ahmad L Akkaya I GPT-4 technical report. arXiv [cs.CL]. (2023). Available online at: http://arxiv.org/abs/2303.08774 · arXiv
Cited by
Sorted by citations
Shaban, M., Osman, Y. M. M., Mohamed, N. A., & Shaban, M. M. (2025) · BMC Nursing · doi:10.1186/s12912-025-03585-w · Cited by 20 · see citing works
Digital Conversational Agents for the Mental Health of Treatment-Seeking Youth: Scoping Review
Hawke, L. D., Hou, J., Nguyen, A. T. P., Phi, T., Gibson, J., Ritchie, B., Strudwick, G., Rodak, T., & Gallagher, L. (2025) · JMIR Mental Health · doi:10.2196/77098 · Cited by 12 · see citing works
Assiry, A. A., Alrehaili, R. S., Mahnashi, A., Alkam, H., Mahdi, R., Hakami, R., Alshammakhy, R., Almallahi, W., Alhawsah, Y., & Khalil, A. S. (2025) · Prosthesis · doi:10.3390/prosthesis7050119 · Cited by 10 · see citing works
Artificial intelligence in oncology: promise, peril, and the future of patient–physician interaction
Thind, B. S., & Tsao, C.-K. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1633577 · Cited by 10 · see citing works
Risks and Harms of Conversational Artificial Intelligence (CAI) Chatbot Use Among US Youth
Hinduja, S., & Patchin, J. W. (2026) · Journal of Adolescence · doi:10.1002/jad.70164 · Cited by 9 · see citing works
Shankar, R., Lim, A., & Xu, Q. (2026) · Healthcare · doi:10.3390/healthcare14101267 · Cited by 9 · see citing works
Saxena, A. K., Prasad, R. V., & Laha, S. (2025) · International Journal of Information Technology · doi:10.1007/s41870-025-03042-6 · Cited by 3 · see citing works
Slepian, P. M., Buryk-Iggers, S., Lomanowska, A. M., Nguyen, B., Janmohamed, T., Clarke, H. A., Katz, J., & Niederstrasser, N. G. (2026) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/87689 · Cited by 1 · see citing works
A scoping review on conversational AI in mental health: A human-centered perspective
Li, J., Li, H., Zhu, H., Walter, H., Banaschewski, T., Li, C., Li, X., & Zhang, Y. (2026) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2026.106460 · Cited by 1 · see citing works
Jeong, Y., Cha, H., & Suh, E. E. (2026) · JMIR Cancer · doi:10.2196/96241 · Cited by 1 · see citing works
Menz, B. D., Scarfo, N. L., Cornelisse, E., Shahnam, A., Chin-Yee, B. H., Rickard, C., Haseloff, M., Lau, A. Y. S., Ugalde, A., Paterson, C. C., et al. (2026) · European Journal of Cancer · doi:10.1016/j.ejca.2026.116990 · Cited by 1 · see citing works
Wang, Y., Romy, R. W., Deng, Y., & Chen, X. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1916780 · Cited by 1 · see citing works
Shalbaf, N., Ahmadi, N., Nasirimehr, K., & Emami, A. (2025) · InfoScience Trends · doi:10.61186/ist.202502.04.06 · Cited by 1 · see citing works
Leveraging Foundation Models in Maternal and Child Health: A Systematic ReviewPreprint
Mai, X., Liu, Y., Chung, P., Reiss, J. D., Zhou, S., Wong, R. J., Lin, M., Marić, I., Sirota, M., Aghaeepour, N., et al. (2025) · medRxiv · doi:10.1101/2025.08.29.25333768 · Cited by 1 · see citing works
Shen, Z., Shi, S., Mao, L., Li, C., & Xie, J. (2026) · Journal of Medical Internet Research · doi:10.2196/105599
Dormitory Student Persona Development for A Generative AI Chatbot System
Tambunan, S. R., Simaremare, M. E. S., Simamora, A. N., Hutahaean, C., & Simamora, E. (2025) · International Conference on Informatics and Computing (ICIC) · doi:10.1109/icic68054.2025.11309523
Li, H. Y., & Cheung, H. N. (2026) · British Journal of Clinical Psychology · doi:10.1111/bjc.70087
Service-Based Village Information System with Artificial Intelligence (AI) Chatbot
Murhadi, Saputro, W. T., Jumasa, H. M., Pasa, I. Y., Chirzah, D., & Sa'diah, H. (2025) · International Conference on ICT for Smart Society (ICISS) · doi:10.1109/iciss66954.2025.11389421
Hanzawa, M., Hasei, J., Okada, A., Tanaka, C., Shigeyasu, Y., Fujii, C., Horiuchi, M., Sugihara, A., Takeuchi, K., Nakahara, R., et al. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1759690
Self-citationHodson, A., Schmidt-Waselenchuk, K., Batson, J., Duckman, A., & Roberts, J. (2026) · Canadian Journal of School Psychology · doi:10.1177/08295735261425560
Artificial Intelligence Agents in Mental Health: A Systematic Review and Meta AnalysisPreprint
Zhu, L., Wang, W., Liang, Z., Tan, W., Chen, B., Lin, X., Yu, H., Yu, H., Li, X., Jiao, J., et al. (2026) · medRxiv · doi:10.64898/2026.04.21.26351365
Künstliche Intelligenz in der Psychoonkologie – Anwendungsmöglichkeiten und Implikationen
Sauer, C., Maatouk, I., & Haussmann, A. (2026) · Die Onkologie · doi:10.1007/s00761-026-01939-w
Jeong, Y., Cha, H., & Suh, E. (2026) · doi:10.2196/preprints.96241
Sun, Y., Huang, C., Kang, H., Wu, K., Jin, Z., Chen, C., Liao, M., Wang, B., Chen, X., & Zhang, G. (2026) · doi:10.2196/preprints.97136
Human Shadows in Machine Minds: Quantitative Study Interpreting AI Responses to the Rorschach Test
Csigó, K., & Cserey, G. (2026) · JMIR Mental Health · doi:10.2196/88186
Sun, Y., Huang, C., Kang, H., Wu, K., Jin, Z., Chen, C., Liao, M., Ou, W., Wang, B., Chen, X., et al. (2026) · Journal of Medical Internet Research · doi:10.2196/97136
Clinical implementation of artificial intelligence in adolescent mental healthcare
Bischops, A., Kavanaugh, J. R., & Bickham, D. S. (2026) · Current Opinion in Pediatrics · doi:10.1097/mop.0000000000001584
The Intersection of Social Work and AI: Shaping the Future of Pediatric Mental Health
Pliske, M. M. (2026) · Families in Society The Journal of Contemporary Social Services · doi:10.1177/10443894261448395
Triantafyllidis, A. K., Segkouli, S., Lithoxoidou, E. E., Alexiadis, A., Votis, K., Koutra, K., Kilintzis, V., Kondylakis, H., Arana‐Arri, E., Haug, S., et al. (2026) · Information · doi:10.3390/info17080770
Ennassiri, A., ENNASSIRI, S., Bakkari, F. E., Sadiki, H., & Fadili, S. (2026) · International Conference on Circuit, Systems and Communication (ICCSC) · doi:10.1109/iccsc71566.2026.11650536
Kırca, Ö., Çakır, M. O., Kaya, M. S., Kurt, B., Yilmaz, B., Bilge, U., & Ozdogan, M. (2026) · Biomedicines · doi:10.20944/preprints202609.0010.v1
Hou, J.-R., & Ismiati, M. B. (2026) · Information Systems Frontiers · doi:10.1007/s10796-026-10814-3
Kusumaningrum, A. B., Kusnadi, G., & Wangge, G. (2026) · Clinical Child Psychology and Psychiatry · doi:10.1177/13591045261490266
Friedrich, P., Obremski, D., Latoschik, M. E., & Wienrich, C. (2026) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3776574.3831112
Advance Care Planning for Adolescents and Young Adults with Cancer: A Clinical Review
Gorlick, J., Shanmugiavelayutham, S., Jarrell, J. A., Crawford, C., Roy, J., Kim, R. M., Deeter, A., Fetzko, S., & McEvoy, M. T. (2026) · Children · doi:10.3390/children13101405
- Authors
- Hasei, J., Hanzawa, M., Nagano, A., Maeda, N., Yoshida, S., Endo, M., Yokoyama, N., Ochi, M., Ishida, H., Katayama, H., Fujiwara, T., Nakata, E., Nakahara, R., Kunisada, T., Tsukahara, H., & Ozaki, T.
- Affiliations
- Okayama University (JP)
- Okayama University Hospital (JP)
- Gifu University (JP)
- Nagoya Medical Center (JP)
- Tohoku University (JP)
- Kyushu University (JP)
- Corresponding author
- Hasei, Joe
- ORCID
- Venue
- Frontiers in Digital Health
- Publisher
- Frontiers Media SA
- Published
- 2025-02-25
- Volume
- 7
- Pages
- 1543543-1543543
- ISSN
- 2673-253X (ISSN-L)
- PMC
- PMC11893593
- OpenAlex
- W4407929073
- Cited by
- 34
- References
- 31
- Citations by year
- 2026: 25 · 2025: 9
- FWCI
- 27.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Digital Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Okayama University Scientific Achievement Repository (Okayama University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion, cc-by)
- Funders
- Wesco Science Foundation
- Japan Society for the Promotion of Science (23K08632, 23K08700)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- generative AI chatbots, childhood cancer, adolescent and young adult cancer, psychological distress, anxiety, stress, treatment engagement, GPT-4, feasibility
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
