Evidence map›Paper›PMID 40070545›Full record

ArticleFrontiers in digital health2025

Empowering pediatric, adolescent, and young adult patients with cancer utilizing generative AI chatbots to reduce psychological burden and enhance treatment engagement: a pilot study.

Joe Hasei, Mana Hanzawa, Akihito Nagano, Naoko Maeda, Shinichirou Yoshida, Makoto Endo, Nobuhiko Yokoyama, Motoharu Ochi, Hisashi Ishida, Hideki Katayama and 6 more

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Joe HaseiDepartment of Medical Information and Assistive Technology Development, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Mana HanzawaDepartment of Pediatrics, Okayama University Hospital, Okayama, Japan.
Akihito NaganoDepartment of Orthopedic Surgery, Gifu University Graduate School of Medicine, Gifu, Japan.
Naoko MaedaDepartment of Pediatrics, NHO National Hospital Organization Nagoya Medical Center, Nagoya, Japan.
Shinichirou YoshidaDepartment of Orthopedic Surgery, Tohoku University Graduate School of Medicine, Sendai, Japan.
Makoto EndoDepartment of Orthopedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Nobuhiko YokoyamaDepartment of Orthopedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Motoharu OchiDepartment of Pediatrics, Okayama University Hospital, Okayama, Japan.
Hisashi IshidaDepartment of Pediatrics, Okayama University Hospital, Okayama, Japan.
Hideki KatayamaDepartment of Palliative and Supportive Care, Okayama University Hospital, Okayama, Japan.
Tomohiro FujiwaraScience of Functional Recovery and Reconstruction, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Eiji NakataScience of Functional Recovery and Reconstruction, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Ryuichi NakaharaScience of Functional Recovery and Reconstruction, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Toshiyuki KunisadaScience of Functional Recovery and Reconstruction, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Hirokazu TsukaharaDepartment of Pediatrics, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Toshifumi OzakiScience of Functional Recovery and Reconstruction, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

adolescent and young adult (AYA)generative AI chatbotlarge language modelpediatric cancerpsychological support

Identifiers

PMID40070545
PMCPMC11893593

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.