Evidence map›Paper›PMID 42286506›Full record

ArticleBMC pediatrics2026

Children and adolescents' views on artificial intelligence in pediatric healthcare: a qualitative focus group study.

Lisa Reinhart, Janna-Lina Kerth, Anne C Bischops, Maurus Hagemeister, Lisa Krassuski, Ertan Mayatepek, Thomas Meissner

Abstract read
In one paragraph

Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Lisa ReinhartDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany. lisa.reinhart@med.uni-duesseldorf.de.
Janna-Lina KerthDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.
Anne C BischopsDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.
Maurus HagemeisterDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.
Lisa KrassuskiDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.
Ertan MayatepekDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.
Thomas MeissnerDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, Medical Faculty, University Hospital Duesseldorf, Heinrich-Heine-University, Moorenstr. 5, Duesseldorf, 40227, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe increased use of artificial intelligence (AI) in healthcare, including pediatrics, offers significant opportunities for improving quality, personalization, and effectiveness of care. Nevertheless, successful implementation of this approach in pediatric patients depends on their acceptance and the integration of their preferences regarding AI use within participatory decision-making. Since previous research insufficiently addresses the perspectives of children and adolescents on AI use in pediatric healthcare, the objective of this study was to address this research gap.

methodsThis qualitative study was conducted at the University Children's Hospital Duesseldorf, Germany, and in surrounding schools. Recruitment took place from March to September 2024. Semi-structured interviews including two scenarios were conducted: an AI-based application (1) for assessing the development of children and adolescents, (2) for supporting and monitoring children and adolescents with chronic conditions. Content analysis was used to evaluate information.

resultsEighteen focus group interviews with 58 participants (8-11 years = 10; 12-14 years = 23; 15-17 years = 25) were conducted. Nine key topics emerged: benefits, fears, dealing with misdiagnoses of AI, responsibility for data input and access, impact on the physician-patient relationship, the right not to know, transparency, data sources, and desired features. Participants repeatedly emphasized that AI should serve only as a supportive tool, with healthcare professionals retaining final authority and critically evaluating its findings. Key benefits included early detection of health anomalies and reduced diagnostic or human errors. Barriers to acceptance encompassed data privacy concerns, suspected lack of empathy, absence of physical examination, and risk of false diagnoses.

conclusionsThis qualitative study underlines, that the requirements, perceived benefits, and concerns of AI-based applications in pediatric healthcare are multifaceted and necessitate including minors in their development and implementation. Age-appropriate education on AI use, risks, limitations, opportunities and strengths is essential for acceptance. If possible, minors should be openly informed about the limitations of AI decision transparency, with underlying mechanisms explained where appropriate. At best, children and adolescents should already be involved in development of AI applications in terms of information and consent.

trial registrationThis study was retrospectively registered in the German Clinical Trials Registry (DRKS00034474; 17th June 2024).

Indexed as

Artificial IntelligenceAttitude to HealthPediatricsAdolescentChildFemaleFocus GroupsGermanyHumansMalePhysician-Patient RelationsQualitative ResearchArtificial intelligenceChildren and adolescentsFocus group interviewsHealthcarePediatricsQualitative research

Identifiers

PMID42286506
PMCPMC13267202

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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.