Evidence map›Paper›PMID 37126349›Full record

ArticleJAMA network open2023

Perspectives of Youths on the Ethical Use of Artificial Intelligence in Health Care Research and Clinical Care.

Kelly Thai, Kate H Tsiandoulas, Elizabeth A Stephenson, Dolly Menna-Dack, Randi Zlotnik Shaul, James A Anderson, Alexis R Shinewald, Augustina Ampofo, Melissa D McCradden

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. [Artificial intelligence in preventive medicine for children and adolescents-applications and acceptance].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Kelly ThaiDepartment of Bioethics, The Hospital for Sick Children, Toronto, Ontario, Canada.
Kate H TsiandoulasDepartment of Bioethics, The Hospital for Sick Children, Toronto, Ontario, Canada.
Elizabeth A StephensonLabatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
Dolly Menna-DackHolland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada.
Randi Zlotnik ShaulDepartment of Bioethics, The Hospital for Sick Children, Toronto, Ontario, Canada.
James A AndersonDepartment of Bioethics, The Hospital for Sick Children, Toronto, Ontario, Canada.
Alexis R ShinewaldThe Hospital for Sick Children, Toronto, Ontario, Canada.
Augustina AmpofoThe Hospital for Sick Children, Toronto, Ontario, Canada.
Melissa D McCraddenDepartment of Bioethics, The Hospital for Sick Children, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Understanding the views and values of patients is of substantial importance to developing the ethical parameters of artificial intelligence (AI) use in medicine. Thus far, there is limited study on the views of children and youths. Their perspectives contribute meaningfully to the integration of AI in medicine. Objective: To explore the moral attitudes and views of children and youths regarding research and clinical care involving health AI at the point of care. Design, Setting, and Participants: This qualitative study recruited participants younger than 18 years during a 1-year period (October 2021 to March 2022) at a large urban pediatric hospital. A total of 44 individuals who were receiving or had previously received care at a hospital or rehabilitation clinic contacted the research team, but 15 were found to be ineligible. Of the 29 who consented to participate, 1 was lost to follow-up, resulting in 28 participants who completed the interview. Exposures: Participants were interviewed using vignettes on 3 main themes: (1) health data research, (2) clinical AI trials, and (3) clinical use of AI. Main Outcomes and Measures: Thematic description of values surrounding health data research, interventional AI research, and clinical use of AI. Results: The 28 participants included 6 children (ages, 10-12 years) and 22 youths (ages, 13-17 years) (16 female, 10 male, and 3 trans/nonbinary/gender diverse). Mean (SD) age was 15 (2) years. Participants were highly engaged and quite knowledgeable about AI. They expressed a positive view of research intended to help others and had strong feelings about the uses of their health data for AI. Participants expressed appreciation for the vulnerability of potential participants in interventional AI trials and reinforced the importance of respect for their preferences regardless of their decisional capacity. A strong theme for the prospective use of clinical AI was the desire to maintain bedside interaction between the patient and their physician. Conclusions and Relevance: In this study, children and youths reported generally positive views of AI, expressing strong interest and advocacy for their involvement in AI research and inclusion of their voices for shared decision-making with AI in clinical care. These findings suggest the need for more engagement of children and youths in health care AI research and integration.

Indexed as

Artificial IntelligenceMedicineAdolescentChildDecision Making, SharedEmotionsFemaleHumansMaleQualitative Research

Identifiers

PMID37126349
PMCPMC10152306

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.