Evidence map›Paper›PMID 40953442›Full record

ArticleJMIR infodemiology2025

Viewpoint on the Intersection Among Health Information, Misinformation, and Generative AI Technologies.

António Bandeira, Luis Henrique Gonçalves, Felix Holl, Juliet Ugbedeojo Shaibu, Mariana Laranjo Gonçalves, Ronan Payinda, Sagun Paudel, Alessandro Berionni, Young WFPHA, Tina D Purnat and 1 more

Abstract read
In one paragraph

Article in JMIR infodemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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

11 authors.

António BandeiraUnidade Local de Saúde Santo António, Unidade de Saúde Pública, Polo Gondomar, Porto, Portugal.ORCID https://orcid.org/0000-0001-7549-5982
Luis Henrique Gonçalves *Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0003-4226-4189
Felix Holl *DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany.ORCID https://orcid.org/0000-0002-4020-9509
Juliet Ugbedeojo Shaibu *Technical Advice Connect, Abuja, Nigeria.ORCID https://orcid.org/0009-0008-1995-4396
Mariana Laranjo Gonçalves *STARS Brazil Initiative (Students and Trainees Advocating for Resource Stewardship), Londrina, Brazil.ORCID https://orcid.org/0009-0003-1459-5519
Ronan Payinda *University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0009-0009-3665-3824
Sagun Paudel *Public Health Initiative, Kathmandu, Nepal.ORCID https://orcid.org/0000-0003-4244-6791
Alessandro BerionniWorld Federation of Public Health Associations, Geneva, Switzerland.ORCID https://orcid.org/0000-0002-6110-5557
Young WFPHA *World Federation of Public Health Associations, Geneva, Switzerland.
Tina D PurnatT.H. Chan School of Public Health, Harvard University, Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-0257-6631
Tim MackeyGlobal Health Program, Department of Anthropology, UC San Diego, La Jolla, CA, United States.ORCID https://orcid.org/0000-0002-2191-7833

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, artificial intelligence (AI) has seen rapid advancements, with innovations such as large language models and generative AI evolving at a rapid pace. While this progress offers tremendous opportunities, it also presents risks, particularly in the creation, consumption, and amplification of information and its impact on population health and health program delivery. Thoughtful approaches are necessary to navigate the consequences of advances in AI for different health care professionals and patient populations and from a policy and governance perspective. Through a collaboration between the World Federation of Public Health Associations working groups, this Viewpoint article brings together perspectives, concerns, and aspirations from young adult professionals across 5 continents and from diverse backgrounds to explore the future of public health and AI in the context of the changing health information environment. Our discussion is divided into 2 parts, specifically examining aspects of disinformation and AI, and also the role of public health and medical professionals in a growing AI-driven health information ecosystem. This Viewpoint concludes with 5 key recommendations on how to potentially address issues such as information and disinformation overload; misinformation propagation; and resultant changes in health practices, research, ethics, and the need for robust policies that can dynamically address current and future challenges.

Indexed as

Artificial IntelligenceCommunicationPublic HealthHumansgenerative artificial intelligenceHealth InformationinfodemicsMisinformationpublic health

Identifiers

PMID40953442
PMCPMC12481143

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.