Evidence map›Paper›PMID 40757093›Full record

Articlenpj health systems2025

Spotlighting healthcare frontline workers´ perceptions on artificial intelligence across the globe.

Henrique A Lima, Pedro H F S Trocoli-Couto, Marzia Zaman, Débora C Engelmann, Rosalind Parkes-Ratanshi, Leah Junck, Brenda Hendry, Amelia Taylor, Michelle El Kawak, Nirmal Ravi and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in npj health systems, 2025. 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

13 authors.

Henrique A LimaDepartment of Surgery, Federal University of Minas Gerais Faculty of Medicine, Belo Horizonte, Minas Gerais Brazil.
Pedro H F S Trocoli-CoutoDepartment of Surgery, Federal University of Minas Gerais Faculty of Medicine, Belo Horizonte, Minas Gerais Brazil.
Marzia ZamanCMED Health Limited, Dhaka, Bangladesh.
Débora C EngelmannInstitute of A.I. in Healthcare, Porto Alegre, RS Brazil.
Rosalind Parkes-RatanshiInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Leah JunckGlobal Center on AI Governance, Washington D.C, USA.
Brenda HendryUniversity of Dar es Salaam, Dar es Salaam, Tanzania.
Amelia TaylorKuyesera AI Lab, Malawi University of Business and Applied Sciences, Thyolo, Malawi.
Michelle El KawakHumanitarian Engineering Initiative, Faculty of Health Sciences and Maroun Semaan Faculty of Engineering and Architecture, American University of Beirut, Beirut, Lebanon.
Nirmal RavieHealth Africa; EHA Clinics, Kano, Nigeria.
Henrique D P SantosInstitute of A.I. in Healthcare, Porto Alegre, RS Brazil.
Timothy M PawlikDepartment of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH USA.
Vivian ResendeDepartment of Surgery, Federal University of Minas Gerais Faculty of Medicine, Belo Horizonte, Minas Gerais Brazil.ORCID 0000-0003-4400-0427

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We sought to define healthcare workers' (HCW) views on the integration of generative artificial intelligence (AI) into healthcare delivery and to explore the associated challenges, opportunities, and ethical considerations in low- and middle-income countries (LMICs). We analysed unified data from selected 2023 Gates Foundation AI Grand Challenges projects using a mixed-methods, cross-sectional survey evaluated by an international panel across eight countries. Perceptions were rated on a simplified three-point Likert scale (sceptical, practical, enthusiastic). Among 191 frontline HCWs who interacted with AI tools, 617 responses were assessed by nine evaluators. Enthusiastic responses accounted for the majority (75.4%), while 21.6% were practical and only 3.0% were sceptical. The overall interclass correlation coefficient of 0.93 (95%CI: 0.91-0.94, with an average rating

Indexed as

Developing worldHealth care

Identifiers

PMID40757093
PMCPMC12310525

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.