Evidence map›Paper›PMID 37361442›Full record

ArticleDigital health

Knowledge and perception of primary care healthcare professionals on the use of artificial intelligence as a healthcare tool.

Queralt Miró Catalina, Aïna Fuster-Casanovas, Josep Vidal-Alaball, Anna Escalé-Besa, Francesc X Marin-Gomez, Joaquim Femenia, Jordi Solé-Casals

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 5 pooled it
2.3field-weighted citation impact, top 9% of its field
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

33 citing papers in PubMed, 5 syntheses or guidelines pooled it, 60 citations in OpenAlex.

  1. Atencion primaria · 2026
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. AI and Primary Care: Scoping Review.Journal of medical Internet research · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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 at 2 institutions in 2 countries.

Queralt Miró CatalinaUnitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.ORCID https://orcid.org/0000-0001-7379-4671
Aïna Fuster-CasanovasUnitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.
Josep Vidal-AlaballUnitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.
Anna Escalé-BesaUnitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.
Francesc X Marin-GomezUnitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.
Joaquim FemeniaFaculty of Medicine, University of Vic-Central University of Catalonia, Vic, Spain.
Jordi Solé-CasalsData and Signal Processing group, Faculty of Science, Technology and Engineering, University of Vic-Central University of Catalonia, Vic, Spain.ORCID https://orcid.org/0000-0002-6534-1979
Institut Universitari d'Investigació en Atenció Primària Jordi Gol · ESUniversitat de Vic - Universitat Central de Catalunya · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The rapid digitisation of healthcare data and the sheer volume being generated means that artificial intelligence (AI) is becoming a new reality in the practice of medicine. For this reason, describing the perception of primary care (PC) healthcare professionals on the use of AI as a healthcare tool and its impact in radiology is crucial to ensure its successful implementation. Methods: Observational cross-sectional study, using the validated Shinners Artificial Intelligence Perception survey, aimed at all PC medical and nursing professionals in the health region of Central Catalonia. Results: The survey was sent to 1068 health professionals, of whom 301 responded. And 85.7% indicated that they understood the concept of AI but there were discrepancies in the use of this tool; 65.8% indicated that they had not received any AI training and 91.4% that they would like to receive training. The mean score for the Conclusions: The results of this study show that the majority of professionals understood the concept of AI, perceived its impact positively, and felt prepared for its implementation. In addition, despite being limited to a diagnostic aid, the implementation of AI in radiology was a high priority for these professionals.

Indexed as

Artificial intelligencedigital healthknowledgeperceptionprimary caresurveytechnology

Identifiers

PMID37361442
PMCPMC10286543
OpenAlexW4380682381

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.