Evidence map›Paper›PMID 41104277›Full record

ArticleFrontiers in digital health2025

Healthcare providers' perception and knowledge of the use of artificial intelligence in healthcare service delivery in the Limbe and Buea Health Districts: a cross-sectional study.

Oliver Itoe, Francis Desire Tatsinkou Bomba, Odette Dzemo Kibu, Innocentia Ginyu Kwalar, Elvis Asangbeng Tanue, Denis Nkweteyim, Madeleine L Nyamsi, Peter L Achankeng, Christian Tchapga, Justine Ayuk and 6 more

Abstract read
In one paragraph

Article in Frontiers in digital health, 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. 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

16 authors.

Oliver ItoeDepartment of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Buea, Cameroon.
Francis Desire Tatsinkou BombaDepartment of Biomedical Sciences, Faculty of Health Sciences, University of Buea, Buea, Cameroon.
Odette Dzemo KibuDepartment of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Buea, Cameroon.
Innocentia Ginyu KwalarDepartment of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Buea, Cameroon.
Elvis Asangbeng TanueDepartment of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Buea, Cameroon.
Denis NkweteyimDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Madeleine L NyamsiDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Peter L AchankengDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Christian TchapgaDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Justine AyukDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Moise OnduaDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Patrick Jolly Ngono EmaDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Maurice Marcel SandeuDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Gregory Eddie Halle-EkaneDigiCare Cameroon Consortium, University of Buea, South West Region, Cameroon.
Jude Dzevela KongDepartment of Mathematics & Statistics, York University, Toronto, ON, Canada.
Dickson Shey NsaghaDepartment of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Buea, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial Intelligence (AI) in healthcare is rapidly growing in recent years, and has substantially improved the quality of care and health outcomes of patients. Understanding healthcare providers' perception and knowledge of AI in healthcare is crucial for its effective adoption, and its use. This study aimed to determine healthcare providers' awareness, assess their knowledge of healthcare AI, assess their perceived benefits, readiness to adopt AI in healthcare in Limbe and Buea Health Districts. Methods: A hospital-based cross-sectional study was conducted using a multi-staged sampling technique that recruited participants from seven hospitals in Limbe and Buea Health Districts. A questionnaire designed on koboCollect was used for data collection through face-to-face interviews from 494 participants recruited through a multi-stage sampling technique. The data was analyzed using SPSS version 26 where descriptive statistics and logistic regressions were done to determine the factors associated with readiness to adopt AI in healthcare. A Results: A total of 494 participants were recruited into the study with a mean age of 32.6 ± 7.5 years, the majority 355 (71.9%) were females, 448 (90.7%) had attained tertiary education and the highest proportion 295 (59.7%) were Nurses. The study revealed that 373 (75.5%) were aware of the use of AI in healthcare, 261 (52.8%) had used AI tools, 213 (43.1%) had good knowledge of healthcare AI, 283 (57.3%) had good perception of its benefits and 230 (46.6%) were ready to adopt its use. Those who had access to AI tools were about 5 times more ready to adopt AI use (AOR: 4.5, CI: 3.05-6.72, Conclusion: Healthcare providers' awareness and perceived benefits of AI use in healthcare were good, the knowledge was below average, and an average of the population were ready to adopt AI. Despite the benefits of AI, most of them fear AI will replace their jobs and believe training is important for the effective adoption of AI in healthcare.

Indexed as

artificial intelligenceCameroonhealthcarehealthcare providerperception

Identifiers

PMID41104277
PMCPMC12521128

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LicenceCC BY
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Registered trials

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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.