Evidence map›Paper›PMID 42877487›Full record

ArticleHealth science reports2026

Predictors of Intentions to Learn and Adopt Medical Artificial Intelligence Among Healthcare Professionals in Ghana: A Descriptive Cross-Sectional Study.

Godwin Adzakpah, Daniel Kwame Kwansah Quansah, Mavis Puopelle Dakorah, Quaye Emmanuel, Lydia Korkor Djangmah, Gloria Prah, David Okyere, David Boateng Baah, Jessica Abakah, Eric Yaw Koranteng and 3 more

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Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Godwin AdzakpahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0000-0002-6916-6733
Daniel Kwame Kwansah QuansahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0009-0005-7004-5305
Mavis Puopelle DakorahDepartment of Medical Laboratory Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0000-0002-3522-0412
Quaye EmmanuelDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.
Lydia Korkor DjangmahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.
Gloria PrahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.
David OkyereDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0009-0005-5015-8695
David Boateng BaahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0009-0009-5632-8316
Jessica AbakahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.
Eric Yaw KorantengDepartment of Health Information Management University of Ghana Medical Centre Legon-Accra Ghana.ORCID https://orcid.org/0009-0005-4000-0384
Frederick TikoliDepartment of Health Information Management Pentecost Hospital Madina Accra Ghana.ORCID https://orcid.org/0009-0008-8137-1490
Samuel AntwiSchool of Public Health University of Ghana Accra Ghana.ORCID https://orcid.org/0009-0001-4230-9853
Nathan Kumasenu MensahDepartment of Health Information Management, College of Health and Allied Sciences, School of Allied Health Sciences University of Cape Coast Cape Coast Ghana.ORCID https://orcid.org/0000-0001-5333-589X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Effective integration of medical artificial intelligence (AI) into healthcare delivery requires healthcare professionals to possess the necessary knowledge and skills. This study examined factors associated with healthcare professionals' behavioural intentions to learn about and adopt medical AI in Ghana. Methods: An analytical cross-sectional study was conducted among 1131 healthcare professionals selected through systematic sampling between 15 October and 30 November 2023. Data were collected using a structured, self-administered questionnaire assessing personal relevance, social norms, self-efficacy, knowledge, behavioural intentions, and learning engagement related to medical AI. Data were entered using EpiData 3.2 and analysed in Stata 18 using descriptive statistics and structural equation modelling to identify significant predictors ( Results: Behavioural intention significantly predicted actual knowledge acquisition in medical AI ( Conclusion: The adoption of medical AI among healthcare professionals is predominantly shaped by behavioural intention, self-efficacy, knowledge, and social influences. Strategic interventions that strengthen self-efficacy, underscore the professional relevance of AI, and capitalise on prevailing social norms may serve as critical enablers in advancing AI integration within Ghana's healthcare sector.

Indexed as

artificial intelligenceattitude of health personnelGhanahealth personneltechnology adoption

Identifiers

PMID42877487
PMCPMC13662526

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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.