ArticleBMC medical education2025
Exploring the digital competencies of clinical educators: a framework-based qualitative study.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Research Trends in Medical Teachers' Digital Literacy: A Bibliometric Analysis.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDigital transformation is reshaping healthcare education, requiring educators to demonstrate competence in digital teaching, patient care, and communication. Existing frameworks such as DigCompEdu, DigHealthCom, and UNESCO’s AI Competency Framework offer guidance, yet their suitability for clinical educators is not well established. This study explored how clinical educators integrate digital tools in teaching and practice, and examined strengths and gaps in their digital competencies through the lens of these frameworks.
methodsA qualitative, exploratory study with Semi-structured interviews was conducted, including clinical educators and comparative basic sciences educators from both public and private institutions. Questions informed by the DigCompEdu, DigHealthCom, and UNESCO artificial intelligence (AI) Competency Frameworks for teachers, examined the types of digital resources educators used and their confidence in applying these tools for teaching and learning and patient care. Thematic analysis revealed five major themes, which were mapped to the DigCompEdu, DigHealthCom, and UNESCO AI Competency frameworks, highlighting critical gaps in digital pedagogy, health communication, and AI literacy within clinical education settings.
resultsParticipants expressed varying levels of confidence and competence. Basic sciences educators were more confident in using structured tools such as LMS platforms and interactive apps, while clinicians tended to use WhatsApp, PowerPoint, or emails with limited integration into teaching practices, particularly deficient areas were student assessment and empowerment.
conclusionThis study highlights both strengths and gaps in the digital competencies of healthcare educators. While educators showed confidence in communication through mobile platforms, they lacked skills in resource creation, data literacy, student engagement and interaction with emerging technologies like artificial intelligence (AI). Basic sciences educators showed greater confidence in structured digital teaching, whereas clinical educators struggled with integrating technology, both into patient-centered contexts and teaching. The study underscores gaps in current digital competence frameworks and we advocate for inclusive, clinically grounded models that recognize and respond to the dual responsibilities of clinician-educators as teachers and caregivers.
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Registered trials
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.