Evidence map›Paper›PMID 42812395›Full record

ArticleFrontiers in digital health2026

Decoding digital transformation in health professions education: a comparative analysis of knowledge, attitudes, and readiness among faculty and students at KSAU-HS.

Amal I Khalil, Lamyaa Y ALyaba, Amnah M Jambi

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In one paragraph

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

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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

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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

3 authors.

Amal I KhalilKing Abdullah International Medical Research Center, Jeddah, Saudi Arabia.
Lamyaa Y ALyabaKing Abdullah International Medical Research Center, Jeddah, Saudi Arabia.
Amnah M JambiKing Abdullah International Medical Research Center, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital transformation is altering educational processes in health professions and needs instructors and students to acquire competencies for its implementation. At the same time, comparative information about readiness for digital transformation for educators and students in Saudi Arabian universities is scarce and the reasons for such readiness are not fully known. This study reviewed the knowledge, attitude and readiness of instructors and learners at King Saud bin Abdulaziz University for Health Sciences. Methods: The study used a cross-sectional comparative design. Data was collected from the respondents with the help of a specially designed questionnaire, based on the Technology Acceptance Model. The questionnaire measured digital competency, perceived usefulness and ease of use and facilitating conditions. Results: Respondents displayed a slightly more developed level of digital competence, perceived usefulness, perceived ease of use, and readiness for digital transformation. As for students, motivation and confidence in one's ability to work with digital technologies turned out to be the best predictors. Structural equation modeling has validated that usefulness and ease of use along with facilitating conditions represent significant factors for predicting the intention to use digital technologies. Hence, psychology and organizational aspects play a bigger role in being ready for the digital transformation than demographic variables. Discussion: The readiness for digital transformation in health professions education relates to not only the technical aspect but also to individual motivation, confidence, and institutional backing. Therefore, universities should develop specific strategies to motivate and encourage students to learn, along with training faculty, giving sufficient resources, and offering suitable organizational conditions.

Indexed as

digital competencedigital transformationfacultyhealth professions educationreadinessSEMstudentstechnology acceptance model

Identifiers

PMID42812395
PMCPMC13619956

What OpenQuestion holds

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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.