Evidence map›Paper›PMID 42430717›Full record

ArticleJMIR medical education2026

e-Learning, Distance Education, and Virtual and Augmented Reality in Orthopedic Training: European Cross-Sectional Survey of Trainee Acceptance Guided by the Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology.

Adam Tibor Schlegl, Marko Ostojić, Ines Unterfrauner, Gianluca Ciolli, Panayiotis D Megaloikonomos, Vasilios G Igoumenou, Michele Mercurio, Thomas Stark, David Kordic, Martijn Dietvorst and 6 more

Abstract read
In one paragraph

Article in JMIR medical education, 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
–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

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

16 authors.

Adam Tibor SchleglDepartment of Orthopaedics, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0003-0349-2525
Marko OstojićTraumatology Department, University Hospital Sisters of Mercy, Zagreb, Croatia.ORCID 0000-0002-0108-5750
Ines UnterfraunerDepartment of Orthopedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-0116-574X
Gianluca CiolliDepartment of Orthopaedics and Traumatology, Agostino Gemelli University Polyclinic, Rome, Italy.ORCID 0000-0002-3653-4552
Panayiotis D MegaloikonomosFirst Department of Orthopaedic Surgery, Attikon University General Hospital, National and Kapodistrian University of Athens, Athens, Greece.ORCID 0000-0001-9509-6524
Vasilios G IgoumenouDepartment of Spine Surgery, Medius Klinik Nürtingen, Nürtingen, Germany.ORCID 0000-0003-2922-3980
Michele MercurioDepartment of Orthopedic and Trauma Surgery, "Renato Dulbecco" University Hospital, Magna Graecia University, Catanzaro, Italy.ORCID 0000-0002-8742-5612
Thomas StarkOrthopedics and Trauma Surgery Clinic, University Hospital of Basel, Basel, Switzerland.ORCID 0009-0009-4741-5151
David KordicDepartment of Orthopaedics, University Clinical Hospital Mostar, Mostar, Bosnia and Herzegovina.ORCID 0000-0003-0128-3754
Martijn DietvorstDepartment of Orthopaedic Surgery and Trauma, Máxima Medisch Centrum, Eindhoven, The Netherlands.ORCID 0000-0003-3581-287X
Filipe Lima SantosServiço de Ortopedia e Traumatologia, Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal.ORCID 0000-0002-5124-4449
Viktória NyakasDepartment of Orthopaedics, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0002-6284-7405
Luca TóthDepartment of Neurosurgery, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0002-5425-1863
András KomócsiHeart Centre, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0002-8170-1778
Péter MarótiMedical Skills Education and Innovation Centre, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0001-7538-0675
András MatuzDepartment of Behavioural Sciences, Medical School, University of Pecs, Pecs, Hungary.ORCID 0000-0002-4996-2732

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital technologies increasingly shape postgraduate medical education, yet orthopedic and trauma training face unique challenges because of the tactile, procedurally focused skills involved. Digital tools partially address these needs, but gaps remain, particularly across diverse European contexts.

objectiveOur primary aim was to quantitatively assess predictors of digital learning technology acceptance (e-learning, distance education, and virtual reality [VR] and augmented reality [AR]) among European orthopedic and trauma trainees, drawing on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) as conceptual guides. Specifically, we examined how perceived usefulness and perceived ease of use (TAM), alongside performance expectancy, effort expectancy, social influence, and facilitating conditions (UTAUT), related to trainees' acceptance of digital technologies. These constructs guided variable selection and grouping, attitudinal scale design, and interpretation of how individual and contextual factors shape acceptance of digital learning tools in orthopedic training. Secondary aims were to describe adoption and attitude patterns, identify attitudinal trainee profiles, and examine contextual associations (eg, workplace type and national gross domestic product [GDP]).

methodsWe distributed a multinational survey via European trainee federations and used validated scales to assess digital competence and attitudes and gathered demographic data (n=217 across 29 European countries). We administered the questionnaire in English; however, respondents who self-reported English proficiency below the intermediate level were excluded from the analyses to minimize potential comprehension-related bias. The survey assessed digital experience, self-reported digital competence, and attitudes toward e-learning, distance education, and VR/AR, and collected detailed demographic and workplace data. Expert review, cognitive pretesting, and pilot testing ensured validity and clarity. Analytical methods included Wilcoxon tests, ANOVA, clustering, multinomial logistic regression, and factor analysis to ensure the reliability and validity of attitudinal measures.

resultse-Learning technologies were the most widely adopted, whereas VR/AR tools were less frequently used despite high average attitude ratings (mean 4.07, SD 0.88). Cluster analysis identified 3 distinctive groups-enthusiastic, supportive, and hesitant-that differed significantly in digital competence and acceptance profiles. Digital competence and national GDP emerged as significant predictors of group membership, consistent with TAM/UTAUT expectations that perceived capability and contextual facilitating conditions shape acceptance. Variation in attitudes was further associated with workplace type and regional resource disparities, underscoring the influence of contextual factors on technology adoption.

conclusionsEuropean orthopedic trainees show broad support for digital innovations, preferring VR/AR despite low use. Preliminary evidence supports digital competence as a key mediator of acceptance, with GDP and workplace disparities predicting profiles (hesitant vs enthusiastic). Competence-first strategies and targeted resource equity (eg, low-GDP subsidies), together with policy adjustments, may address regional disparities. Future longitudinal and multimethod studies are needed to test causal pathways implied by TAM and UTAUT and to evaluate the generalizability of these findings across specialties and educational contexts.

Indexed as

Augmented RealityEducation, DistanceOrthopedicsVirtual RealityAdultCross-Sectional StudiesEuropeFemaleHumansMaleSurveys and Questionnairesaugmented realitydigital learningdistance educatione-learningmedical educationorthopedic trainingvirtual reality

Identifiers

PMID42430717
PMCPMC13401077

What OpenQuestion holds

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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.