Evidence map›Paper›PMID 42310612›Full record

ArticleBMC medical education2026

Integrating 3D skin lesion models with traditional 2D imagery in dermatology education: student perceptions within a VARK learning framework.

Chayada Chaiyabutr, Teerapat Paringkarn, Rungnapa Thongyoo, Pornpan Panjai, Penvadee Pattanaprichakul, Kanchalit Thanomkitti, Silada Kanokrungsee, Pattriya Jirawattanadon, Pichaya Limphoka, Somchai Chongpipatchaipron and 3 more

Abstract read
In one paragraph

Article in BMC 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

13 authors.

Chayada ChaiyabutrDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Teerapat ParingkarnDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Rungnapa ThongyooDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Pornpan PanjaiDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Penvadee PattanaprichakulDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Kanchalit ThanomkittiDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Silada KanokrungseeDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Pattriya JirawattanadonDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Pichaya LimphokaDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
Somchai ChongpipatchaipronMedical Education Technology Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Suriya LamsopaMedical Education Technology Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Kasem YimchaiMedical Education Technology Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Sumanas BunyaratavejDepartment of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand. consultskin@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDermatology education relies heavily on visual learning, yet students exhibit diverse learning preferences categorized by the VARK model: Visual (V), Auditory (A), Reading/Writing (R), and Kinesthetic (K). Traditional teaching utilizing two-dimensional (2D) images primarily benefits visual learners whilst lacking tactile engagement. Three-dimensional (3D) skin lesion models address this limitation by incorporating kinesthetic learning, thereby enhancing students' comprehension of lesion morphology and texture.

objectivesTo evaluate student perceptions and preferences regarding the integration of 3D skin lesion models with 2D images in a station-based dermatology learning approach.

resultsMost students (90.2%) preferred the combined approach utilizing both modalities. 2D images received marginally higher ratings than 3D models for diagnostic skill development (7.3 ± 3.0 vs. 6.8 ± 3.0) and clinical application (7.2 ± 3.0 vs. 6.7 ± 3.1). The primary advantages of 3D models were hands-on practice (74.5%), enhanced palpation skills (57.8%), and interactive learning opportunities.

conclusionsThe integration of 3D models with 2D images was well accepted by students and supports a multimodal learning approach aligned with VARK learning preferences. These findings suggest that 3D models may serve as a useful complementary tool in dermatology education. Further studies are needed to evaluate their impact on objective learning outcomes and clinical performance in diverse educational settings.

Indexed as

DermatologyEducation, Medical, UndergraduateImaging, Three-DimensionalModels, AnatomicSkin DiseasesStudents, MedicalClinical CompetenceFemaleHumansLearningMale3D skin lesion modelDermatologyEducationUndergraduateVARK

Identifiers

PMID42310612
PMCPMC13520452

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.