Evidence map›Paper›PMID 40374852›Full record

ReviewJournal of cancer education : the official journal of the American Association for Cancer Education2026

Enhancing Radiation Oncology Delineation Skills Through Simulation-Based Learning (SBL): A Five-Step Practical Approach Using the ADDIE Model.

Hany S Attallah, Rania Abdelghani, Omayma Hamed

Abstract readReview
In one paragraph

Review in Journal of cancer education : the official journal of the American Association for Cancer 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

3 authors.

Hany S AttallahRadiation Oncology, AFCM, Cairo, Egypt. hanysamy2006@yahoo.com.ORCID 0000-0002-1969-5645
Rania AbdelghaniDermatology, Armed Forces College of Medicine, Cairo, Egypt.ORCID 0000-0002-1590-8375
Omayma HamedMedical Education, AFCM, Cairo, Egypt.ORCID 0000-0001-9050-5966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation of radiotherapy treatment setup is an integral part of the daily radiation oncology practice. Hence, simulation-based learning (SBL) plays a critical role in radiation oncology resident training. Such practical training approach enhances the precision of tumor delineation and the organs at risk (OARs), thus, directly influencing treatment efficacy and patient safety. Our review explores the application of the ADDIE (analysis, design, development, implementation, and evaluation) model in developing and implementing an SBL program of delineation skills training for the radiation oncologists. In this review, we discussed the phases of the ADDIE model as follows: analysis to determine the skills gap, design to tailor the training program to incorporate the advanced technology methods, development targets creating practical case scenarios and assessment tools, implementation assures the real-time feedback and the model-based debriefing sessions, and finally evaluation phase that employs the Kirkpatrick model. The application of the ADDIE model in SBL emphasizes that the training aligns with the educational needs. This enhances the clinical performance, and consequently, improves patient outcomes in radiation oncology. Applying the ADDIE model in SBL achieves the educational needs in radiation oncology delineation skills training, which will lead to enhance the clinical performance.

Indexed as

Clinical CompetenceModels, EducationalNeoplasmsRadiation OncologySimulation TrainingHumansInternship and ResidencyADDIE modelDelineation skillsRadiation oncologySBL

Identifiers

PMID40374852
PMCPMC13222235

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.