ArticleTechnical innovations & patient support in radiation oncology2022
Screen-based digital learning methods in radiation oncology and medical education.
Article in Technical innovations & patient support in radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Fill the VOID- an introductory guide for learning medical imaging.BMC medical education · 2026Article
- Enhancing radiographic interpretation: effects of gamification on medical students' knowledge, skills, and satisfaction - a quasi-experimental study.BMC medical education · 2025Article
- The feasibility of a patient oriented interactive panoramic virtual tour for external beam radiation therapy.Frontiers in oncology · 2025Article
- Students' perception and self-efficacy in blended learning of medical nutrition course: a mixed-method research.BMC medical education · 2024Article
- Scholarship in radiation oncology education.Technical innovations & patient support in radiation oncology · 2023Article
- Virtual reality and augmented reality in radiation oncology education - A review and expert commentary.Technical innovations & patient support in radiation oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The field of radiation oncology is rapidly advancing through technological and biomedical innovation backed by robust research evidence. In addition, cancer professionals are notoriously time-poor, meaning there is a need for high quality, accessible and tailored oncological education programs. Digital learning (DL) is well-placed to cater to these needs, as it provides teaching options that can be delivered flexibly and on-demand from anywhere in the world. The evidence for usage of these techniques in medical education has expanded rapidly in recent years. However, there remains many reservations in the oncological community to adopting and developing DL, largely due to a poor familiarity with the pedagogical evidence base. This article will review the application of the screen-based DL tools that are at educators' disposal. It will summarize best-practice in developing tailored, made-for-screen videos, gamification, and infographics. It also reviews data behind the following practical tips of 1) strategically combining text with graphics to decrease cognitive load, 2) engaging users through use of interactive elements in digital content, and 3) maximizing impact through thoughtful organization of animations/images. Overall, the digital space evolving is well placed to cater to the evolving educational needs of oncology learners. This review and its practical tips aim to inspire further development in this arena, production of high-yield educational products, use of engaging delivery methods and programs that are tailored to individual learning needs.
Indexed as
Identifiers
What OpenQuestion holds
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.