Evidence map›Paper›PMID 41622167›Full record

ArticleBMC medical education2026

Virtual & mixed reality fatigue questionnaire.

Ana María Cintora-Sanz, Raúl Muñoz-Romo, Helmut Schrom-Feiertag, Alberto Blanco-Lara, Tatiana Vazquéz-Rodriguez, M Carmen Cardós-Alonso

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Ana María Cintora-SanzPrehospital Medical Emergency Service of Madrid Community SUMMA112, C/Antracita, nº2 bis, Madrid, 28045, Spain. anamaria.cintora@salud.madrid.org.
Raúl Muñoz-RomoPrehospital Medical Emergency Service of Madrid Community SUMMA112, C/Antracita, nº2 bis, Madrid, 28045, Spain.
Helmut Schrom-FeiertagDepartment of Artificial Intelligence and Human Interfaces, Austrian Institute of Technology Center for Technology Experience AIT, Giefinggasse 4, Vienna, 1210, Austria.
Alberto Blanco-LaraPrehospital Medical Emergency Service of Madrid Community SUMMA112, C/Antracita, nº2 bis, Madrid, 28045, Spain.
Tatiana Vazquéz-RodriguezPrehospital Medical Emergency Service of Madrid Community SUMMA112, C/Antracita, nº2 bis, Madrid, 28045, Spain.
M Carmen Cardós-AlonsoPrehospital Medical Emergency Service of Madrid Community SUMMA112, C/Antracita, nº2 bis, Madrid, 28045, Spain.

Funding

European Union's Horizon 2020 Research and Innovation Program 101021775
6 · The paper itself

Abstract

backgroundVirtual Reality (VR) generates an artificial environment in which users interact with computer-generated scenarios and sounds. Using devices such as headsets and motion sensors, users are immersed in a simulated world. Augmented reality (AR) is an interactive overlay of the real environment that provides an additional wrapper over the environment, and the user experiences an immersive and interactive environment. In Mixed reality (MR), VR and AR elements are combined; computer graphics interplay with real objects, allowing users to interact with virtual and physical objects at the same time. VR and MR are effective training tools in different healthcare settings. These tools are useful for preparing emergency health personnel to respond to disasters by providing them with an immersive reality since real practices are very difficult to implement in mass casualty incidents. Given the usefulness of this approach, assessing the optimal training times associated with this method and the side effects that may influence learning is helpful. One of the most common side effects is fatigue. We developed a questionnaire to assess fatigue in terms of various dimensions, that can affect a person while training in the context of VR and MR.

methodsWe designed a questionnaire to assess the fatigue levels perceived by professionals and validated this measure after VR training experience. We analyzed ratings of visual, mental, physical, and general fatigue. This questionnaire was applied to emergency professionals (Sample size = 101).

resultsThe reliability and validity of the questionnaire were assessed in terms of the following factors: general, social, emotional, visual, and motivational fatigue.

conclusionsThe results of this research suggest that fatigue is an element of VR and MR training. Educators should take these effects into account to optimize learning in the context of VR and MR. According to user feedback, the optimal length of time for mixed reality training is around 20 min, especially when the user has little or no experience.

Indexed as

FatigueVirtual RealityAdultFemaleHumansSurveys and QuestionnairesUser-Computer InterfaceEmergencies trainingFatigueQuestionnaireTrainingVirtual reality

Identifiers

PMID41622167
PMCPMC12958750

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.