Virtual & Mixed Reality Fatigue Scale

Virtual & Mixed Reality Fatigue Scale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Virtual & Mixed Reality Fatigue Scale Ana María Cintora-Sanz, Paula Sanchiz-Torres, Alberto Blanco-Lara, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4251601/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Feb, 2026 Read the published version in BMC Medical Education → Version 1 posted 11 You are reading this latest preprint version Abstract Background : Virtual reality (VR) and mixed reality (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 during 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 scale to assess fatigue in terms of various dimensions that can affect a person while training in the context of VR and MR. Methods: We designed a questionnaire to assess the fatigue levels perceived by professionals and validated this measure after a VR training experience. We analyzed ratings of visual, mental, physical, and general fatigue. This questionnaire was applied to emergency professionals (n=66). Results: The reliability and validity of the scale were assessed in terms of the following factors: general, social, emotional, visual, and motivational fatigue. Conclusions : The results of this research suggest that fatigue is an element of VR training. Educators should take these effects into account to optimize learning in the context of MR. virtual reality fatigue scale training mixed reality simulation Highlights Headset-based virtual training simulation modalities yield fatigue symptoms. The Virtual and mixed reality fatigue scale can value the different fatigue profiles. Virtual reality training can cause visual fatigue, general fatigue, and decreased concentration afterwards. The optimal time for the mixed reality training is about 20 minutes, depending on the user experience. Background Virtual reality (VR) is an emerging technology that has become increasingly prominent as an effective and efficient training tool in different healthcare settings (Liu et al., 2023 ; Ifanov et al., 2023; Barteit et al., 2021 ) since it was first introduced more than 56 years ago (Gutiérrez-Maldonado, 2022 ). The use of this technology offers many benefits (Woon et al., 2021 ) (Allcoat et al., 2021 ); however, not all of these benefits are advantageous. Thus, we observe important side effects of this type of innovative training, including so-called "virtual reality disease" (Cometti et al., 2018 ; Gabbard et al., 2019 ; Shrestha et al., 2019 ; Lim et al., 2022 ; Souchet et al., 2023 ). About this syndrome, we focus on the symptom of fatigue, a concept that features different dimensions. Fatigue has been widely studied in other situations (Smets et al., 1995 ; Dittner et al., 2004 ; Quintana et al., 2022 ). One area of study related to this broad concept has been its relationship with the use of other new technologies, specifically concerning digital platforms (Nadler, 2020 ; Wiederhold, 2020 ; Fauville et al., 2021 ). However, given that our search did not reveal any articles that focused on measuring fatigue in the context of training in VR and mixed reality (MR), we designed a questionnaire to evaluate the level of fatigue perceived by professionals in this context. We validated this measure in the context of health emergencies after the use of VR and MR. The questionnaire developed values for the scope of fatigue and assessed both previous experiences using VR, and the training time associated with this technology as factors that may affect the degree and intensity of fatigue in terms of its various dimensions. Sample Participants: Sixty-six out-of-hospital emergency nurses, physicians and technicians from the Emergency Medical Service of Madrid who attended the SUMMA112 Mass Casualty Incident (MCI) course. This course featured a VR segment lasting 15 minutes (the maximum time). A nonprobabilistic convenience sampling approach was used for this research. First, the participants received information regarding this research and signed an informed consent form. Subsequently, they engaged in VR exercises with the assistance of Oculus Quest 2 goggles® and HoloLens® technology. The SUMMA112 professionals had previously participated in earlier versions of the Mass Casualty Incidents course as part of their ordinary corporate training. We performed the VR procedures using two heads-mounted displays (Oculus goggles® and HoloLens®) technologies indiscriminately. We freely invited participants in the VR practices to evaluate and complete the questionnaires. Method A review of the literature concerning this topic was performed. The concept of fatigue is complex and multifaceted (Dukes et al., 2021 ). The North American Nursing Diagnostic Association (NANDA) established a working definition of fatigue that identifies it as a feeling of exhaustion that is associated with a decreased capacity for physical and mental work (Voith et al.; J., 1989) (Quintana et al., 2022 ). To align our work on MR with the definition provided by NANDA, we define MR fatigue as a feeling of exhaustion that results from participating in MR activities. To account for the mental and physical aspects of fatigue, the Multidimensional Fatigue Inventory was examined (Smets et al., 1995 ). This questionnaire represents one of the most widely used scales to measure fatigue and includes five constructs. Fauville outlined (2021) in the Zoom and Exhaustion Fatigue Scale (ZEF), five fatigue dimensions. In the experts group, four dimensions of interpersonal interaction of fatigue that could be present in a MR experience were selected. The first dimension involves the manner in which people express their fatigue is primarily through the phrase "I feel tired". Accordingly, general fatigue refers to the general experience of being tired. The second dimension, according to Fauville et al. ( 2021 ), concerns how people express their physical fatigue as another construct related to fatigue. Third, people can experience fatigue in the form of difficulty concentrating, and "mental fatigue" refers to these cognitive symptoms related to fatigue. The fourth dimension of fatigue included in the Multidimensional Fatigue Inventory, i.e., “reduced motivation”, involves a lack of motivation to engage in any task linked to fatigue. Finally, Smets et al. ( 1995 ) identified “reduced activity” as the fifth dimension of fatigue, in which context a decreased level of activity emerges frequently, which we associated with the time that people need to recover from the MR experience. This previous research helps us understand which aspects of MR could lead to MR fatigue. Therefore, these five dimensions of fatigue could contribute to our understanding of MR fatigue. As participating in MR entails visual immersion using a head-mounted screen, the associated visual fatigue might represent another important dimension of MR fatigue. Moreover, engaging in MR training alongside other professionals involves social interactions and speech. McCarthy & Saegert ( 1978 ) proposed the concept of social overload based on the negative impact of crowded places that characterizes this type of training on the stress associated with properly addressing an MCI in a timely manner. In the present paper, we present the development and validation of the MR & Fatigue Scale (MR Scale), which aims to assess the fatigue associated with MR use. A descriptive and exploratory study focused on the validation of a fatigue questionnaire was conducted by experts by following the suggestions of Fehring (Fehring, 1987 ) and employing the Delphi technique. This method used expert group validation as a basis for confirming the validity of the scale. The inclusion criteria limited the participants to emergency professionals (nurses, doctors, technicians or experts involved in health emergencies). Experts were defined as individuals who achieved a minimum score of 6 points in terms of the criteria proposed by Quatrini et al. (2016), namely, academic level and clinical, teaching and research experience related to critical healthcare, which represented the training content. After various meetings were conducted and a consensus was reached among members of the research team and external experts in fatigue (the council of experts), the final items to be included in the scale were confirmed. The data collection process took place between January and December 2023. Our goal was to develop a tool that took into account both the psychological and physical aspects of fatigue related to VR and MR use. To validate the fatigue scale, a study featuring a quantitative approach and a nonexperimental design was conducted following the procedures associated with the adaptation of the ZEF scale and the development of the proposed Virtual and Mixed Reality Fatigue Scale with the goal of obtaining evidence of the measure’s validity and reliability. The data thus obtained were analyzed by reference to the content validity index, correlation values, internal consistency, and the results of a factor analysis. DEVELOPMENT OF THE RESEARCH In Table 1 , we present the Virtual and Mixed Reality Fatigue Scale. Table 1 . Fatigue Scale for Virtual and Mixed Reality QUESTION ANSWER 1 Do you feel fatigued after using virtual and/or mixed reality? 1–2–3–4–5 2 Are you experiencing musculoskeletal discomfort such as neck pain or tension? 1–2–3–4–5 3 Do you experience visual discomfort, such as pain, blurred vision, dryness, or irritation, after using virtual and/or mixed reality,? 1–2–3–4–5 4 Do you feel that you need time alone with yourself after using virtual and/or mixed reality? 1–2–3–4–5 5 Do you experience difficulty maintaining attention and concentration after using virtual and/or mixed reality? 1–2–3–4–5 6 Do you feel too tired to do other things after using virtual and/or mixed reality? 1–2–3–4–5 7 Do you feel emotionally drained after using virtual and/or mixed reality? 1–2–3–4–5 8 How irritable do you feel after using virtual and/or mixed reality? 1–2–3–4–5 9 How often do you participate in virtual or mixed reality training sessions? 1. Never 2. Approximately once per month 3. Approximately once per week 4. Approximately once per day 5. Several times, more than once per day 10 In your opinion, a mixed reality training session (with glasses) should not exceed…? 1. 15 minutes 2. 20 minutes 3. 25 minutes 4. 30 minutes 5. 35 minutes 11 Do you consider the utilization of virtual reality to enhance the learning process to be necessary and/or useful? 1. Extremely necessary/useful 2. Very necessary/useful 3. Moderately necessary/useful 4. Slightly necessary/useful 5. Not necessary/useful at all Each question from 1 to 8 was scored on the following five-point Likert scale: 1. Not at all. 2. Slightly 3. Moderately 4. A lot 5. Extremely Procedure: The Virtual and Mixed Reality Fatigue Scale was employed considering the ethical factors related to this research and ensuring that individuals could participate in this research in a voluntary, pseudoanonymous and confidential manner. Data analysis: A confirmatory factor analysis (CFA) was performed using the maximum likelihood method. Finally, Cronbach's alpha coefficients were calculated to determine the reliability of the factors and the complete scale. The data were analyzed using SPSS V.28.0 software. Results Table 2 shows the frequency of the results obtained by analyzing the various items included in the questionnaires. Table 2 . Descriptive Statistic Percentage for the Items Included in the Virtual and Mixed Reality Scale Do you suffer from general fatigue after engaging in VR training sessions? Do you experience musculoskeletal complaints such as neck pain or muscle tension after using VR? Do you notice any visual symptoms, such as ocular pain, after using VR? Do you seek to spend a quiet and isolated time alone after using VR? Do you experience difficulty maintaining attention and/or concentration after using VR? Do you experience excessive tiredness when performing other tasks after using VR? Not at all (%) 40.9 83.3 56.1 81.8 69.7 80.3 Slight (%) 30.3 10.6 27.3 10.6 25.8 16.7 Moderate (%) 22.7 4.5 10.6 6.1 4.5 3 Severe (%) 6.1 1.5 4.5 1.5 0 0 Extreme 0 0 1.5 0 0 0 An analysis of the data revealed that after training in MCI using VR technology, 58% of the students suffered fatigue of some kind, which was generally mild but was severe in 6% of cases. More than 80% of the students did not experience any muscle discomfort, pain, tension, etc., or report any physical complaints after completing the proposed MCI exercises using VR, and among students who did notice some discomfort, the majority (10.6%) reported mild discomfort. One case of severe discomfort was recorded after the simulation. In terms of eye discomfort, such as eye pain, blurred vision, and eye strain, 83% of the students did not suffer any or suffered only very mild eye discomfort after the simulation, while 16.6% of the students experienced moderate or severe eye discomfort. The majority of the students (82%) did not need to spend time in isolation or solitude after the exercise to recover from this strain. A total of 30% of the students reported difficulty maintaining attention and/or concentration after using the head-mounted display, and 18% of students exhibited excessive tiredness after participating in the virtual MCI training. In line with the other results, more than 15% of the participants reported irritation after the virtual training, with a similar proportion of students feeling emotionally drained. Table 3 shows the results regarding participants’ previous experience in virtual or MR, 85% of the volunteers had never used VR or MR, 11% reported using it once per week, and 4% reported using it daily. A total of 82% of the participants identified the length of VR training ranging from 15 to 20 minutes as adequate. A minority of 9% of the participants would prefer to double the training time. Table 3 Descriptive Statistic Percentage for the MR trainees experience, the more adequate time training according to user experience and the perceived usability of the MR professional training How often do you practice virtual or mixed reality? How much time do you consider, in general, more suitable for training with mixed reality glasses? Do you think it is important/useful to use mixed/virtual reality to improve learning in Mass Casualty Incident training? Never 84.8% Until 15 minutes 39.40% Extremely important 0 Approximately once a month 10.6% Until 20 minutes 42.4% Very important 31.8% Approximately once a week 0 Until 25 minutes 9.1% Moderately important 53% Approximately once a day 4.5% Until 30 minutes 9.1% Slightly important 15.2% Several times a day 0 Until 35 minutes 0 Not important at all 0 Psychometric Analysis Based on the data analysis, the model exhibited the following fit indices: X2 = 61.10, gl = 69, X2/gl = 1.08, p < .01; CFI = .71, IFI = .72, GFI = .65, AGFI = .81, NFI = .73, RMR = .06 and RMSEA = .05. According to psychometric literature, the data support the construct validity of the Fatigue Scale. Similarly, the model was parsimonious, i.e., it was obtained without changing the identified scale and the errors did not exhibit covariance. The reliability of the total scale remained the same; however, the factor data exhibited slight changes that were not considered to be significant. When we asked the participants about the usefulness of this technology in terms of its ability to enhance the learning process, 15.2% considered it to be moderately important, 53% considered it to be very important, and 31.8% considered it to be extremely important; no participants evaluated this pedagogical tool as exhibiting little value. The use of a methodology based on VR/MR in attempts to instruct health staff in how to respond to incidents involving multiple victims is acceptable in terms of the fatigue it produces. This approach can be an interesting teaching tool if the proper training time to obtain optimal results is taken into account and if secondary effects are avoided as much as possible. This approach represents an improvement over current and traditional training methods and is more effective in the long term due to its increased capacity to generate immersive simulations that can offer students in MCI courses the most realistic experience of the task of performing in the context of an MCI. 15% of the participants who frequently used VR suffered less fatigue than people who were experiencing VR for the first time, especially for eye-related symptoms, emotional symptoms and irritation. Physical discomfort and other negative factors can most likely be mitigated if healthcare professionals are accustomed to the use of VR/MR. In most cases, these data were obtained from healthcare professionals who are not accustomed to VR. This hypothesis can be confirmed by additional studies that can corroborate this trend. Finally, it is helpful to explore the prevalence of fatigue when different MR devices are used. Another factor that should be considered in the future is fatigue affectation, particularly about whether fatigue levels change based on the purpose of MR use, such as whether this approach is used for training at the professional level, as in the case, or for entertainment-related purposes. Measurements in these different environments may vary due to a variety of factors, such as the responsibility associated with learning in the professional environment or the increased challenge of interpreting visual data in an immersive environment. The type of headset display used in this context can influence the results of such a fatigue evaluation based on the immersive experience of the field trial and its quality. More studies should be conducted to investigate this issue in the future. Conclusions It has not been found in the extant literature exploration of the different fatigue dimensions that can affect the optimal use of interactive mixed-reality learning for health professionals. It has been validated the Virtual and Mixed Reality Fatigue Scale, that is valid in detecting the general, social, emotional, visual, and motivational dimensions of fatigue: The fatigue scale for VR and MR fulfills several objectives; on the one hand, it provides a method for subjectively measuring experienced fatigue in the context of this training model and makes it possible to optimize various aspects such as the duration of training or the experience of well-being in the context of MR, thus allowing us to make this approach more effective. The duration of the VR activity was also identified as a decisive factor that influenced the results obtained by applying the fatigue scale. Despite the emergence of mild symptoms, users identified a duration of 15–20 minutes as optimal for an immersive VR experience. In conclusion, it is crucial to establish a balance among immersion, influencing factors and fatigue to optimize participants’ experience in these environments. Given the increase in the use of new technologies, such as VR, this work is focused on determining the validity of a questionnaire used to measure fatigue when these technologies are used. After controlling for certain variables, data were collected to adapt this questionnaire and observe participants’ responses to MR training fatigue. The VR and MR Fatigue Scale includes validated constructs about physical and mental fatigue. The test is a valid measurement of the fatigue items that were proposed. The increase in the use of this technology requires these measurements to perform the best professional training using MR. Declarations Ethics approval and consent to participate All methods were carried out in accordance with relevant guidelines and regulations. The study was approved by the Ethics Committee of the University of Cultural and Behavioral Studies Heidelberg under registration no. AZ Beu 2023 1/1. The informed consent was obtained from all subjects that participated in the research. Consent for publication Not applicable. Data availability The data and materials are available at https://bit.ly/DatabaseSUMMA112ValidationFatigueResearch Competing interests The authors declare that they have no competing interests. Funding This research is supported by the European project MED1stMR (Medical First Responder Training using a Mixed Reality Approach featuring haptic feedback for enhanced realism). Med1stMR project is funded by the European Union's Horizon 2020 Research and Innovation Program with the Grant agreement Nº 101021775. Acknowledgments The authors acknowledge the operational support provided by Sara Pérez García (FIIBAP). Authors’ contributions AMCS, PST, ABL, TVR, SHS and CCA were involved in the conception and design of the work. AMCS, PST and CCA contributed to the screening process, data extraction and quality assessment of papers; ABL and AMCS interpreted the data. AMCS, PST, TVR, SHS, MRL and CCA drafted the manuscript, ABL prepared tables 1 and 2 and AMCS prepared table 3. The manuscript was critically reviewed and enriched with medical expertise by ABL and MRL, with psychological expertise by SP; and with technological expertise by AMCS and CCA. All authors read and approved the final manuscript. References Allcoat, D., Hatchard, T., Azmat, F., Stansfield, K., Watson, D., & von Mühlenen, A. (2021). Education in the Digital Age: Learning Experience in Virtual and Mixed Realities. Journal of Educational Computing Research , 59 (5), 795–816. https://doi.org/10.1177/0735633120985120. Barteit, S., Lanfermann, L., Bärnighausen, T., Neuhann, F., & Beiersmann, C. (2021). Augmented, Mixed, and Virtual Reality-Based Head-Mounted Devices for Medical Education: Systematic Review. JMIR Serious Games , 9 (3), e29080. https://doi.org/10.2196/29080. Cometti, C., Païzis, C., Casteleira, A., Pons, G., & Babault, N. (2018). Effects of mixed reality head-mounted glasses during 90 minutes of mental and manual tasks on cognitive and physiological functions. PeerJ , 6 , e5847. https://doi.org/10.7717/peerj.5847. Dittner, A. J., Wessely, S. C., & Brown, R. G. (2004). The assessment of fatigue: A practical guide for clinicians and researchers. Journal of Psychosomatic Research , 56 (2), 157–170. https://doi.org/10.1016/S0022-3999(03)00371-4. Dukes, J. C., Chakan, M., Mills, A., & Marcaurd, M. (2021). Approach to Fatigue: Best Practice. Med Clin North Am , 137–148. Fauville, G., Luo, M., Muller Queiroz, A. C., Bailenson, J. N., & Hancock, J. (2021). Zoom Exhaustion & Fatigue Scale (SSRN Scholarly Paper 3786329). https://doi.org/10.2139/ssrn.3786329. Fehring, R. J. (1987). Methods to validate nursing diagnoses. Heart & Lung: The Journal of Critical Care , 16 (6 Pt 1), 625–629. Gabbard, J. L., Mehra, D. G., & Swan, J. E. (2019). Effects of AR Display Context Switching and Focal Distance Switching on Human Performance. IEEE Transactions on Visualization and Computer Graphics , 25 (6), 2228–2241. https://doi.org/10.1109/TVCG.2018.2832633. Gutiérrez-Maldonado, J. (2022). The Use of Virtual Reality Technology in the Treatment of Psychopathological Disorders. Journal of Clinical Medicine , 11 (18), Article 18. https://doi.org/10.3390/jcm11185358. Ifanov, Jessica, P., Salim, S., Syahputra, M. E., & Suri, P. A. (2023). A Systematic literature review on the implementation of virtual reality for learning. Procedia Computer Science , 216 , 260–265. https://doi.org/10.1016/j.procs.2022.12.135. Lim, S., Jeon, H., Jung, M., Lee, C., Moon, W., Kim, K., Kim, H., & Hahn, J. (2022). Fatigue-free visual perception of high-density super-multiview augmented reality images. Scientific Reports , 12 (1), Article 1. https://doi.org/10.1038/s41598-022-06778-4. Liu, K., Zhang, W., Li, W., Wang, T., & Zheng, Y. (2023). Effectiveness of virtual reality in nursing education: A systematic review and meta-analysis. BMC Medical Education , 23 (1), 710. https://doi.org/10.1186/s12909-023-04662-x. McCarthy, D., & Saegert, S. (1978). Residential density, social overload, and social withdrawal. Human Ecology , 6 (3), 253–272. https://doi.org/10.1007/BF00889026 Nadler, R. (2020). Understanding “Zoom fatigue”: Theorizing spatial dynamics as third skins in computer-mediated communication. Computers and Composition , 58 , 102613. https://doi.org/10.1016/j.compcom.2020.102613. Quatrini Carvalho Passos Guimarães, H. C., Pena, S. B., Lopes, J. de L., Lopes, C. T., & Bottura Leite de Barros, A. L. (2016). Experts for Validation Studies in Nursing: New Proposal and Selection Criteria. International Journal of Nursing Knowledge , 27 (3), 130–135. https://doi.org/10.1111/2047-3095.12089. Quintana, C. O., Cid-Expósito, M. G., Martín-García, Á., Brito-Brito, P. R., Parro-Moreno, A. I., Alcolea-Cosín, M. T., & Alameda-Cuesta, A. (2022). Validación por expertos del contenido del diagnóstico enfermero de NANDA-I Fatiga (00093). Revista Cubana de Enfermería , 38 (1), Article 1. https://revenfermeria.sld.cu/index.php/enf/article/view/4427 Shrestha, P. K., Pryn, M. J., Jia, J., Chen, J.-S., Fructuoso, H. N., Boev, A., Zhang, Q., & Chu, D. (2019). Accommodation-Free Head Mounted Display with Comfortable 3D Perception and an Enlarged Eye-box. Research (Washington, D.C.) , 2019 , 9273723. https://doi.org/10.34133/2019/9273723 Smets, E. M., Garssen, B., Bonke, B., & De Haes, J. C. (1995). The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. Journal of Psychosomatic Research , 39 (3), 315–325. https://doi.org/10.1016/0022-3999(94)00125-o. Souchet, A. D., Lourdeaux, D., Pagani, A., & Rebenitsch, L. (2023). A narrative review of immersive virtual reality’s ergonomics and risks at the workplace: Cybersickness, visual fatigue, muscular fatigue, acute stress, and mental overload. Virtual Reality , 27 (1), 19–50. https://doi.org/10.1007/s10055-022-00672-0. Voith, A. M., Frank, A. M., & Smith Pigg, J. (1989). Nursing diagnosis: Fatigue. In Classification of Nursing Diagnoses, Proceedings of 8th Conference NANDA . 8th Conference NANDA, Mosby, St Louis. Wiederhold, B. K. (2020). Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding ‘Zoom Fatigue’. Cyberpsychology, Behavior and Social Networking , 23 (7), 437–438. https://doi.org/10.1089/cyber.2020.29188.bkw. Woon, A. P. N., Mok, W. Q., Chieng, Y. J. S., Zhang, H. M., Ramos, P., Mustadi, H. B., & Lau, Y. (2021). Effectiveness of virtual reality training in improving knowledge among nursing students: A systematic review, meta-analysis and meta-regression. Nurse Education Today , 98 , 104655. https://doi.org/10.1016/j.nedt.2020.104655. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Feb, 2026 Read the published version in BMC Medical Education → Version 1 posted Editorial decision: Revision requested 24 Feb, 2025 Reviews received at journal 23 Feb, 2025 Reviewers agreed at journal 13 Feb, 2025 Reviews received at journal 24 Jan, 2025 Reviewers agreed at journal 18 Jan, 2025 Reviewers agreed at journal 25 Nov, 2024 Reviewers invited by journal 01 Jul, 2024 Editor assigned by journal 19 Jun, 2024 Editor invited by journal 22 Apr, 2024 Submission checks completed at journal 22 Apr, 2024 First submitted to journal 11 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Medical Emergency Service Madrid (SUMMA112), Spain","correspondingAuthor":false,"prefix":"","firstName":"Soledad","middleName":"","lastName":"Herrador-Sánchez","suffix":""},{"id":294033788,"identity":"e0508470-fa0a-4e01-bcd9-7f55d5d1ad36","order_by":5,"name":"María Redondo-Lozano","email":"","orcid":"","institution":"Out-of-Hospital Medical Emergency Service Madrid (SUMMA112), Spain","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"","lastName":"Redondo-Lozano","suffix":""},{"id":294033789,"identity":"c6989263-fc5d-4e0a-9026-3bb018d4c141","order_by":6,"name":"Carmen Cardós-Alonso","email":"","orcid":"","institution":"Out-of-Hospital Medical Emergency Service Madrid (SUMMA112), Spain","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"","lastName":"Cardós-Alonso","suffix":""}],"badges":[],"createdAt":"2024-04-11 09:42:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4251601/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4251601/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12909-026-08641-w","type":"published","date":"2026-02-01T15:59:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":101691884,"identity":"a41c56da-5015-4829-ac29-02fc84bd86df","added_by":"auto","created_at":"2026-02-02 16:16:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":693356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4251601/v1/bb6fc011-d2df-4c25-8ddf-92374d0a3554.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Virtual \u0026 Mixed Reality Fatigue Scale","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eHeadset-based virtual training simulation modalities yield fatigue symptoms.\u003c/li\u003e\n \u003cli\u003eThe Virtual and mixed reality fatigue scale can value the different fatigue profiles.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVirtual reality training can\u0026nbsp;cause\u0026nbsp;visual fatigue, general fatigue,\u0026nbsp;and decreased concentration\u0026nbsp;afterwards.\u003c/li\u003e\n \u003cli\u003eThe optimal time for the mixed reality training is about 20 minutes, depending on the user experience.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eVirtual reality (VR) is an emerging technology that has become increasingly prominent as an effective and efficient training tool in different healthcare settings (Liu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ifanov et al., 2023; Barteit et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) since it was first introduced more than 56 years ago (Guti\u0026eacute;rrez-Maldonado, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe use of this technology offers many benefits (Woon et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) (Allcoat et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); however, not all of these benefits are advantageous. Thus, we observe important side effects of this type of innovative training, including so-called \"virtual reality disease\" (Cometti et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gabbard et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shrestha et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lim et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Souchet et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). About this syndrome, we focus on the symptom of fatigue, a concept that features different dimensions. Fatigue has been widely studied in other situations (Smets et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Dittner et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Quintana et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne area of study related to this broad concept has been its relationship with the use of other new technologies, specifically concerning digital platforms (Nadler, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wiederhold, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fauville et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, given that our search did not reveal any articles that focused on measuring fatigue in the context of training in VR and mixed reality (MR), we designed a questionnaire to evaluate the level of fatigue perceived by professionals in this context. We validated this measure in the context of health emergencies after the use of VR and MR.\u003c/p\u003e \u003cp\u003eThe questionnaire developed values for the scope of fatigue and assessed both previous experiences using VR, and the training time associated with this technology as factors that may affect the degree and intensity of fatigue in terms of its various dimensions.\u003c/p\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003e Participants: Sixty-six out-of-hospital emergency nurses, physicians and technicians from the Emergency Medical Service of Madrid who attended the SUMMA112 Mass Casualty Incident (MCI) course. This course featured a VR segment lasting 15 minutes (the maximum time). A nonprobabilistic convenience sampling approach was used for this research.\u003c/p\u003e \u003cp\u003e First, the participants received information regarding this research and signed an informed consent form. Subsequently, they engaged in VR exercises with the assistance of Oculus Quest 2 goggles\u0026reg; and HoloLens\u0026reg; technology. The SUMMA112 professionals had previously participated in earlier versions of the Mass Casualty Incidents course as part of their ordinary corporate training.\u003c/p\u003e \u003cp\u003eWe performed the VR procedures using two heads-mounted displays (Oculus goggles\u0026reg; and HoloLens\u0026reg;) technologies indiscriminately. We freely invited participants in the VR practices to evaluate and complete the questionnaires.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eA review of the literature concerning this topic was performed.\u003c/p\u003e\n\u003cp\u003eThe concept of fatigue is complex and multifaceted (Dukes et al., \u003cspan\u003e2021\u003c/span\u003e). The North American Nursing Diagnostic Association (NANDA) established a working definition of fatigue that identifies it as a feeling of exhaustion that is associated with a decreased capacity for physical and mental work (Voith et al.; J., 1989) (Quintana et al., \u003cspan\u003e2022\u003c/span\u003e). To align our work on MR with the definition provided by NANDA, we define MR fatigue as a feeling of exhaustion that results from participating in MR activities.\u003c/p\u003e\n\u003cp\u003eTo account for the mental and physical aspects of fatigue, the Multidimensional Fatigue Inventory was examined (Smets et al., \u003cspan\u003e1995\u003c/span\u003e). This questionnaire represents one of the most widely used scales to measure fatigue and includes five constructs. Fauville outlined (2021) in the Zoom and Exhaustion Fatigue Scale (ZEF), five fatigue dimensions. In the experts group, four dimensions of interpersonal interaction of fatigue that could be present in a MR experience were selected.\u003c/p\u003e\n\u003cp\u003eThe first dimension involves the manner in which people express their fatigue is primarily through the phrase \u0026quot;I feel tired\u0026quot;. Accordingly, general fatigue refers to the general experience of being tired. The second dimension, according to Fauville et al. (\u003cspan\u003e2021\u003c/span\u003e), concerns how people express their physical fatigue as another construct related to fatigue. Third, people can experience fatigue in the form of difficulty concentrating, and \u0026quot;mental fatigue\u0026quot; refers to these cognitive symptoms related to fatigue. The fourth dimension of fatigue included in the Multidimensional Fatigue Inventory, i.e., \u0026ldquo;reduced motivation\u0026rdquo;, involves a lack of motivation to engage in any task linked to fatigue. Finally, Smets et al. (\u003cspan\u003e1995\u003c/span\u003e) identified \u0026ldquo;reduced activity\u0026rdquo; as the fifth dimension of fatigue, in which context a decreased level of activity emerges frequently, which we associated with the time that people need to recover from the MR experience.\u003c/p\u003e\n\u003cp\u003eThis previous research helps us understand which aspects of MR could lead to MR fatigue. Therefore, these five dimensions of fatigue could contribute to our understanding of MR fatigue. As participating in MR entails visual immersion using a head-mounted screen, the associated visual fatigue might represent another important dimension of MR fatigue.\u003c/p\u003e\n\u003cp\u003eMoreover, engaging in MR training alongside other professionals involves social interactions and speech. McCarthy \u0026amp; Saegert (\u003cspan\u003e1978\u003c/span\u003e) proposed the concept of social overload based on the negative impact of crowded places that characterizes this type of training on the stress associated with properly addressing an MCI in a timely manner.\u003c/p\u003e\n\u003cp\u003eIn the present paper, we present the development and validation of the MR \u0026amp; Fatigue Scale (MR Scale), which aims to assess the fatigue associated with MR use.\u003c/p\u003e\n\u003cp\u003eA descriptive and exploratory study focused on the validation of a fatigue questionnaire was conducted by experts by following the suggestions of Fehring (Fehring, \u003cspan\u003e1987\u003c/span\u003e) and employing the Delphi technique. This method used expert group validation as a basis for confirming the validity of the scale.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria limited the participants to emergency professionals (nurses, doctors, technicians or experts involved in health emergencies). Experts were defined as individuals who achieved a minimum score of 6 points in terms of the criteria proposed by Quatrini et al. (2016), namely, academic level and clinical, teaching and research experience related to critical healthcare, which represented the training content.\u003c/p\u003e\n\u003cp\u003eAfter various meetings were conducted and a consensus was reached among members of the research team and external experts in fatigue (the council of experts), the final items to be included in the scale were confirmed.\u003c/p\u003e\n\u003cp\u003eThe data collection process took place between January and December 2023.\u003c/p\u003e\n\u003cp\u003eOur goal was to develop a tool that took into account both the psychological and physical aspects of fatigue related to VR and MR use.\u003c/p\u003e\n\u003cp\u003eTo validate the fatigue scale, a study featuring a quantitative approach and a nonexperimental design was conducted following the procedures associated with the adaptation of the ZEF scale and the development of the proposed Virtual and Mixed Reality Fatigue Scale with the goal of obtaining evidence of the measure\u0026rsquo;s validity and reliability. The data thus obtained were analyzed by reference to the content validity index, correlation values, internal consistency, and the results of a factor analysis.\u003c/p\u003e\n\u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003eDEVELOPMENT OF THE RESEARCH\u003c/h2\u003e\n \u003cp\u003eIn Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e, we present the Virtual and Mixed Reality Fatigue Scale.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e. Fatigue Scale for Virtual and Mixed Reality\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQUESTION\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eANSWER\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you feel fatigued after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAre you experiencing musculoskeletal discomfort such as neck pain or tension?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you experience visual discomfort, such as pain, blurred vision, dryness, or irritation, after using virtual and/or mixed reality,?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you feel that you need time alone with yourself after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you experience difficulty maintaining attention and concentration after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you feel too tired to do other things after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you feel emotionally drained after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHow irritable do you feel after using virtual and/or mixed reality?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u0026ndash;3\u0026ndash;4\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHow often do you participate in virtual or mixed reality training sessions?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1. Never\u003c/p\u003e\n \u003cp\u003e2. Approximately once per month\u003c/p\u003e\n \u003cp\u003e3. Approximately once per week\u003c/p\u003e\n \u003cp\u003e4. Approximately once per day\u003c/p\u003e\n \u003cp\u003e5. Several times, more than once per day\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn your opinion, a mixed reality training session (with glasses) should not exceed\u0026hellip;?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1. 15 minutes\u003c/p\u003e\n \u003cp\u003e2. 20 minutes\u003c/p\u003e\n \u003cp\u003e3. 25 minutes\u003c/p\u003e\n \u003cp\u003e4. 30 minutes\u003c/p\u003e\n \u003cp\u003e5. 35 minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDo you consider the utilization of virtual reality to enhance the learning process to be necessary and/or useful?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1. Extremely necessary/useful\u003c/p\u003e\n \u003cp\u003e2. Very necessary/useful\u003c/p\u003e\n \u003cp\u003e3. Moderately necessary/useful\u003c/p\u003e\n \u003cp\u003e4. Slightly necessary/useful\u003c/p\u003e\n \u003cp\u003e5. Not necessary/useful at all\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n \u003cp\u003eEach question from 1 to 8 was scored on the following five-point Likert scale:\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e1. Not at all.\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e2. Slightly\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e3. Moderately\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e4. A lot\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e5. Extremely\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eProcedure: The Virtual and Mixed Reality Fatigue Scale was employed considering the ethical factors related to this research and ensuring that individuals could participate in this research in a voluntary, pseudoanonymous and confidential manner.\u003c/p\u003e\n \u003cp\u003eData analysis: A confirmatory factor analysis (CFA) was performed using the maximum likelihood method. Finally, Cronbach\u0026apos;s alpha coefficients were calculated to determine the reliability of the factors and the complete scale.\u003c/p\u003e\n \u003cp\u003eThe data were analyzed using SPSS V.28.0 software.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eshows the frequency of the results obtained by analyzing the various items included in the questionnaires.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cem\u003eDescriptive Statistic Percentage for the Items Included in the Virtual and Mixed Reality Scale\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo you suffer from general fatigue after engaging in VR training sessions?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDo you experience musculoskeletal complaints such as neck pain or muscle tension after using VR?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDo you notice any visual symptoms, such as ocular pain, after using VR?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDo you seek to spend a quiet and isolated time alone after using VR?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDo you experience difficulty maintaining attention and/or concentration after using VR?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDo you experience excessive tiredness when performing other tasks after using VR?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot at all (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlight (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtreme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAn analysis of the data revealed that after training in MCI using VR technology, 58% of the students suffered fatigue of some kind, which was generally mild but was severe in 6% of cases.\u003c/p\u003e \u003cp\u003eMore than 80% of the students did not experience any muscle discomfort, pain, tension, etc., or report any physical complaints after completing the proposed MCI exercises using VR, and among students who did notice some discomfort, the majority (10.6%) reported mild discomfort. One case of severe discomfort was recorded after the simulation.\u003c/p\u003e \u003cp\u003eIn terms of eye discomfort, such as eye pain, blurred vision, and eye strain, 83% of the students did not suffer any or suffered only very mild eye discomfort after the simulation, while 16.6% of the students experienced moderate or severe eye discomfort.\u003c/p\u003e \u003cp\u003eThe majority of the students (82%) did not need to spend time in isolation or solitude after the exercise to recover from this strain. A total of 30% of the students reported difficulty maintaining attention and/or concentration after using the head-mounted display, and 18% of students exhibited excessive tiredness after participating in the virtual MCI training.\u003c/p\u003e \u003cp\u003e In line with the other results, more than 15% of the participants reported irritation after the virtual training, with a similar proportion of students feeling emotionally drained.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results regarding participants\u0026rsquo; previous experience in virtual or MR, 85% of the volunteers had never used VR or MR, 11% reported using it once per week, and 4% reported using it daily. A total of 82% of the participants identified the length of VR training ranging from 15 to 20 minutes as adequate. A minority of 9% of the participants would prefer to double the training time.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistic Percentage for the MR trainees experience, the more adequate time training according to user experience and the perceived usability of the MR professional training\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHow often do you practice virtual or mixed reality?\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eHow much time do you consider, in general, more suitable for training with mixed reality glasses?\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eDo you think it is important/useful to use mixed/virtual reality to improve learning in Mass Casualty Incident training?\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUntil 15 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExtremely important\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproximately once a month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUntil 20 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVery important\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproximately once a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUntil 25 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately important\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproximately once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUntil 30 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSlightly important\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeveral times a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUntil 35 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot important at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePsychometric Analysis\u003c/p\u003e \u003cp\u003eBased on the data analysis, the model exhibited the following fit indices: X2\u0026thinsp;=\u0026thinsp;61.10, gl\u0026thinsp;=\u0026thinsp;69, X2/gl\u0026thinsp;=\u0026thinsp;1.08, p\u0026thinsp;\u0026lt;\u0026thinsp;.01; CFI\u0026thinsp;=\u0026thinsp;.71, IFI\u0026thinsp;=\u0026thinsp;.72, GFI\u0026thinsp;=\u0026thinsp;.65, AGFI\u0026thinsp;=\u0026thinsp;.81, NFI\u0026thinsp;=\u0026thinsp;.73, RMR\u0026thinsp;=\u0026thinsp;.06 and RMSEA\u0026thinsp;=\u0026thinsp;.05.\u003c/p\u003e \u003cp\u003eAccording to psychometric literature, the data support the construct validity of the Fatigue Scale. Similarly, the model was parsimonious, i.e., it was obtained without changing the identified scale and the errors did not exhibit covariance.\u003c/p\u003e \u003cp\u003eThe reliability of the total scale remained the same; however, the factor data exhibited slight changes that were not considered to be significant.\u003c/p\u003e \u003cp\u003eWhen we asked the participants about the usefulness of this technology in terms of its ability to enhance the learning process, 15.2% considered it to be moderately important, 53% considered it to be very important, and 31.8% considered it to be extremely important; no participants evaluated this pedagogical tool as exhibiting little value.\u003c/p\u003e \u003cp\u003eThe use of a methodology based on VR/MR in attempts to instruct health staff in how to respond to incidents involving multiple victims is acceptable in terms of the fatigue it produces. This approach can be an interesting teaching tool if the proper training time to obtain optimal results is taken into account and if secondary effects are avoided as much as possible.\u003c/p\u003e \u003cp\u003eThis approach represents an improvement over current and traditional training methods and is more effective in the long term due to its increased capacity to generate immersive simulations that can offer students in MCI courses the most realistic experience of the task of performing in the context of an MCI.\u003c/p\u003e \u003cp\u003e15% of the participants who frequently used VR suffered less fatigue than people who were experiencing VR for the first time, especially for eye-related symptoms, emotional symptoms and irritation. Physical discomfort and other negative factors can most likely be mitigated if healthcare professionals are accustomed to the use of VR/MR. In most cases, these data were obtained from healthcare professionals who are not accustomed to VR. This hypothesis can be confirmed by additional studies that can corroborate this trend.\u003c/p\u003e \u003cp\u003eFinally, it is helpful to explore the prevalence of fatigue when different MR devices are used. Another factor that should be considered in the future is fatigue affectation, particularly about whether fatigue levels change based on the purpose of MR use, such as whether this approach is used for training at the professional level, as in the case, or for entertainment-related purposes. Measurements in these different environments may vary due to a variety of factors, such as the responsibility associated with learning in the professional environment or the increased challenge of interpreting visual data in an immersive environment.\u003c/p\u003e \u003cp\u003eThe type of headset display used in this context can influence the results of such a fatigue evaluation based on the immersive experience of the field trial and its quality. More studies should be conducted to investigate this issue in the future.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIt has not been found in the extant literature exploration of the different fatigue dimensions that can affect the optimal use of interactive mixed-reality learning for health professionals.\u003c/p\u003e \u003cp\u003eIt has been validated the Virtual and Mixed Reality Fatigue Scale, that is valid in detecting the general, social, emotional, visual, and motivational dimensions of fatigue:\u003c/p\u003e \u003cp\u003eThe fatigue scale for VR and MR fulfills several objectives; on the one hand, it provides a method for subjectively measuring experienced fatigue in the context of this training model and makes it possible to optimize various aspects such as the duration of training or the experience of well-being in the context of MR, thus allowing us to make this approach more effective.\u003c/p\u003e \u003cp\u003eThe duration of the VR activity was also identified as a decisive factor that influenced the results obtained by applying the fatigue scale.\u003c/p\u003e \u003cp\u003eDespite the emergence of mild symptoms, users identified a duration of 15\u0026ndash;20 minutes as optimal for an immersive VR experience.\u003c/p\u003e \u003cp\u003eIn conclusion, it is crucial to establish a balance among immersion, influencing factors and fatigue to optimize participants\u0026rsquo; experience in these environments. Given the increase in the use of new technologies, such as VR, this work is focused on determining the validity of a questionnaire used to measure fatigue when these technologies are used.\u003c/p\u003e \u003cp\u003eAfter controlling for certain variables, data were collected to adapt this questionnaire and observe participants\u0026rsquo; responses to MR training fatigue. The VR and MR Fatigue Scale includes validated constructs about physical and mental fatigue. The test is a valid measurement of the fatigue items that were proposed.\u003c/p\u003e \u003cp\u003eThe increase in the use of this technology requires these measurements to perform the best professional training using MR.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the University of Cultural and Behavioral Studies Heidelberg under registration no. AZ Beu 2023 1/1. The informed consent was obtained from all subjects that participated in the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and materials are available at https://bit.ly/DatabaseSUMMA112ValidationFatigueResearch\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is supported by the European project MED1stMR (Medical First Responder Training using a Mixed Reality Approach featuring haptic feedback for enhanced realism). Med1stMR project is funded by the European Union\u0026apos;s Horizon 2020 Research and Innovation Program with the Grant agreement N\u0026ordm; 101021775.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the operational support provided by Sara P\u0026eacute;rez Garc\u0026iacute;a (FIIBAP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAMCS, PST, ABL, TVR, SHS \u0026nbsp;and CCA were involved in the conception and design of the work. AMCS, PST and CCA contributed to the screening process, data extraction and quality assessment of papers; ABL and AMCS \u0026nbsp;interpreted the data. AMCS, PST, TVR, SHS, MRL \u0026nbsp;and CCA drafted the manuscript, \u0026nbsp;ABL prepared tables 1 and 2 and AMCS prepared table 3. The manuscript was critically reviewed and enriched with medical expertise by ABL and MRL, with psychological expertise by SP; and with technological expertise by AMCS \u0026nbsp;and CCA. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllcoat, D., Hatchard, T., Azmat, F., Stansfield, K., Watson, D., \u0026amp; von M\u0026uuml;hlenen, A. (2021). Education in the Digital Age: Learning Experience in Virtual and Mixed Realities. \u003cem\u003eJournal of Educational Computing Research\u003c/em\u003e, \u003cem\u003e59\u003c/em\u003e(5), 795\u0026ndash;816. https://doi.org/10.1177/0735633120985120.\u003c/li\u003e\n\u003cli\u003eBarteit, S., Lanfermann, L., B\u0026auml;rnighausen, T., Neuhann, F., \u0026amp; Beiersmann, C. (2021). Augmented, Mixed, and Virtual Reality-Based Head-Mounted Devices for Medical Education: Systematic Review. \u003cem\u003eJMIR Serious Games\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(3), e29080. https://doi.org/10.2196/29080.\u003c/li\u003e\n\u003cli\u003eCometti, C., Pa\u0026iuml;zis, C., Casteleira, A., Pons, G., \u0026amp; Babault, N. (2018). Effects of mixed reality head-mounted glasses during 90 minutes of mental and manual tasks on cognitive and physiological functions. \u003cem\u003ePeerJ\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, e5847. https://doi.org/10.7717/peerj.5847.\u003c/li\u003e\n\u003cli\u003eDittner, A. J., Wessely, S. C., \u0026amp; Brown, R. G. (2004). The assessment of fatigue: A practical guide for clinicians and researchers. \u003cem\u003eJournal of Psychosomatic Research\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(2), 157\u0026ndash;170. https://doi.org/10.1016/S0022-3999(03)00371-4.\u003c/li\u003e\n\u003cli\u003eDukes, J. C., Chakan, M., Mills, A., \u0026amp; Marcaurd, M. (2021). Approach to Fatigue: Best Practice. \u003cem\u003eMed Clin North Am\u003c/em\u003e, 137\u0026ndash;148.\u003c/li\u003e\n\u003cli\u003eFauville, G., Luo, M., Muller Queiroz, A. C., Bailenson, J. N., \u0026amp; Hancock, J. (2021). \u003cem\u003eZoom Exhaustion \u0026amp; Fatigue Scale\u003c/em\u003e (SSRN Scholarly Paper 3786329). https://doi.org/10.2139/ssrn.3786329.\u003c/li\u003e\n\u003cli\u003eFehring, R. J. (1987). Methods to validate nursing diagnoses. \u003cem\u003eHeart \u0026amp; Lung: The Journal of Critical Care\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(6 Pt 1), 625\u0026ndash;629.\u003c/li\u003e\n\u003cli\u003eGabbard, J. L., Mehra, D. G., \u0026amp; Swan, J. E. (2019). Effects of AR Display Context Switching and Focal Distance Switching on Human Performance. \u003cem\u003eIEEE Transactions on Visualization and Computer Graphics\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(6), 2228\u0026ndash;2241. https://doi.org/10.1109/TVCG.2018.2832633.\u003c/li\u003e\n\u003cli\u003eGuti\u0026eacute;rrez-Maldonado, J. (2022). The Use of Virtual Reality Technology in the Treatment of Psychopathological Disorders. \u003cem\u003eJournal of Clinical Medicine\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(18), Article 18. https://doi.org/10.3390/jcm11185358.\u003c/li\u003e\n\u003cli\u003eIfanov, Jessica, P., Salim, S., Syahputra, M. E., \u0026amp; Suri, P. A. (2023). A Systematic literature review on the implementation of virtual reality for learning. \u003cem\u003eProcedia Computer Science\u003c/em\u003e, \u003cem\u003e216\u003c/em\u003e, 260\u0026ndash;265. https://doi.org/10.1016/j.procs.2022.12.135.\u003c/li\u003e\n\u003cli\u003eLim, S., Jeon, H., Jung, M., Lee, C., Moon, W., Kim, K., Kim, H., \u0026amp; Hahn, J. (2022). Fatigue-free visual perception of high-density super-multiview augmented reality images. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), Article 1. https://doi.org/10.1038/s41598-022-06778-4.\u003c/li\u003e\n\u003cli\u003eLiu, K., Zhang, W., Li, W., Wang, T., \u0026amp; Zheng, Y. (2023). Effectiveness of virtual reality in nursing education: A systematic review and meta-analysis. \u003cem\u003eBMC Medical Education\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(1), 710. https://doi.org/10.1186/s12909-023-04662-x.\u003c/li\u003e\n\u003cli\u003eMcCarthy, D., \u0026amp; Saegert, S. (1978). Residential density, social overload, and social withdrawal. \u003cem\u003eHuman Ecology\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(3), 253\u0026ndash;272. https://doi.org/10.1007/BF00889026\u003c/li\u003e\n\u003cli\u003eNadler, R. (2020). Understanding \u0026ldquo;Zoom fatigue\u0026rdquo;: Theorizing spatial dynamics as third skins in computer-mediated communication. \u003cem\u003eComputers and Composition\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e, 102613. https://doi.org/10.1016/j.compcom.2020.102613.\u003c/li\u003e\n\u003cli\u003eQuatrini Carvalho Passos Guimar\u0026atilde;es, H. C., Pena, S. B., Lopes, J. de L., Lopes, C. T., \u0026amp; Bottura Leite de Barros, A. L. (2016). Experts for Validation Studies in Nursing: New Proposal and Selection Criteria. \u003cem\u003eInternational Journal of Nursing Knowledge\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(3), 130\u0026ndash;135. https://doi.org/10.1111/2047-3095.12089.\u003c/li\u003e\n\u003cli\u003eQuintana, C. O., Cid-Exp\u0026oacute;sito, M. G., Mart\u0026iacute;n-Garc\u0026iacute;a, \u0026Aacute;., Brito-Brito, P. R., Parro-Moreno, A. I., Alcolea-Cos\u0026iacute;n, M. T., \u0026amp; Alameda-Cuesta, A. (2022). Validaci\u0026oacute;n por expertos del contenido del diagn\u0026oacute;stico enfermero de NANDA-I Fatiga (00093). \u003cem\u003eRevista Cubana de Enfermer\u0026iacute;a\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(1), Article 1. https://revenfermeria.sld.cu/index.php/enf/article/view/4427\u003c/li\u003e\n\u003cli\u003eShrestha, P. K., Pryn, M. J., Jia, J., Chen, J.-S., Fructuoso, H. N., Boev, A., Zhang, Q., \u0026amp; Chu, D. (2019). Accommodation-Free Head Mounted Display with Comfortable 3D Perception and an Enlarged Eye-box. \u003cem\u003eResearch (Washington, D.C.)\u003c/em\u003e, \u003cem\u003e2019\u003c/em\u003e, 9273723. https://doi.org/10.34133/2019/9273723\u003c/li\u003e\n\u003cli\u003eSmets, E. M., Garssen, B., Bonke, B., \u0026amp; De Haes, J. C. (1995). The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. \u003cem\u003eJournal of Psychosomatic Research\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(3), 315\u0026ndash;325. https://doi.org/10.1016/0022-3999(94)00125-o.\u003c/li\u003e\n\u003cli\u003eSouchet, A. D., Lourdeaux, D., Pagani, A., \u0026amp; Rebenitsch, L. (2023). A narrative review of immersive virtual reality\u0026rsquo;s ergonomics and risks at the workplace: Cybersickness, visual fatigue, muscular fatigue, acute stress, and mental overload. \u003cem\u003eVirtual Reality\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(1), 19\u0026ndash;50. https://doi.org/10.1007/s10055-022-00672-0.\u003c/li\u003e\n\u003cli\u003eVoith, A. M., Frank, A. M., \u0026amp; Smith Pigg, J. (1989). Nursing diagnosis: Fatigue. In Classification of Nursing Diagnoses, \u003cem\u003eProceedings of 8th Conference NANDA\u003c/em\u003e. 8th Conference NANDA, Mosby, St Louis.\u003c/li\u003e\n\u003cli\u003eWiederhold, B. K. (2020). Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding \u0026lsquo;Zoom Fatigue\u0026rsquo;. \u003cem\u003eCyberpsychology, Behavior and Social Networking\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(7), 437\u0026ndash;438. https://doi.org/10.1089/cyber.2020.29188.bkw.\u003c/li\u003e\n\u003cli\u003eWoon, A. P. N., Mok, W. Q., Chieng, Y. J. S., Zhang, H. M., Ramos, P., Mustadi, H. B., \u0026amp; Lau, Y. (2021). Effectiveness of virtual reality training in improving knowledge among nursing students: A systematic review, meta-analysis and meta-regression. \u003cem\u003eNurse Education Today\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e, 104655. https://doi.org/10.1016/j.nedt.2020.104655.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"virtual reality, fatigue, scale, training, mixed reality simulation","lastPublishedDoi":"10.21203/rs.3.rs-4251601/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4251601/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Virtual reality (VR) and mixed reality (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 during mass casualty incidents.\u003c/p\u003e\n\u003cp\u003eGiven 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 scale to assess fatigue in terms of various dimensions that can affect a person while training in the context of VR and MR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We designed a questionnaire to assess the fatigue levels perceived by professionals and validated this measure after a VR training experience. We analyzed ratings of visual, mental, physical, and general fatigue. This questionnaire was applied to emergency professionals (n=66).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The reliability and validity of the scale were assessed in terms of the following factors: general, social, emotional, visual, and motivational fatigue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The results of this research suggest that fatigue is an element of VR training. Educators should take these effects into account to optimize learning in the context of MR.\u003c/p\u003e","manuscriptTitle":"Virtual \u0026amp; Mixed Reality Fatigue Scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-24 15:49:50","doi":"10.21203/rs.3.rs-4251601/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-24T10:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-23T16:44:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332561929859912269297498080068862058030","date":"2025-02-13T19:29:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-24T22:45:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9554820957416518666538381120478027995","date":"2025-01-18T22:49:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108392652603012641302605038731665989692","date":"2024-11-25T23:22:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-01T09:13:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-19T11:37:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-22T07:00:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-22T06:57:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2024-04-11T09:41:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8979ac06-0cf3-4c49-87d6-5868c6b677c0","owner":[],"postedDate":"April 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:06:33+00:00","versionOfRecord":{"articleIdentity":"rs-4251601","link":"https://doi.org/10.1186/s12909-026-08641-w","journal":{"identity":"bmc-medical-education","isVorOnly":false,"title":"BMC Medical Education"},"publishedOn":"2026-02-01 15:59:04","publishedOnDateReadable":"February 1st, 2026"},"versionCreatedAt":"2024-04-24 15:49:50","video":"","vorDoi":"10.1186/s12909-026-08641-w","vorDoiUrl":"https://doi.org/10.1186/s12909-026-08641-w","workflowStages":[]},"version":"v1","identity":"rs-4251601","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4251601","identity":"rs-4251601","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}