1. Acceptance and feasibility of virtual reality for teaching adult basic life support in older populationsAna Belen Ocampo Cervantes, Carmen Amalia Lopez Lopez, Robert Greif, Federico Semeraro, Manuel Pardo Rios, Nino Fijačko, 2025, izvirni znanstveni članek Opis: Abstract Background Virtual reality (VR) is emerging in adult Basic Life Support (BLS) training, but its acceptance among older adults has not been fully studied. This study aimed to develop expert-informed BLS content for both VR and laptop formats, and to evaluate the feasibility, usability, knowledge acquisition, satisfaction, and cybersickness of these platforms among older adult learners. Methods A two-phase mixed-methods study was conducted. Five experts co-developed and validated a VR/laptop-compatible adult BLS scenario based on the 2021 European Resuscitation Council guidelines. This scenario was then tested by older adults who voluntarily participated in either VR- or laptop-based training at a public technology event in Spain. Post-training, we measured knowledge acquisition, usability, satisfaction, user experience, and cybersickness. Comparative statistics and regression analyses were performed to evaluate learning outcomes and predictors. Results Five experts developed a consensus-based adult BLS decision tree with 10 scenes and six questions. A total of 583 adults (mean age 72.3 ± 4.8 years) took part in the BLS training evaluation. Those in the VR group (n = 415) outperformed those in the laptop group (n = 168) in key steps, including initiating CPR (58 % vs 41 %, p < 0.001) and using an AED (49 % vs 23 %, p < 0.001). VR participants rated usability of VR-training as excellent (73.8 ± 4.2), expressed high satisfaction and realism. Cybersickness was low (13.1 %). VR training predicted higher knowledge scores (β = 5.8, p < 0.001), and increased scores by 5.8 points over laptop training. VR participants were 2.3 times more likely to answer BLS questions correctly (OR = 2.3, 95 % CI: 1.6–3.2, p < 0.001) Conclusion VR could improve adult BLS knowledge in older adults, with high levels of acceptance and positive user experience. Future work should enhance accessibility and reduce discomfort.
Ključne besede: Older adults, Training methods, Virtual reality, Cardiopulmonary resuscitation, Basic Life Support, Knowledge, Usability
Objavljeno v DKUM: 29.10.2025; Ogledov: 0; Prenosov: 2
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2. Leg-foot chest compressions: a scoping reviewNino Fijačko, Kristina McShea, Eva Dolenc Šparovec, Špela Metličar, Tomaž Horvat, Vinay M. Nadkarni, Robert Greif, 2025, pregledni znanstveni članek Ključne besede: Cardiopulmonary resuscitation, Chest compressions, Leg-foot, Heel of the foot, Ball of the foot
Objavljeno v DKUM: 27.10.2025; Ogledov: 0; Prenosov: 2
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3. Virtual reality for basic life support training in high school students : thematic analysis of focus group interviewsHyojin Jenny Min, Caroline Andler, Rebecca Ortiz La Banca Barber, Todd P. Chang, Cristian Abelairas-Gómez, Laquanda T. Knowlin, Deborah R. Liu, Nino Fijačko, 2024, izvirni znanstveni članek Ključne besede: virtual reality, mixed reality, technology, basic life support, cardiovascular pulmonary resuscitation, near-peer mentoring, education, high school students
Objavljeno v DKUM: 07.10.2025; Ogledov: 0; Prenosov: 3
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4. International facets of the `chain of survival` for out-of-hospital and in-hospital cardiac arrest : a scoping reviewSebastian Schnaubelt, Koenraad G. Monsieurs, Nino Fijačko, Christoph Veigl, Zehra Al-Hilali, Huba Atiq, Blair L. Bigham, Kathryn Eastwood, Ying-Chih Ko, Tasuku Matsuyama, Justine Athieno Odakha, Alexander Olaussen, Robert Greif, 2024, pregledni znanstveni članek Ključne besede: chain of survival, chainmail of survival, out-of-hospital cardiac arrest, OHCA, cardiopulmonary resuscitation, CPR, scoping review
Objavljeno v DKUM: 19.09.2025; Ogledov: 0; Prenosov: 1
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5. Use of augmented and virtual reality in resuscitation training : a systematic reviewAdam Cheng, Nino Fijačko, Andrew Lockey, Robert Greif, Cristian Abelairas-Gómez, Lucija Gosak, Yiqun Lin, 2024, pregledni znanstveni članek Ključne besede: resuscitation, immersive technology, virtual reality, augmented reality, training, life support
Objavljeno v DKUM: 17.09.2025; Ogledov: 0; Prenosov: 4
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6. Rethinking realities: a call for accurate terminology in eXtended reality studiesNino Fijačko, Gregor Štiglic, Christina Gsaxner, Todd P. Chang, Robert Greif, 2024, drugi znanstveni članki Ključne besede: resuscitation education, virtual technology, XR terminology, new terminologies, reality studies
Objavljeno v DKUM: 15.09.2025; Ogledov: 0; Prenosov: 2
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8. Artificial intelligence in resuscitation: a scoping reviewDrieda Zace, Federico Semeraro, Sebastian Schnaubelt, Jonathan Montomoli, Giuseppe Ristagno, Nino Fijačko, Lorenzo Gamberini, Elena G. Bignami, Robert Greif, Koenraad G. Monsieurs, Andrea Scapigliati, 2025, pregledni znanstveni članek Opis: Background
Artificial intelligence (AI) is increasingly applied in medicine, with growing interest in its potential to improve outcomes in cardiac arrest (CA). However, the scope and characteristics of current AI applications in resuscitation remain unclear.
Methods
This scoping review aims to map the existing literature on AI applications in CA and resuscitation and identify research gaps for further investigation. PRISMA-ScR framework and ILCOR guidelines were followed. A systematic literature search across PubMed, EMBASE, and Cochrane identified AI applications in resuscitation. Articles were screened and classified by AI methodology, study design, outcomes, and implementation settings. AI-assisted data extraction was manually validated for accuracy.
Results
Out of 4046 records, 197 studies met inclusion criteria. Most were retrospective (90%), with only 16 prospective studies and 2 randomised controlled trials. AI was predominantly applied in prediction of CA, rhythm classification, and post-resuscitation outcome prognostication. Machine learning was the most commonly used method (50% of studies), followed by deep learning and, less frequently, natural language processing. Reported performance was generally high, with AUROC values often exceeding 0.85; however, external validation was rare and real-world implementation limited.
Conclusions
While AI applications in resuscitation demonstrate encouraging performance in prediction and decision support tasks, clear evidence of improved patient outcomes or routine clinical use remains limited. Future research should focus on prospective validation, equity in data sources, explainability, and seamless integration of AI tools into clinical workflows.
Ključne besede: Cardiac arrest, Resuscitation, Artificial intelligence, Machine learning, Deep learning, Large language model, Scoping review
Objavljeno v DKUM: 22.07.2025; Ogledov: 0; Prenosov: 3
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9. Analyzing resuscitation conference content through the lens of the chain of survivalNino Fijačko, Sebastian Schnaubelt, Vinay Nadkarni, Špela Metličar, Robert Greif, 2025, drugi znanstveni članki Ključne besede: resuscitation science, resuscitation conferences, abstracts, chain of survival, inclusivity, artificial intelligence, machine learning, deep learning
Objavljeno v DKUM: 21.07.2025; Ogledov: 0; Prenosov: 1
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10. Perception of personal participation of the nurses in resuscitation procedures : a qualitative studyAnton Koželj, Maja Strauss, Vita Poštuvan, Anže Strauss Koželj, Matej Strnad, 2024, izvirni znanstveni članek Opis: Background and Objectives: Resuscitation is one of the most stressful tasks in emergency medicine. The participation of nurses in this procedure can have specific effects on them. In this research, we wanted to find out what these effects are.
Materials and Methods: A qualitative approach by conducting semi-structured interviews was used, and a thematic data analysis of the recorded interviews was carried out. The collected data were transcribed verbatim, with no corrections to the audio recordings. The computer program ATLAS.ti 22 was used for the qualitative data analysis.
Results: Eleven male registered nurses were interviewed, with an average of 18.5 years of experience working in a prehospital environment (max. 32/min. 9). A total of 404 min of recordings were analyzed, and 789 codes were found, which were combined into 36 patterns and 11 themes. As the most stressful situations, the interviewees pointed out the resuscitation of a child, familiar persons, conflicts with the environment, conflicts within the resuscitation team, nonfunctioning or insufficient equipment, complications during resuscitation, and resuscitating a person only for training. As positive effects, the interviewees cited successful resuscitations or their awareness that, despite an unsuccessful resuscitation, they did everything they could.
Conclusions: Participation in these interventions has a specific positive or negative impact on the performers. The interviewees shared the opinion that they can cope effectively with the adverse or stressful effects of resuscitation. Yet, despite everything, they allow the possibility of subconscious influences of this intervention on themselves.
Ključne besede: resuscitation, personal experiences, paramedics, prehospital environment
Objavljeno v DKUM: 07.04.2025; Ogledov: 0; Prenosov: 20
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