Effectiveness of extended reality technologies in cardiopulmonary resuscitation training: a bayesian network meta-analysis
High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network me...
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Published in | BMC emergency medicine Vol. 25; no. 1; pp. 94 - 11 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
BioMed Central Ltd
07.06.2025
BioMed Central BMC |
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Online Access | Get full text |
ISSN | 1471-227X 1471-227X |
DOI | 10.1186/s12873-025-01256-2 |
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Abstract | High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods.
A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models.
11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected.
XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact.
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AbstractList | High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods.
A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models.
11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected.
XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact.
Not applicable. Abstract Background High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods. Methods A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models. Results 11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected. Conclusions XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact. Clinical trial number Not applicable. BackgroundHigh-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods.MethodsA Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models.Results11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected.ConclusionsXR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact.Clinical trial numberNot applicable. High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods.BACKGROUNDHigh-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods.A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models.METHODSA Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models.11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected.RESULTS11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected.XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact.CONCLUSIONSXR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact.Not applicable.CLINICAL TRIAL NUMBERNot applicable. Background High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods. Methods A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models. Results 11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected. Conclusions XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact. Clinical trial number Not applicable. Keywords: Cardiopulmonary resuscitation training, Extended reality, Augmented reality, Virtual reality, Mixed reality High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), provide immersive and interactive training, potentially enhancing CPR outcomes. This network meta-analysis compared the effectiveness of XR-based CPR training to traditional face-to-face methods. A Bayesian network meta-analysis was conducted following PRISMA guidelines. We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI for randomized controlled trials (RCTs) comparing XR-based and traditional CPR training. Primary outcomes included chest compression depth and rate; secondary outcomes assessed full chest wall recoil. The CINeMA tool (GRADE framework) was used to assess evidence quality. Statistical analyses were performed using Stata 15 SE and ADDIS software with random-effects models. 11 RCTs (1,190 participants) were included. MR showed the improvement in chest compression depth (SMD = 10.96; 95% CI, 0.95 to 20.82) compared to VR and traditional methods. For full chest wall recoil, AR outperformed VR (SMD = 48.57; 95% CI, 19.56 to 79.75) and traditional methods (SMD = 52.95; 95% CI, 25.94 to 80.48). However, no significant differences were observed for chest compression rate. SUCRA rankings placed MR as most effective for compression depth (87.4%) and AR for full chest wall recoil (99.1%). Evidence quality was moderate to high, with minor downgrades for imprecision. No publication bias was detected. XR technologies, particularly MR and AR, significantly improve chest compression depth and full chest wall recoil in comparing with face to face CRP training, offering a flexible and engaging approach to CPR training. Further studies are needed to evaluate long-term skill retention and real-world impact. |
ArticleNumber | 94 |
Audience | Academic |
Author | Wang, Xiaokai Li, Xiangmin Yin, Xinbo Huang, Guoqing |
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Cites_doi | 10.1016/j.ecns.2022.04.004 10.2196/35674 10.1007/s10648-020-09586-2 10.1080/10618600.1998.10474787 10.1016/j.medine.2023.10.011 10.1016/j.resplu.2024.100643 10.1016/j.resuscitation.2021.05.034 10.1002/sim.3767 10.1002/ase.1941 10.3390/ijerph20054095 10.1002/14651858.ED000142 10.1089/cyber.2023.0411 10.1057/jos.2014.14 10.1080/07853890.2024.2424450 10.1186/s12909-023-04974-y 10.1016/j.resuscitation.2020.03.017 10.1097/nr9.0000000000000010 10.1001/jamacardio.2019.4992 10.3390/medicina59101720 10.1186/s41077-021-00158-0 10.1186/s12909-021-03037-4 10.1109/MCSE.2020.2972822 10.1016/j.auec.2023.08.002 10.1016/j.resuscitation.2007.01.030 10.1161/CIR.0b013e31829d8654 10.7326/M14-2385 10.5001/omj.2020.43 10.1016/j.resuscitation.2016.08.021 10.3389/fdgth.2020.00001 10.7759/cureus.68757 10.1186/s13643-024-02723-w 10.1016/j.amsu.2022.103241 |
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Keywords | Extended reality Cardiopulmonary resuscitation training Mixed reality Augmented reality Virtual reality |
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References | 1256_CR1 T Baniasadi (1256_CR37) 2020; 35 PA Meaney (1256_CR2) 2013; 128 L Hou (1256_CR19) 2022; 1 S Nabecker (1256_CR5) 2021; 165 S Dias (1256_CR12) 2010; 29 C Crowley (1256_CR26) 2024; 198 M Leary (1256_CR24) 2020; 2 MJ Choi (1256_CR31) 2024; 19 B Hutton (1256_CR11) 2015; 162 GS Ruthenbeck (1256_CR36) 2015; 9 1256_CR14 1256_CR32 Y Zhou (1256_CR18) 2022; 17 A Sivananthan (1256_CR33) 2022; 6 M-J Hsieh (1256_CR4) 2016; 108 SP Brooks (1256_CR13) 1998; 7 K Kuyt (1256_CR8) 2021; 6 TM Olasveengen (1256_CR25) 2020; 142 D Hubail (1256_CR15) 2022; 73 EL Einspruch (1256_CR3) 2007; 74 H Sungur (1256_CR7) 2024; 27 J Nas (1256_CR22) 2020; 5 R Sun (1256_CR6) 2024; 24 E Toni (1256_CR29) 2024; 13 1256_CR27 MR Desselle (1256_CR35) 2020; 22 YT Chang (1256_CR16) 2023; 18 1256_CR23 PM Alcázar Artero (1256_CR17) 2024; 27 K Bogomolova (1256_CR28) 2020; 13 V Popov (1256_CR9) 2024; 56 A Cheng (1256_CR10) 2024; 18 I Minty (1256_CR34) 2022; 22 S Aranda-García (1256_CR21) 2024; 48 L Hou (1256_CR20) 2022; 68 G Makransky (1256_CR30) 2021; 33 |
References_xml | – volume: 68 start-page: 9 year: 2022 ident: 1256_CR20 publication-title: Clin Simul Nurs doi: 10.1016/j.ecns.2022.04.004 – volume: 6 start-page: e35674 issue: 5 year: 2022 ident: 1256_CR33 publication-title: JMIR Form Res doi: 10.2196/35674 – volume: 33 start-page: 937 issue: 3 year: 2021 ident: 1256_CR30 publication-title: Educ Psychol Rev doi: 10.1007/s10648-020-09586-2 – volume: 7 start-page: 434 issue: 4 year: 1998 ident: 1256_CR13 publication-title: J Comput Graph Stat ASA Website doi: 10.1080/10618600.1998.10474787 – volume: 48 start-page: 77 issue: 2 year: 2024 ident: 1256_CR21 publication-title: Med Intensiva (English Ed doi: 10.1016/j.medine.2023.10.011 – volume: 18 start-page: 100643 issue: March year: 2024 ident: 1256_CR10 publication-title: Resusc Plus Authors doi: 10.1016/j.resplu.2024.100643 – volume: 18 start-page: 1 issue: 3 March year: 2023 ident: 1256_CR16 publication-title: PLoS ONE – volume: 165 start-page: 77 year: 2021 ident: 1256_CR5 publication-title: Resusc Elsevier doi: 10.1016/j.resuscitation.2021.05.034 – volume: 29 start-page: 932 issue: 7–8 year: 2010 ident: 1256_CR12 publication-title: Stat Med Engl doi: 10.1002/sim.3767 – volume: 19 start-page: 1 issue: 2 February year: 2024 ident: 1256_CR31 publication-title: PLoS ONE – volume: 13 start-page: 558 issue: 5 year: 2020 ident: 1256_CR28 publication-title: Anat Sci Educ United States doi: 10.1002/ase.1941 – ident: 1256_CR23 doi: 10.3390/ijerph20054095 – ident: 1256_CR14 doi: 10.1002/14651858.ED000142 – volume: 27 start-page: 379 issue: 6 year: 2024 ident: 1256_CR7 publication-title: Cyberpsychology Behav Soc Netw doi: 10.1089/cyber.2023.0411 – volume: 9 start-page: 16 issue: 1 year: 2015 ident: 1256_CR36 publication-title: J Simul Taylor Francis doi: 10.1057/jos.2014.14 – volume: 56 start-page: 2424450 issue: 1 year: 2024 ident: 1256_CR9 publication-title: Ann Med Engl doi: 10.1080/07853890.2024.2424450 – volume: 24 start-page: 1 issue: 1 year: 2024 ident: 1256_CR6 publication-title: BMC Med Educ BioMed Cent doi: 10.1186/s12909-023-04974-y – ident: 1256_CR27 doi: 10.1016/j.resuscitation.2020.03.017 – volume: 1 start-page: 43 issue: 1 year: 2022 ident: 1256_CR19 publication-title: Interdiscip Nurs Res doi: 10.1097/nr9.0000000000000010 – volume: 5 start-page: 328 issue: 3 year: 2020 ident: 1256_CR22 publication-title: JAMA Cardiol doi: 10.1001/jamacardio.2019.4992 – ident: 1256_CR32 doi: 10.3390/medicina59101720 – volume: 6 start-page: 4 issue: 1 year: 2021 ident: 1256_CR8 publication-title: Adv Simul Adv Simul doi: 10.1186/s41077-021-00158-0 – volume: 22 start-page: 1 issue: 1 year: 2022 ident: 1256_CR34 publication-title: BMC Med Educ BioMed Cent doi: 10.1186/s12909-021-03037-4 – volume: 22 start-page: 18 issue: 3 year: 2020 ident: 1256_CR35 publication-title: Comput Sci Eng doi: 10.1109/MCSE.2020.2972822 – volume: 27 start-page: 57 issue: 1 year: 2024 ident: 1256_CR17 publication-title: Australas Emerg Care doi: 10.1016/j.auec.2023.08.002 – volume: 74 start-page: 476 issue: 3 year: 2007 ident: 1256_CR3 publication-title: Resusc Elsevier doi: 10.1016/j.resuscitation.2007.01.030 – volume: 17 start-page: 963 issue: 7 year: 2022 ident: 1256_CR18 publication-title: Chin J Emerg Resusc Disaster Med – volume: 198 start-page: 110142 year: 2024 ident: 1256_CR26 publication-title: Resusc Irel – volume: 142 start-page: S41 issue: 16suppl1 year: 2020 ident: 1256_CR25 publication-title: Circulation United States – volume: 128 start-page: 417 issue: 4 year: 2013 ident: 1256_CR2 publication-title: Circulation Am Heart Association doi: 10.1161/CIR.0b013e31829d8654 – volume: 162 start-page: 777 issue: 11 year: 2015 ident: 1256_CR11 publication-title: Ann Intern Med United States doi: 10.7326/M14-2385 – volume: 35 start-page: e125 issue: 3 year: 2020 ident: 1256_CR37 publication-title: Oman Med J Oman doi: 10.5001/omj.2020.43 – volume: 108 start-page: 8 year: 2016 ident: 1256_CR4 publication-title: Resuscitation doi: 10.1016/j.resuscitation.2016.08.021 – volume: 2 start-page: 1 issue: February year: 2020 ident: 1256_CR24 publication-title: Front Digit Heal doi: 10.3389/fdgth.2020.00001 – ident: 1256_CR1 doi: 10.7759/cureus.68757 – volume: 13 start-page: 299 issue: 1 year: 2024 ident: 1256_CR29 publication-title: Syst Rev Engl doi: 10.1186/s13643-024-02723-w – volume: 73 start-page: 103241 issue: December 2021 year: 2022 ident: 1256_CR15 publication-title: Ann Med Surg Elsevier Ltd doi: 10.1016/j.amsu.2022.103241 |
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Snippet | High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented Reality (AR),... Background High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented... BackgroundHigh-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including Augmented... Abstract Background High-quality cardiopulmonary resuscitation (CPR) is critical to cardiac arrest patients. Extended Reality (XR) technologies, including... |
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SubjectTerms | Analysis Augmented Reality Bayes Theorem Bayesian analysis Cardiopulmonary resuscitation Cardiopulmonary Resuscitation - education Cardiopulmonary resuscitation training Chest Clinical trials Compression Computer applications CPR CPR (First aid) Evidence Extended reality Humans Lifesaving Mathematical models Meta-analysis Mixed reality Randomized Controlled Trials as Topic Software Statistical analysis Training Virtual Reality |
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Title | Effectiveness of extended reality technologies in cardiopulmonary resuscitation training: a bayesian network meta-analysis |
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