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Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review
Abstract
REVIEW DATE: 1969 to 2003, 34 years. BACKGROUND AND CONTEXT: Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. OBJECTIVES: Review and synthesize existing evidence in educational science that addresses the question, 'What are the features and uses of high-fidelity medical simulations that lead to most effective learning?'. SEARCH STRATEGY: The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the 'grey literature' were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. INCLUSION AND EXCLUSION CRITERIA: Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. DATA EXTRACTION: Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. DATA SYNTHESIS: Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. HEADLINE RESULTS: Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical simulations facilitate learning under the right conditions. These include the following: providing feedback--51 (47%) journal articles reported that educational feedback is the most important feature of simulation-based medical education; repetitive practice--43 (39%) journal articles identified repetitive practice as a key feature involving the use of high-fidelity simulations in medical education; curriculum integration--27 (25%) journal articles cited integration of simulation-based exercises into the standard medical school or postgraduate educational curriculum as an essential feature of their effective use; range of difficulty level--15 (14%) journal articles address the importance of the range of task difficulty level as an important variable in simulation-based medical education; multiple learning strategies--11 (10%) journal articles identified the adaptability of high-fidelity simulations to multiple learning strategies as an important factor in their educational effectiveness; capture clinical variation--11 (10%) journal articles cited simulators that capture a wide variety of clinical conditions as more useful than those with a narrow range; controlled environment--10 (9%) journal articles emphasized the importance of using high-fidelity simulations in a controlled environment where learners can make, detect and correct errors without adverse consequences; individualized learning--10 (9%) journal articles highlighted the importance of having reproducible, standardized educational experiences where learners are active participants, not passive bystanders; defined outcomes--seven (6%) journal articles cited the importance of having clearly stated goals with tangible outcome measures that will more likely lead to learners mastering skills; simulator validity--four (3%) journal articles provided evidence for the direct correlation of simulation validity with effective learning. CONCLUSIONS: While research in this field needs improvement in terms of rigor and quality, high-fidelity medical simulations are educationally effective and simulation-based education complements medical education in patient care settings.
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“While technological advancements offer promising solutions through digital platforms, high-fidelity simulations, and streamlined feedback mechanisms, significant challenges remain in ensuring alignment with varying curricula, gathering longitudinal evidence of student growth, and developing flexible implementation models that can accommodate diverse learning objectives and timelines [12,13].”
From Formative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189 (2026) · cites this paper as [13]
In the citing paper
“However, it has been accepted that simulation facilitates learning when it is used in the appropriate conditions that include providing feedback, repetition, curriculum integration, individualized learning and controlled environment [28].”
From The virtual patient as a learning tool: a mixed quantitative qualitative study (2018) · cites this paper as [28]
In the citing paper
“This suggests that instructional strategies, whether technology-based or not, must include some solid principles from pedagogical theory that were incorporated to the VP course and some of what Issenberg et al. described as key for simulation-based learning [28].”
From The virtual patient as a learning tool: a mixed quantitative qualitative study (2018) · cites this paper as [28]
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“396 resident competency scores and surgical performance in the OR in both early and late stages of residency training [1,5-15].”
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“a controlled environment, individualized learning, capturing clinical variation, and defining outcomes.(22)”
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Experiential learning improves the learning and retention of endotracheal intubation
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Simulation-based otolaryngology – head and neck surgery boot camp: ‘how I do it’
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“The majority of recommendations to guide debriefings are most often the result of experts’ consensus or simple surveys, and are rarely informed by the results of rigorous research (Arafeh et al., 2010; Cheng et al., 2014; Issenberg et al., 2005; LevettJones & Lapkin, 2011).”
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“One of the reasons for the changes is concern for the patient’s safety [1, 2].”
BackgroundThe role of indoor positioning analytics in assessment of simulation‐based learning
Yan, L., Martínez‐Maldonado, R., Zhao, L., Dix, S., Jaggard, H., Wotherspoon, R., Li, X., & Gašević, D. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13262 · Cited by 49
Expressions of critical thinking in role-playing simulations: comparisons across roles
Ertmer, P. A., Ströbel, J., Cheng, X., Chen, X., Kim, H., Olesova, L., Sadaf, A., & Tomory, A. (2010) · Journal of Computing in Higher Education · doi:10.1007/s12528-010-9030-7 · Cited by 41
“In general, nursing simulations tend to revolve around the use of patient simulators, which offer students the chance to apply their knowledge in real situations without the fear of hurting patients (Issenberg et al. 2005).”
BackgroundStarkie, T., & Drake, E. J. (2013) · Canadian Journal of Anesthesia/Journal canadien d anesthésie · doi:10.1007/s12630-013-0045-1 · Cited by 41
Applications of 3‐dimensional printing in small‐animal surgery: A review of current practices
Altwal, J., Wilson, C. H., & Griffon, D. J. (2021) · Veterinary Surgery · doi:10.1111/vsu.13739 · Cited by 42
Boutros, P., Kassem, N., Nieder, J., Jaramillo, C., von Petersdorff, J., Walsh, F., Bärnighausen, T., & Barteit, S. (2023) · Healthcare · doi:10.3390/healthcare11212902 · Cited by 43
Sun, W., Xing, J., Dong, X., Yu, G., Feng, Z., & Shuai, L. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e35627 · Cited by 51
Luctkar‐Flude, M., Baker, C., Pulling, McGraw, Dagnone, Medves, Turner-Kelly, Baker, C., & Dagnone (2010) · Advances in Medical Education and Practice · doi:10.2147/amep.s14100 · Cited by 40
Technology-assisted education in graduate medical education: a review of the literature
Jwayyed, S., Stiffler, K. A., Wilber, S. T., Southern, A., Weigand, J. V., Bare, R., & Gerson, L. W. (2011) · International Journal of Emergency Medicine · doi:10.1186/1865-1380-4-51 · Cited by 40
“Issenberg and colleagues, in a systemic review of simulation-based education, identified 20 important guidelines they recommend authors should adhere to when conducting research on simulation-based education [27].”
BackgroundSportsman, S., Schumacker, R. E., & Hamilton, P. (2011) · Nursing Education Perspectives · doi:10.5480/1536-5026-32.4.259 · Cited by 40
“Issenberg et al. concluded that while research regarding simulation in medical education needed improvement in terms of rigor and quality, high-fidelity simulations are educationally effective and simulation-based education complements other forms of education. Weaver (2011) analyzed studies published since 1998 on th…”
BackgroundA New Paradigm for Surgical Procedural Training
Sachdeva, A. K., Buyske, J., Dunnington, G. L., Sanfey, H. A., Mellinger, J. D., Scott, D. J., Satava, R. M., Fried, G. M., Jacobs, L. M., & Burns, K. J. (2011) · Current Problems in Surgery · doi:10.1067/j.cpsurg.2011.08.003 · Cited by 40
Debriefing in Simulation and Beyond
Abatzis, V. T., & Littlewood, K. E. (2015) · International Anesthesiology Clinics · doi:10.1097/aia.0000000000000070 · Cited by 40
“Marshall can be credited with the development of military debriefing.(3) As the chief United States Army historian in WWII, Korea, and Vietnam, he developed debriefing methods to interview surviving personnel after combat.”
BackgroundPrakash, S., Bihari, S., Need, P., Sprick, C., & Schuwirth, L. (2017) · BMC Medical Education · doi:10.1186/s12909-017-0871-x · Cited by 40
Hall, K. (2017) · Clinical Simulation in Nursing · doi:10.1016/j.ecns.2017.04.002 · Cited by 40
Debriefing the Interprofessional Team in Medical Simulation
Salik, I., & Paige, J. T. (2021) · StatPearls · Cited by 40
Technology for Enhancing Chest Auscultation in Clinical Simulation
Ward, J. J., & Wattier, B. A. (2011) · Respiratory Care · doi:10.4187/respcare.01072 · Cited by 39
Simulation: A Panacea for interprofessional learning?
Reeves, S., & van Schaik, S. M. (2012) · Journal of Interprofessional Care · doi:10.3109/13561820.2012.678183 · Cited by 40
Formative feedback generation in a VR-based dental surgical skill training simulator
Yin, M. S., Haddawy, P., Suebnukarn, S., Kulapichitr, F., Rhienmora, P., Jatuwat, V., & Uthaipattanacheep, N. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103659 · Cited by 39
Fostering Adaptive Expertise Through Simulation
Clarke, S., Ilgen, J. S., & Regehr, G. (2023) · Academic Medicine · doi:10.1097/acm.0000000000005257 · Cited by 41
Development and Validation of a Novel Ear Simulator to Teach Pneumatic Otoscopy
Morris, E. A., Kesser, B. W., Peirce, S. M., & Keeley, M. (2011) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0b013e31822eac39 · Cited by 39
Weekly and Consecutive Day Neonatal Intubation Training
Ernst, K., Cline, W. L., Dannaway, D. C., Davis, E., Anderson, M. P., Atchley, C. B., & Thompson, B. M. (2014) · Academic Medicine · doi:10.1097/acm.0000000000000150 · Cited by 39
Computer‐based learning: Interleaving whole and sectional representation of neuroanatomy
Pani, J. R., Chariker, J. H., & Naaz, F. (2012) · Anatomical Sciences Education · doi:10.1002/ase.1297 · Cited by 39
Teaching Aseptic Technique for Central Venous Access Under Ultrasound Guidance
Latif, R. K., Bautista, A. F., Memon, S. B., Smith, E. A., Wang, C., Wadhwa, A. N., Carter, M. B., & Akça, O. (2011) · Anesthesia & Analgesia · doi:10.1213/ane.0b013e3182405eb3 · Cited by 39
Scholz, C., Mann, C., Kopp, V., Kost, B., Kainer, F., & Fischer, M. R. (2012) · Journal of Perinatal Medicine · doi:10.1515/jpm-2012-0052 · Cited by 39
“There are solid data that high-fi delity simulation cannot serve as a substitute for real-life exposure to real clinical challenges [13, 10] .”
BackgroundEppich, W., Nypaver, M. M., Mahajan, P., Denmark, K. T., Kennedy, C. S., Joseph, M. M., & Kim, I. (2012) · Pediatric Emergency Care · doi:10.1097/pec.0b013e31827b20d0 · Cited by 39
“Critical performance feedback to the trainee has been reported to be the most important beneficial feature of the simulation sessions.(9,69) The investment required for the development and maintenance of a simulation program can be substantial.”
BackgroundSupporting transitions in medical career pathways: the role of simulation-based education
Cleland, J., Patey, R. E., Thomas, I., Walker, K., O'Connor, P. E., & Russ, S. (2016) · Advances in Simulation · doi:10.1186/s41077-016-0015-0 · Cited by 39
“Also built in is an adherence to Issenberg’s highly evidence-based 10 conditions for effective simulation-based learning [70].”
BackgroundField, J. C., Stone, S. J., Orsini, C. A., Hussain, A., Vital, S. O., Crothers, A. J., & Walmsley, A. D. (2017) · European Journal Of Dental Education · doi:10.1111/eje.12276 · Cited by 39
Feasibility of Simulation-Based Medical Education in a Low-Income Country
Bulamba, F., Sendagire, C., Kintu, A., Hewitt‐Smith, A., Musana, F., Lilaonitkul, M., Ayebale, E. T., Law, T. J., Dubowitz, G., Kituuka, O., et al. (2018) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000345 · Cited by 39
Hege, I., Kononowicz, A. A., Berman, N. B., Lenzer, B., & Kiesewetter, J. (2018) · PubMed Central · doi:10.3205/zma001159 · Cited by 43
“Virtual patients are learner-centered, adaptable activities [31], [32] however, the degree of learner-centeredness is limited, because VPs are often used to standardize teaching and assessment [33].”
BackgroundSimulation as an Improvement Technique
Brazil, V. A., Purdy, E. I., & Bajaj, K. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009338172 · Cited by 39
Keskitalo, T. (2012) · Australasian Journal of Educational Technology · doi:10.14742/ajet.820 · Cited by 41
Rich-Narrative Case Study for Online PBL in Medical Education
Bizzocchi, J., & Schell, R. (2009) · Academic Medicine · doi:10.1097/acm.0b013e3181b6ead0 · Cited by 39
Metadata
- Authors
- Barry Issenberg, S., Mcgaghie, W. C., Petrusa, E. R., Lee Gordon, D., & Scalese, R. J.
- Affiliations
- Northwestern University (US)
- Duke Medical Center (US)
- University of Miami (US)
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2005-01
- Volume
- 27
- Issue
- 1
- Pages
- 10-28
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W2162661914
- Cited by
- 3,966
- References
- 203
- Citations by year
- 2026: 311 · 2025: 239 · 2024: 194 · 2023: 177 · 2022: 198 · 2021: 245 · 2020: 224 · 2019: 233 · 2018: 191 · 2017: 178 · 2016: 227 · 2015: 252 · 2014: 199 · 2013: 233 · 2012: 190
- FWCI
- 9.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Teacher (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Education › Simulation-Based Education in Healthcare
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Social Sciences › Education › Innovations in Medical Education
- Keywords
- high-fidelity simulation, simulation-based medical education, medical education, instructional feedback, repeated practice, curriculum integration, task difficulty, student outcomes, research quality, graduate medical education, student motivation, learner confidence, student self-efficacy, student self-assessment, student self-regulation, learner autonomy
- MeSH terms
- Clinical Competence, Education, Medical, Humans, Research Design, Software, Patient Simulation, Total Quality Management, Medical Errors
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