Cited by 172Innovations in Medical EducationVisual and Cognitive Learning ProcessesClinical Reasoning and Diagnostic Skills

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

From Theory to Practice: The Application of Cognitive Load Theory to the Practice of Medicine

Open access

Szulewski, Adam, Howes, Daniel, van Merriënboer, Jeroen J.G., Sweller, John·2021·Academic Medicine

DOI 10.1097/acm.0000000000003524

Open this paper in CoChat — free account

Abstract

Cognitive load theory has become a leading model in educational psychology and has started to gain traction in the medical education community over the last decade. The theory is rooted in our current understanding of human cognitive architecture in which an individual’s limited working memory and unlimited long-term memory interact during the process of learning. Though initially described as primarily a theory of learning, parallels between cognitive load theory and broader aspects of medical education as well as clinical practice are now becoming clear. These parallels are particularly relevant and evident in complex clinical environments, like resuscitation medicine. The authors have built on these connections to develop a recontextualized version of cognitive load theory that applies to complex professional domains and in which the connections between the theory and clinical practice are made explicit, with resuscitation medicine as a case study. Implications of the new model for medical education are also presented along with suggested applications.

Integrity signals

Registry

Crossref · 10.1097/acm.0000000000003524

Cites

36 of 36 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Executive functions
Diamond, A. (2013) · Annual Review of Psychology · doi:10.1146/annurev-psych-113011-143750 · Cited by 13,268
Cognitive Architecture and Instructional Design
Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998) · Educational Psychology Review · doi:10.1023/a:1022193728205 · Cited by 6,023
Self-citation
Long-term working memory.
Ericsson, K. A., & Kintsch, W. (1995) · Psychological Review · doi:10.1037/0033-295x.102.2.211 · Cited by 3,498
Deliberate Practice and the Acquisition and Maintenance of Expert Performance in Medicine and Related Domains
Ericsson, K. A. (2004) · Academic Medicine · doi:10.1097/00001888-200410001-00022 · Cited by 2,988
Naturalistic Decision Making
Klein, G. A. (2008) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872008x288385 · Cited by 2,434
Cognitive Architecture and Instructional Design: 20 Years Later
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09465-5 · Cited by 2,337
Self-citation
Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load
Sweller, J. (2010) · Educational Psychology Review · doi:10.1007/s10648-010-9128-5 · Cited by 2,020
Self-citation
Cognitive load theory in health professional education: design principles and strategies
Van Merriënboer, J. J. G., & Sweller, J. (2010) · Medical Education · doi:10.1111/j.1365-2923.2009.03498.x · Cited by 1,511
Self-citation
Decomposing adult age differences in working memory
Salthouse, T. A., & Babcock, R. L. (1991) · Developmental Psychology · doi:10.1037/0012-1649.27.5.763 · Cited by 1,373
Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load
Choi, H.-H., van Merriënboer, J. J. G., & Paas, F. (2014) · Educational Psychology Review · doi:10.1007/s10648-014-9262-6 · Cited by 413

Show all 36 references

Sorted by citations

Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load
Skulmowski, A., & Xu, K. M. (2022) · Educational Psychology Review · doi:10.1007/s10648-021-09624-7 · Cited by 678
The Validity of Physiological Measures to Identify Differences in Intrinsic Cognitive Load
Ayres, P., Lee, J. Y., PAAS, F. G. W. C., & van Merriënboer, J. J. G. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.702538 · Cited by 232
Virtual Reality Head-Mounted Displays in Medical Education
Tursø-Finnich, T., Jensen, R. O., Jensen, L. X., Konge, L., & Thinggaard, E. (2022) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000636 · Cited by 95
Cognitive Load Management: An Invaluable Tool for Safe and Effective Surgical Training
Howie, E. E., Dharanikota, H., Gunn, E., Ambler, O., DIAS, R. D., Wigmore, S. J., Skipworth, R. J. E., & Yule, S. (2023) · Journal of surgical education · doi:10.1016/j.jsurg.2022.12.010 · Cited by 94
The Assessment Burden in Competency-Based Medical Education: How Programs Are Adapting
Szulewski, A., Braund, H., Dagnone, D., McEwen, L., Dalgarno, N., Schultz, K., & Hall, A. K. (2023) · Academic Medicine · doi:10.1097/acm.0000000000005305 · Cited by 75
Self-citation
The Application of Cognitive Load Theory to the Design of Health and Behavior Change Programs: Principles and Recommendations
Baxter, K. A., Sachdeva, N., & Baker, S. (2025) · Health Education & Behavior · doi:10.1177/10901981251327185 · Cited by 99
Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions
Taylor, R. A., Sangal, R. B., Smith, M. E., Haimovich, A. D., Rodman, A., Iscoe, M. S., Pavuluri, S. K., Rose, C., Janke, A. T., Wright, D. S., et al. (2025) · Academic Emergency Medicine · doi:10.1111/acem.15066 · Cited by 62
Critical design choices in healthcare simulation education: a 4C/ID perspective on design that leads to transfer
Frèrejean, J., van Merriënboer, J. J. G., Condron, C. M., Strauch, U., & Eppich, W. (2023) · Advances in Simulation · doi:10.1186/s41077-023-00242-7 · Cited by 53
Project for Universal Management of Airways – part 1: concept and methods
Chrimes, N. C., Higgs, A., Law, J. A., Baker, P., Cooper, R. M., Greif, R. T., Kovacs, G. J., Myatra, S. N., O’Sullivan, E., Rosenblatt, W. H., et al. (2020) · Anaesthesia · doi:10.1111/anae.15269 · Cited by 46
Educating Anesthesiologists During the Coronavirus Disease 2019 Pandemic and Beyond
Martinelli, S. M., Chen, F., Isaak, R. S., Huffmyer, J. L., Neves, S. E., & Mitchell, J. (2020) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000005333 · Cited by 43
Measuring Cognitive Load in Virtual Reality Training via Pupillometry
Lee, J. Y., de Jong, N., Donkers, J. H. H. L. M., Jarodzka, H., & van Merriënboer, J. J. G. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3326473 · Cited by 53
The Effect of Animation-Guided Mindfulness Meditation on the Promotion of Creativity, Flow and Affect
Chen, H., Liu, C., Zhou, F., Chiang, C.-H., Chen, Y., Wu, K., Huang, D., Liu, C.-Y., & Chiou, W. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.894337 · Cited by 47
The medical pause: Importance, processes and training
Lee, J. Y., Szulewski, A., Young, J. Q., Donkers, J. H. H. L. M., Jarodzka, H., & van Merriënboer, J. J. G. (2021) · Medical Education · doi:10.1111/medu.14529 · Cited by 44
Self-citation
Association between Clinical Simulation Design Features and Novice Healthcare Professionals’ Cognitive Load: A Systematic Review and Meta-Analysis
Lapierre, A., Arbour, C., Maheu‐Cadotte, M., Vinette, B., Fontaine, G., & Lavoie, P. (2022) · Simulation & Gaming · doi:10.1177/10468781221120599 · Cited by 44
Cognitive load theory in workplace-based learning from the viewpoint of nursing students: application of a path analysis
Tabatabaee, S. S., Jambarsang, S., & Keshmiri‬, F. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05664-z · Cited by 47
Task complexity and cognitive load in simulation‐based education: A randomised trial
Tremblay, M., Rethans, J., & Dolmans, D. H. J. M. (2022) · Medical Education · doi:10.1111/medu.14941 · Cited by 44
The use of cognitive task analysis in clinical and health services research — a systematic review
Swaby, L., Shu, P., Hind, D., & Sutherland, K. (2022) · Pilot and Feasibility Studies · doi:10.1186/s40814-022-01002-6 · Cited by 37
An exploratory investigation of the measurement of cognitive load on shift: Application of cognitive load theory in emergency medicine
Vella, K. M., Hall, A. K., van Merriënboer, J. J. G., Hopman, W. M., & Szulewski, A. (2021) · AEM Education and Training · doi:10.1002/aet2.10634 · Cited by 32
Self-citation
A randomized controlled trial on evaluating clinician-supervised generative AI for decision support
Harari, R. E., Al-Taweel, A., Ahram, T., Keehner, M., & Shokoohi, H. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105701 · Cited by 32
Using cognitive load theory to evaluate and improve preparatory materials and study time for the flipped classroom
Fischer, K., Sullivan, A. M., Cohen, A. P., King, R. W., Cockrill, B. A., & Besche, H. C. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04325-x · Cited by 28
In Smart Classroom: Investigating the Relationship between Human–Computer Interaction, Cognitive Load and Academic Emotion
Nie, J., Yuan, Y., Chao, X., Li, Y., & Lv, L. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2190257 · Cited by 32
Diagnostic reasoning and cognitive error in emergency medicine: Implications for teaching and learning
Pelaccia, T., Sherbino, J., Wyer, P. C., & Norman, G. R. (2024) · Academic Emergency Medicine · doi:10.1111/acem.14968 · Cited by 31
How to select high-quality health educational short videos on social media? insights from youtube and douyin
Hu, Y., Yang, Y., Chen, N., Pang, Z., Zhong, X., & Sun, J. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08018-5 · Cited by 23
The future of simulation‐based medical education: Adaptive simulation utilizing a deep multitask neural network
Ruberto, A. J., Rodenburg, D., Ross, K., Sarkar, P., Hungler, P. C., Etemad, A., Howes, D., Clarke, D., McLellan, J., Wilson, D., et al. (2021) · AEM Education and Training · doi:10.1002/aet2.10605 · Cited by 22
Self-citation
Implementation considerations for the adoption of artificial intelligence in the emergency department
Cheng, R. K.-H., Aggarwal, A. K., Chakraborty, A., Harish, V., McGowan, M., Roy, A., Szulewski, A., & Nolan, B. (2024) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2024.05.020 · Cited by 21
Self-citation
Workload Assessment of Operators: Correlation Between NASA-TLX and Pupillary Responses
Wu, Y., Zhang, Y., & Zheng, B. (2024) · Applied Sciences · doi:10.3390/app142411975 · Cited by 20
MVP–Medical Situation, Values, and Plan: A Memorable and Useful Model for All Serious Illness Conversations
Horowitz, R. K., Hogan, L. A., & Carroll, T. (2020) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2020.07.022 · Cited by 20
A behavioural study of obedience in health professional students
Violato, E. M., Witschen, B., Violato, E., & King, S. (2021) · Advances in Health Sciences Education · doi:10.1007/s10459-021-10085-4 · Cited by 21
Immersive virtual reality learning and cognitive load: A multiple-day field study
Witte, B. D., Reynaert, V., Kieken, D., Jabbour, J., Demarey, C., Dumoulin, A., & Possik, J. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108853 · Cited by 19
Cognition and Learning
Doolittle, P. E., & Byrnes, M. K. (2023) · Wiley eBooks · doi:10.1002/9781119852865.ch3 · Cited by 20
A survey on large language models with multilingualism: recent advances and new frontiers
Huang, K., Mo, F., Zhang, X., Li, H., Li, Y., Zhang, Y., yi, W., Mao, Y., Liu, J., Xu, Y., et al. (2026) · Artificial Intelligence Review · doi:10.1007/s10462-026-11534-5 · Cited by 132
Exploring the relationship between emotion and cognitive load types during patient handovers
Young, J. Q., Thakker, K., John, M., Friedman, K. A., Sugarman, R., van Merriënboer, J. J. G., Sewell, J. L., & O’Sullivan, P. (2021) · Advances in Health Sciences Education · doi:10.1007/s10459-021-10053-y · Cited by 22
CLARE: Cognitive Load Assessment in Real-Time With Multimodal Data
Bhatti, A., Angkan, P., Behinaein, B., Mahmud, Z., Rodenburg, D., Braund, H., Mclellan, P. J., Ruberto, A. J., Harrison, G., Wilson, D., et al. (2025) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2025.3555517 · Cited by 30
Self-citation
Extending Cognitive Load Theory: The CLAM Framework for Biometric, Adaptive, and Ethical Learning
Vasilaki, E., & Mavrogianni, A. (2025) · Psychology International · doi:10.3390/psycholint7020040 · Cited by 26
Cognitive Ergonomics: A Review of Interventions for Outpatient Practice
Li-Wang, J., Townsley, A., & Katta, R. (2023) · Cureus · doi:10.7759/cureus.44258 · Cited by 14
Dynamic Cognitive Load Assessment in Virtual Reality
Elkin, R. L., Beaubien, J., Damaghi, N., Chang, T. P., & Kessler, D. O. (2024) · Simulation & Gaming · doi:10.1177/10468781241248821 · Cited by 17
Cognitive load theory in action: e-learning modules improve performance in simulation-based education. A pilot study
Gutiérrez, G., Lunsky, I. O., Heer, S. V., Szulewski, A., & Chaplin, T. (2023) · Canadian Journal of Emergency Medicine · doi:10.1007/s43678-023-00586-z · Cited by 19
Self-citation
Cognitive perspectives on maintaining physicians’ medical expertise: I. Reimagining Maintenance of Certification to promote lifelong learning
Rottman, B. M., Caddick, Z. A., Nokes‐Malach, T. J., & Fraundorf, S. H. (2023) · Cognitive Research Principles and Implications · doi:10.1186/s41235-023-00496-9 · Cited by 15
Toward better prevention of physician burnout: insights from individual participant data using the MD-specific Occupational Stressor Index and organizational interventions
Belkic, K. L. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1514706 · Cited by 15
Application of the R2C2 Model to In-the-Moment Feedback and Coaching
Lockyer, J., Lee-Krueger, R. C. W., Armson, H., Hanmore, T., Koltz, E., Könings, K. D., Mahalik, A., Ramani, S., Ordons, A. R. D., Trier, J., et al. (2023) · Academic Medicine · doi:10.1097/acm.0000000000005237 · Cited by 13
The Effects of Reflective Pauses on Performance in Simulation Training
Lee, J. Y., Donkers, J. H. H. L. M., Jarodzka, H., Sellenraad, G., Faber, T. J. E., & van Merriënboer, J. J. G. (2023) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000729 · Cited by 14
The Cognitive Load of Inpatient Consults: Development of the Consult Cognitive Load Instrument and Initial Validity Evidence
Brondfield, S., Blum, A. M., Lee, K., Linn, M. C., & O’Sullivan, P. S. (2021) · Academic Medicine · doi:10.1097/acm.0000000000004178 · Cited by 11
Students’ attitudes toward LLMs and its association with metacognitive abilities: A cross-sectional study
Yeh, S. N., & Siah, C. J. R. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104567 · Cited by 11
Clinical Reasoning in CanMEDS 2025
Young, M. E., Szulewski, A., Anderson, R., Gomez-Garibello, C. A., Thoma, B., & Monteiro, S. (2022) · Canadian Medical Education Journal · doi:10.36834/cmej.75843 · Cited by 10
Self-citation
When better data meets better design: How EHR data usability and system usability shape physicians' cognitive load
Merriweather, Lyytinen, K., Aron, D., & Cauley, M. R. (2026) · npj Digital Medicine · doi:10.1038/s41746-025-02243-4 · Cited by 9
“Cognitive load must be managed for effective problem-solving and clinical decision-making (correct decisions/reduction of errors), as levels of cognitive load in ﬂ uence decisions and outcomes 38,49 – 53 .”
Influential
Potential role of cannabis in ameliorating observed racialized disparities in cancer pain management
Gibson, L. P., Ferrer, R. A., Meghani, S. H., & Acevedo, A. M. (2024) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djae058 · Cited by 9
The mental workload of ICU nurses performing human‐machine tasks and associated factors: A cross‐sectional questionnaire survey
Yan, Y., Zhao, C., Bi, X., Or, C. K., & Ye, X. (2024) · Journal of Advanced Nursing · doi:10.1111/jan.16199 · Cited by 14
Multi-perspective analysis of daVinci surgical virtual reality training: a prospective randomized controlled study
Wang, R., Zheng, N., Liang, Y.-J., Cui, H., Ren, T., Xing, W., & Li, Y. (2025) · Journal of Robotic Surgery · doi:10.1007/s11701-025-02309-1 · Cited by 9
Education Research: High-Fidelity Simulation to Evaluate Diagnostic Reasoning Reveals Failure to Detect Viral Encephalitis in Medical Trainees
Pergakis, M. B., Chang, W.-T. W., Gutierrez, C., Neustein, B., Podell, J. E., Parikh, G. Y., Badjatia, N., Motta, M., Lerner, D. P., & Morris, N. A. (2022) · Neurology Education · doi:10.1212/ne9.0000000000200020 · Cited by 9
Using cognitive load theory to develop an emergency airway management curriculum: the Queen’s University Mastery Airway Course (QUMAC)
McGraw, R. C., Newbigging, J., Blackmore, E., Stacey, M., Mercer, C., Lam, W., Braund, H., & Gilic, F. (2023) · Canadian Journal of Emergency Medicine · doi:10.1007/s43678-023-00495-1 · Cited by 9
Classification of Cognitive Load Using Deep Learning Based on Eye Movement Indices
Wibirama, S., Alfarozi, S. A. I., Suhari, A. R., Fristiana, A. H., Nurlatifa, H., & Santosa, P. I. (2025) · IEEE Access · doi:10.1109/access.2025.3613292 · Cited by 8
Preparing for the future of cardiothoracic surgery with virtual reality simulation and surgical planning: a narrative review
Bakhuis, W., Max, S. A., Maat, A. P. W. M., Bogers, A. J. J. C., Mahtab, E. A. F., & Sadeghi, A. H. (2023) · Shanghai Chest · doi:10.21037/shc-22-63 · Cited by 8
Shaken and stirred: emotional state, cognitive load, and performance of junior residents in simulated resuscitation
Heer, S. V., Cofie, N., Gutiérrez, G., Upagupta, C., Szulewski, A., & Chaplin, T. (2021) · Canadian Medical Education Journal · doi:10.36834/cmej.71760 · Cited by 9
Self-citation
Sharing the Bandwidth in Cognitively Overloaded Teams and Systems: Mechanistic Insights from a Walk on the Wild Side of Clinical Reasoning
Boyle, J. G., Walters, M. R., Jamieson, S., & Durning, S. J. (2021) · Teaching and Learning in Medicine · doi:10.1080/10401334.2021.1924723 · Cited by 9
Cognitive load and processes during chest radiograph interpretation in the emergency department across the spectrum of expertise
Morra, M., Braund, H., Hall, A. K., & Szulewski, A. (2021) · AEM Education and Training · doi:10.1002/aet2.10693 · Cited by 7
Self-citation
Western Journal of Emergency Medicine
Saucedo, C., & Do, N. (2022) · Western Journal of Emergency Medicine · doi:10.5811/westjem.2022.3.56639 · Cited by 8
Teaching the technical performance of bronchoscopy to residents in a step-wise simulated approach: factors supporting learning and impacts on clinical work – a qualitative analysis
Eickelmann, A.-K., Waldner, N., & Huwendiek, S. (2021) · BMC Medical Education · doi:10.1186/s12909-021-03027-6 · Cited by 8
The transformation of Cure4Kids: Expanding knowledge transfer capacity
Berg, F., Conger, K., Avula, M., Hansen, C., Chatman, G., Provasnik, J., Alguire, K., Wellman, A., Chantada, G. L., Galindo, C. R., et al. (2024) · Pediatric Blood & Cancer · doi:10.1002/pbc.31135 · Cited by 7
User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative–Quantitative Study
Gasciauskaite, G., Malorgio, A., Castellucci, C., Budowski, A. D., Schweiger, G., Kolbe, M., Grande, B., Noethiger, C. B., Spahn, D. R., Roche, T. R., et al. (2023) · Bioengineering · doi:10.3390/bioengineering10030386 · Cited by 7
Trainee selection of tasks in postgraduate medical education: Is there a role for ‘cherry‐picking’ to optimise learning?
Blissett, S., Mensour, E., Shaw, J. M., Martin, L. J., Gauthier, S. R., de Bruin, A. B. H., Siu, S. C., & Sibbald, M. (2023) · Medical Education · doi:10.1111/medu.15180 · Cited by 8
Attention Among Health Care Professionals
Kissler, M. J., Porter, S., Knees, M., Kissler, K. J., Keniston, A., & Burden, M. A. (2024) · Annals of Internal Medicine · doi:10.7326/m23-3229 · Cited by 7
Impact of technology literacy, information literacy, and user satisfaction on the adoption of GAI-ChatGPT for learning, knowledge acquisition, and knowledge dissemination among Chinese students
Mwakapesa, D. S. (2025) · Information Development · doi:10.1177/02666669251366666 · Cited by 9
Use of Self-Efficacy Scale in Mass Casualty Incidents During Drill Exercises
Cardós-Alonso, C., Inzunza, M., Gyllencreutz, L., Ramírez, S. E., Vazquéz-Rodríguez, T., Fernandez, M. A., Blanco, A. G., & Cintora-Sanz, A. M. (2024) · BMC Health Services Research · doi:10.1186/s12913-024-11175-w · Cited by 6
Advancing diagnostic stewardship in contemporary medical practice
Ng, I. K., Liang, J. Z., Goh, W. G. W., Kee, A. C.-L., & Lim, T. K. (2025) · Diagnosis · doi:10.1515/dx-2025-0071 · Cited by 6
Time for a rethink? Discharge summary completion is often delayed and associated with increased readmission
Kleinig, O., Hains, L. R., Murugappa, A., Gluck, S., Marks, J., Gilbert, T., & Bacchi, S. (2025) · Internal Medicine Journal · doi:10.1111/imj.70150 · Cited by 5
The association between AI dependence, AI literacy, and critical thinking ability among nursing interns: a multicenter cross-sectional study
Cui, W., & Zhang, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1823047 · Cited by 6
Rapid-cycle deliberate practice telehealth as an integrative learning strategy in nurse practitioner education
Sheikh, K. R. (2022) · Journal of the American Association of Nurse Practitioners · doi:10.1097/jxx.0000000000000780 · Cited by 5
Understanding the Dark Side of LLMs' Intrinsic Self-Correction
Zhang, Q., Wang, D., Qian, H., Li, Y., Zhang, T., Huang, M., Xu, K., Li, H., Yan, L., & Qiu, H. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2025.acl-long.1314 · Cited by 36
Gamification-Based Teaching Methods for Pandemic and Outbreak Investigation Training Among Healthcare Professionals and Students: A Systematic Review
Krishnamoorthy, Y., Govindan, D., Karunakaran, M., Parveen, M., Poul, A. J., Manohar, A., & Rajendran, G. (2025) · Simulation & Gaming · doi:10.1177/10468781251338382 · Cited by 7
Managing cognitive load and enhancing metacognitive learning in postgraduate training and practice
Ng, I. K., Ko, C. J., & Lim, T. K. (2025) · Diagnosis · doi:10.1515/dx-2025-0067 · Cited by 5
Web-Based Virtual Environment Versus Face-To-Face Delivery for Team-Based Learning of Anesthesia Techniques Among Undergraduate Medical Students: Randomized Controlled Trial
Sripadungkul, D., Boonmak, S., Somjit, M., Plailaharn, N., Sriraj, W., & Boonmak, P. (2026) · JMIR Medical Education · doi:10.2196/80097 · Cited by 4
Applying an AI-human intelligence collaborative cognitive apprenticeship model in nursing psychology education: An explanatory sequential mixed-methods study
Li, J., Wang, Y., Zhu, X., Chen, X., Guo, R., Li, M., Yang, F., Su, X., Du, Z., Xu, H., et al. (2026) · Nurse Education in Practice · doi:10.1016/j.nepr.2026.104743 · Cited by 5
Mitigating Cognitive Overload in Nursing Education: An Integrative Review
Brown, J. E., Meza, C., & Sandiford, D. (2026) · Nurse Educator · doi:10.1097/nne.0000000000002126 · Cited by 4
The Effectiveness of Simulation in the Acquisition of Socioemotional Skills Related to Health Care: A Systematic Review of Systematic Reviews
Postigo, M. L., Abajas‐Bustillo, R., Martín-Melón, R., Ruiz-Pellón, N., & Ortego, C. (2024) · Clinical Simulation in Nursing · doi:10.1016/j.ecns.2024.101547 · Cited by 8
A Cognitive Aid Improves Adherence to Guidelines for Critical Endotracheal Intubation in the Resuscitation Room
Ben-Haddour, M., Colas, M., Lefevre-Scelles, A., Durand, Z., Gillibert, A., Roussel, M., & Joly, L. (2021) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000603 · Cited by 4
The Medical Pause in Simulation Training
Lee, J. Y. (2022) · Research Publications (Maastricht University) · doi:10.26481/dis.20220608jl · Cited by 4
The Transformative Teaching Framework: A roadmap for 21st century teaching
Fey, M. K., & Morse, K. J. (2024) · Journal of Professional Nursing · doi:10.1016/j.profnurs.2024.09.010 · Cited by 3
Education Research: ANSWER: A Multimodal Teaching Intervention for Neurology Undergraduate Medical Education
McElligott, L., Spooner, M., Cahir, C., Gillan, D., Adenan, M. H., Mulkerrin, G., Byrne, S., Delanty, N., Hevican, C., Hill, A. D. K., et al. (2025) · Neurology Education · doi:10.1212/ne9.0000000000200238 · Cited by 3
Development and Evaluation of an Innovative Web-Based Training, Learning, and Sharing Platform for Social Workers (Hong Kong Jockey Club SMART Family-Link Project): Mixed Methods Evaluation Study
Suen, M. M. T., Lai, A. Y. K., Wang, M. P., Ho, S. Y., & Lam, T. (2022) · JMIR Formative Research · doi:10.2196/32894 · Cited by 3
Coaching the coach: A randomized controlled study of a novel curriculum for procedural coaching during intubation
Miller, K. A., Auerbach, M. A., Bin, S. S., Donoghue, A. J., Kerrey, B. T., Mittiga, M. R., D'Ambrosi, G. R., Monuteaux, M. C., Marchese, A., & Nagler, J. (2023) · AEM Education and Training · doi:10.1002/aet2.10846 · Cited by 3
Impact of training in the supervision of clinical reasoning in the pediatric emergency department on residents’ perception of the on-call experience
Piétrement, C., Barbe, C., Bouazzi, L., & Maisonneuve, H. (2023) · Archives de Pédiatrie · doi:10.1016/j.arcped.2023.08.006 · Cited by 3
Human Behaviour in Veterinary Care
MacKay, J. R. D., & Pollock, K. (2023) · Animal Behaviour and Welfare Cases · doi:10.1079/abwcases.2023.0021 · Cited by 5
Cognitive load scale in learning formal definition of limit: A rasch model approach
Oktaviyanthi, R., Agus, R. N., Garcia, M., & Lertdechapat, K. (2024) · Infinity Journal · doi:10.22460/infinity.v13i1.p99-118 · Cited by 6
Collaboration Scripts or Checklists to Engage Novice Observers in Immersive Simulation?
Tremblay, M., Lafleur, A., Dieckmann, P., Rethans, J., & Dolmans, D. H. J. M. (2023) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000713 · Cited by 3
Evaluation of tracheostomy suctioning procedure among nursing and respiratory therapy students: wearable manikin vs. standard manikin
Lumowa, K., Lui, K. L., Daher, N. S., Baek, C., Tan, L. D., & Alismail, A. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1220632 · Cited by 3
Cognitive load theory: researching and planning teaching to maximise learning
Szulewski, A., van Gog, T., Paas, F., & Sweller, J. (2022) · Researching Medical Education · doi:10.1002/9781119839446.ch27 · Cited by 3
Self-citation
Allied health professionals cognitive workload scale in Malacca, Malaysia: A psychometric properties evaluation
Rasid, S. M., Rasdi, H. F. M., Cheng, J.-W., & Nata, D. H. M. S. (2024) · Work · doi:10.1177/10519815241290024 · Cited by 4
Junior doctors' experiences with vulnerability: A rich picture study
van Duin, T. S., de la Croix, A., Jaarsma, D. A. D. C., Versluis, M. A. C., & Filho, C. (2026) · Medical Education · doi:10.1111/medu.70135 · Cited by 2
Design an adaptive e-learning environment based on personalized factors and its impact on the development of students' metacognitive thinking skills
issa, S. A. M., & El-Sabagh, H. A. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1765181 · Cited by 5
Exploring cognitive load in anatomy education: a study of 3D virtual reality and 2D learning environments using fNIRS
Johannessen, E., Benjamin, R., Hungler, P. C., Angkan, P., & Szulewski, A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1767614 · Cited by 2
Self-citation
Comorbid Patterns in the Homeless Population: A Theoretical Model to Enhance Patient Care
Hans, K., Mike, L., Heidel, R., Benavides, P., Arnce, R., & Talley, J. (2022) · Western Journal of Emergency Medicine · doi:10.5811/westjem.2021.10.52539 · Cited by 2
Beyond the Task: Developing a Tool to Measure Workplace Characteristics That Affect Cognitive Load and Learning
Blissett, S., Rodriguez, S., Qasim, A., & O’Sullivan, P. (2024) · Academic Medicine · doi:10.1097/acm.0000000000005763 · Cited by 2
Módulo de promoción del uso responsable de antimicrobianos en odontología: diseño instruccional guiado por la teoría de carga cognitiva
Isbej, L., Oyarzo, N., Véliz, C., & Ríos, J. C. (2024) · Revista Médica Clínica Las Condes · doi:10.1016/j.rmclc.2024.08.004 · Cited by 1
What is the learning effect of video review in postgraduate medical education: a systematic review
Robbrecht, M., Winckel, M. V., Mulder, A., & Embo, M. P. C. (2025) · BMC Medical Education · doi:10.1186/s12909-024-06515-7 · Cited by 2
Cognitive Frailty for Young Breast Cancer Survivors After Chemotherapy: Implication for the Design of Health Education Materials
Jiang, L., Liu, Y., Wiley, J. F., Zhang, C., Wang, X., & Hu, Y. (2025) · Cancer Care Research Online · doi:10.1097/cr9.0000000000000069 · Cited by 2
Achieving Reliable Mastery of Emergency Airway Management Skills Through 4-Component Instructional Design
Gilic, F., McGraw, R. C., Newbigging, J., Blackmore, E., Stacey, M., Mercer, C., Neufeld, T., Johannessen, E., Lam, W., Hall, R., et al. (2025) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000847 · Cited by 2
Process-oriented metrics to provide feedback and assess the performance of students who are learning surgical procedures: The percutaneous dilatational tracheostomy case
Martínez, J. J., Galvez-Yanjari, V., de la Fuente, R., Catalina Kychenthal, L., Kattan, E., Bravo, S., Muñoz-Gama, J., & Sepúlveda, M. (2022) · Medical Teacher · doi:10.1080/0142159x.2022.2073209 · Cited by 2
‘They didn’t do anything wrong! What will I talk about?’
Fey, M. K., & Johnson, B. K. (2023) · International Journal of Healthcare Simulation · doi:10.54531/gevl9221 · Cited by 2
Can AnatomicalTerms.info with its synonyms and succinct open definitions be a solution to address variations in usage of anatomical terminology?
Gobée, O. P., Sulaiman, S., Boaz, N. T., Mork, A. L., & Whitmore, I. (2024) · Anatomical Science International · doi:10.1007/s12565-024-00761-x · Cited by 3
Teaching Before, During, and After a Surgical Resuscitation
Schenarts, P. J., Scarborough, A. J., Abraham, R. J., & Philip, G. (2023) · Surgical Clinics of North America · doi:10.1016/j.suc.2023.10.004 · Cited by 1

Authors: Szulewski, A., Howes, D., van Merriënboer, J. J. G., & Sweller, J.
Affiliations: Queen's University (CA)
Maastricht University (NL)
UNSW Sydney (AU)
Corresponding author: Szulewski, Adam
ORCID: Szulewski, Adam
van Merriënboer, Jeroen J.G.
Sweller, John
Venue: Academic Medicine
Publisher: Oxford University Press (OUP)
Published: 2020-12-29
Volume: 96
Issue: 1
Pages: 24-30
ISSN: 1040-2446 (ISSN-L)
DOI: 10.1097/acm.0000000000003524
OpenAlex: W3029841721
Cited by: 171
References: 36
Citations by year: 2026: 44 · 2025: 35 · 2024: 27 · 2023: 32 · 2022: 16 · 2021: 14 · 2020: 3
FWCI: 12.19
Type: journal article
Language: en
Open access: green
cris.maastrichtuniversity.nl
Licence: other-oa
Locations: Academic Medicine (publishedVersion)
PubMed (publishedVersion)
Research Publications (Maastricht University) (publishedVersion, other-oa)
Research Publications (Maastricht University) (submittedVersion, other-oa)
Topics: Social Sciences › Education › Innovations in Medical Education
Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
Keywords: cognitive load theory, medical education, clinical practice, working memory, long-term memory, resuscitation medicine, clinical decision-making
MeSH terms: Adult, Attitude of Health Personnel, Cognition, Delivery of Health Care, Education, Medical, Female, Humans, Learning, Male, Memory, Physicians, Students, Medical, Models, Educational, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

From Theory to Practice: The Application of Cognitive Load Theory to the Practice of Medicine

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks