{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T16:34:51Z","timestamp":1793723691954,"version":"4.6.1"},"reference-count":31,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2012,10,18]],"date-time":"2012-10-18T00:00:00Z","timestamp":1350518400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["asmepublications.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Education"],"published-print":{"date-parts":[[2012,11]]},"abstract":"<jats:p>\n                    Medical Education 2012:\n                    <jats:bold>46<\/jats:bold>\n                    : 1055\u20131062\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>CONTEXT\u2002<\/jats:bold>\n                    Simulation training has emerged as an effective way to complement clinical training of medical students. Yet outcomes from simulation training must be considered suboptimal when 25\u201330% of students fail to recognise a cardiac murmur on which they were trained 1\u2003hour previously. There are several possible explanations for failure to improve following simulation training, which include the impact of heightened emotions on learning and cognitive overload caused by interactivity with high\u2010fidelity simulators. This study was conducted to assess emotion during simulation training and to explore the relationships between emotion and cognitive load, and diagnostic performance.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>METHODS\u2002<\/jats:bold>\n                    We trained 84 Year\u20031 medical students on a scenario of chest pain caused by symptomatic aortic stenosis. After training, students were asked to rate their emotional state and cognitive load. We then provided training on a dyspnoea scenario before asking participants to diagnose the murmur in which they had been trained (aortic stenosis) and a novel murmur (mitral regurgitation). We used factor analysis to identify the principal components of emotion, and then studied the associations between these components of emotion and cognitive load and diagnostic performance.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>RESULTS\u2002<\/jats:bold>\n                    We identified two principal components of emotion, which we felt represented\n                    <jats:italic>invigoration<\/jats:italic>\n                    and\n                    <jats:italic>tranquillity<\/jats:italic>\n                    . Both of these were associated with cognitive load with adjusted regression coefficients of 0.63 (95% confidence interval [CI] 0.28\u20130.99; p\u2003=\u20030.001) and \u2212\u20030.44 (95% CI \u2212\u20030.77 to \u2212\u20030.10; p\u2003=\u20030.009), respectively. We found a significant negative association between cognitive load and the odds of subsequently identifying the trained murmur (odds ratio 0.27, 95% CI 0.11\u20130.67; p\u2003=\u20030.004).\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>CONCLUSIONS\u2002<\/jats:bold>\n                    We found that increased invigoration and reduced tranquillity during simulation training were associated with increased cognitive load, and that the likelihood of correctly identifying a trained murmur declined with increasing cognitive load. Further studies are needed to evaluate the impact on performance of strategies to alter emotion and cognitive load during simulation training.\n                  <\/jats:p>","DOI":"10.1111\/j.1365-2923.2012.04355.x","type":"journal-article","created":{"date-parts":[[2012,10,18]],"date-time":"2012-10-18T17:40:38Z","timestamp":1350582038000},"page":"1055-1062","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":265,"title":["Emotion, cognitive load and learning outcomes during simulation training"],"prefix":"10.1111","volume":"46","author":[{"given":"Kristin","family":"Fraser","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elise","family":"Teteris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heather","family":"Baxter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce","family":"Wright","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"McLaughlin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2012,10,18]]},"reference":[{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.1080\/01421590500046924"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365-2923.37.s1.6.x"},{"key":"e_1_2_11_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2929.2004.01959.x"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.49.8.725"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2923.2009.03412.x"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.1378\/chest.10-1107"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1202_4"},{"key":"e_1_2_11_9_2","doi-asserted-by":"publisher","DOI":"10.1037\/h0043158"},{"key":"e_1_2_11_10_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2923.2009.03498.x"},{"key":"e_1_2_11_11_2","first-page":"40","article-title":"Fidelity in the design of instructional simulations","volume":"15","author":"Alessi SM","year":"1988","journal-title":"J Comput Case Instr"},{"key":"e_1_2_11_12_2","doi-asserted-by":"crossref","unstructured":"RehmannA MitmanR ReynoldsM.1995.A Handbook of Flight Simulation Fidelity Requirements for Human Factors Research. 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