- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05284838
Facilitating Adaptive Expertise in Learning Computed Tomography (FAIL CT)
March 31, 2024 updated by: Leonardo Aliaga, Stanford University
The FAIL CT Study: Facilitating Adaptive Expertise in Learning Computed Tomography, a Multi-center Randomized Controlled Trial
The main objective of this study is to demonstrate that Error Management Training improves adaptive expertise in head computed tomography interpretation.
The investigators will conduct a randomized controlled trial comparing two learning strategies, Error Management Training vs Error Avoidance Training, in emergency medicine residents.
The investigators hypothesize that Error Management Training, as compared to Error Avoidance Training, will improve adaptive expertise, as measured by skills transfer, when used to teach head computed tomography interpretation to emergency medicine residents.
Study Overview
Status
Completed
Conditions
Detailed Description
Adaptive expertise is the ability to apply existing skills to novel situations.
Adaptive expertise enables physicians to reduce preventable medical errors when managing clinical scenarios not encountered during training.
However, residency curricula rarely address this learning outcome.
Error Management Training improves transfer of skills to new contexts and develops adaptive expertise.
Although this methodology has been shown to improve adaptive expertise in procedural skills, its impact on cognitive skills in medical training remains underexplored.
Error Management Training promises to improve patient care by developing emergency physicians' adaptive expertise.
However, the investigators need further evidence for its efficacy with cognitive skills in residency training.
The investigators aim to demonstrate that Error Management Training improves adaptive expertise in a cognitive skill, using head computed tomography interpretation as a model.
Study Type
Interventional
Enrollment (Actual)
150
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
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California
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Stanford, California, United States, 94305
- Stanford University
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
Yes
Description
Inclusion Criteria:
- Study participation will be available to all current emergency medicine residents at Stanford and at thirteen external sites.
Exclusion Criteria:
- Adults unable to consent
- Pregnant women
- Individuals who are not yet adults (infants, children, teenagers)
- Prisoners
- Medical students
- Residents from specialties other than emergency medicine
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Double
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Error Management Training (Difficult)
Participants receive the learning strategy Error Management Training and encounter difficult questions.
|
Error Management Training is used to teach head computed tomography interpretation.
Participants encounter difficult questions.
|
Experimental: Error Management Training (Easy)
Participants receive the learning strategy Error Management Training and encounter easy questions.
|
Error Management Training is used to teach head computed tomography interpretation.
Participants encounter easy questions.
|
Active Comparator: Error Avoidance Training
Participants receive the learning strategy Error Avoidance Training.
|
Error Avoidance Training used to teach head computed tomography interpretation.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Percent correct on an assessment of transfer of skills (adaptive expertise)
Time Frame: Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Participants will have to demonstrate transfer of head computed tomography interpretation skills by interpreting novel radiology cases different from those used in the instructional session.
Performance will be assessed by percent score on a head computed tomography interpretation test using novel radiology content not addressed in the instructional session.
Score range is 0-100%.
|
Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Percent correct on an assessment of post-session proficiency for learning objectives (routine expertise)
Time Frame: Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Participants will have to demonstrate direct application of the intervention's learning objectives by interpreting radiology cases similar to those used in the instructional session.
Performance will be assessed by percent score on a head computed tomography interpretation test using radiology content similar to that used in the instructional session.
Score range is 0-100%.
|
Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Effect of post-graduate year level on post-test performance
Time Frame: Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Performance on a head computed tomography interpretation test (both adaptive expertise and routine expertise cases) will be assessed by percent score, stratified by post-graduate year level to show differences across residency training stage.
Score range is 0-100%.
|
Immediately after instructional session (up to 60 minutes to complete the assessment)
|
Mediation effect of errors on performance on the adaptive expertise cases
Time Frame: Number of errors will be measured during the educational intervention
|
The number of errors made during the educational intervention will be measured for both the Error Management Training (Difficult) arm and the Error Management Training (Easy) arm.
A mediation analysis will be conducted to assess the effect of committing errors during learning on subsequent performance in the cases measuring adaptive expertise.
|
Number of errors will be measured during the educational intervention
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Investigators
- Principal Investigator: Leonardo Aliaga, MD, Stanford University
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Mylopoulos M, Brydges R, Woods NN, Manzone J, Schwartz DL. Preparation for future learning: a missing competency in health professions education? Med Educ. 2016 Jan;50(1):115-23. doi: 10.1111/medu.12893.
- Aliaga L, Clarke SO. Rethinking Radiology: An Active Learning Curriculum for Head Computed Tomography Interpretation. West J Emerg Med. 2022 Jan 1;23(1):47-51. doi: 10.5811/westjem.2021.10.53665.
- Pusic MV, Santen SA, Dekhtyar M, Poncelet AN, Roberts NK, Wilson-Delfosse AL, Cutrer WB. Learning to balance efficiency and innovation for optimal adaptive expertise. Med Teach. 2018 Aug;40(8):820-827. doi: 10.1080/0142159X.2018.1485887. Epub 2018 Aug 9.
- Royce CS, Hayes MM, Schwartzstein RM. Teaching Critical Thinking: A Case for Instruction in Cognitive Biases to Reduce Diagnostic Errors and Improve Patient Safety. Acad Med. 2019 Feb;94(2):187-194. doi: 10.1097/ACM.0000000000002518.
- King A, Holder MG Jr, Ahmed RA. Errors as allies: error management training in health professions education. BMJ Qual Saf. 2013 Jun;22(6):516-9. doi: 10.1136/bmjqs-2012-000945. Epub 2013 Jan 3.
- Dyre L, Tabor A, Ringsted C, Tolsgaard MG. Imperfect practice makes perfect: error management training improves transfer of learning. Med Educ. 2017 Feb;51(2):196-206. doi: 10.1111/medu.13208. Epub 2016 Dec 12.
- Gardner AK, Abdelfattah K, Wiersch J, Ahmed RA, Willis RE. Embracing Errors in Simulation-Based Training: The Effect of Error Training on Retention and Transfer of Central Venous Catheter Skills. J Surg Educ. 2015 Nov-Dec;72(6):e158-62. doi: 10.1016/j.jsurg.2015.08.002. Epub 2015 Sep 8.
- Keith N, Frese M. Effectiveness of error management training: a meta-analysis. J Appl Psychol. 2008 Jan;93(1):59-69. doi: 10.1037/0021-9010.93.1.59.
- Keith N, Frese M. Self-regulation in error management training: emotion control and metacognition as mediators of performance effects. J Appl Psychol. 2005 Jul;90(4):677-91. doi: 10.1037/0021-9010.90.4.677.
- Kua J, Lim WS, Teo W, Edwards RA. A scoping review of adaptive expertise in education. Med Teach. 2021 Mar;43(3):347-355. doi: 10.1080/0142159X.2020.1851020. Epub 2020 Nov 28.
- Eva KW. Diagnostic error in medical education: where wrongs can make rights. Adv Health Sci Educ Theory Pract. 2009 Sep;14 Suppl 1:71-81. doi: 10.1007/s10459-009-9188-9. Epub 2009 Aug 11.
- Soderstrom NC, Bjork RA. Learning versus performance: an integrative review. Perspect Psychol Sci. 2015 Mar;10(2):176-99. doi: 10.1177/1745691615569000.
- Metcalfe J. Learning from Errors. Annu Rev Psychol. 2017 Jan 3;68:465-489. doi: 10.1146/annurev-psych-010416-044022. Epub 2016 Sep 14.
- Mylopoulos M, Kulasegaram K, Woods NN. Developing the experts we need: Fostering adaptive expertise through education. J Eval Clin Pract. 2018 Jun;24(3):674-677. doi: 10.1111/jep.12905. Epub 2018 Mar 8.
- Mylopoulos M, Steenhof N, Kaushal A, Woods NN. Twelve tips for designing curricula that support the development of adaptive expertise. Med Teach. 2018 Aug;40(8):850-854. doi: 10.1080/0142159X.2018.1484082. Epub 2018 Jul 15.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
July 18, 2022
Primary Completion (Actual)
July 31, 2023
Study Completion (Actual)
September 30, 2023
Study Registration Dates
First Submitted
March 10, 2022
First Submitted That Met QC Criteria
March 10, 2022
First Posted (Actual)
March 17, 2022
Study Record Updates
Last Update Posted (Actual)
April 2, 2024
Last Update Submitted That Met QC Criteria
March 31, 2024
Last Verified
March 1, 2024
More Information
Terms related to this study
Other Study ID Numbers
- 64099
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
IPD Plan Description
No current plan to share data.
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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