Capturing growth curves of medical students' clinical skills performance.
Journal
The clinical teacher
ISSN: 1743-498X
Titre abrégé: Clin Teach
Pays: England
ID NLM: 101227511
Informations de publication
Date de publication:
12 2023
12 2023
Historique:
received:
24
05
2023
accepted:
31
07
2023
medline:
22
11
2023
pubmed:
22
8
2023
entrez:
22
8
2023
Statut:
ppublish
Résumé
A benefit of a milestone or Entrustable Professional Activity (EPA) assessment framework is the ability to capture longitudinal performance with growth curves using multi-level modelling (MLM). Growth curves can inform curriculum design and individualised learning. Residency programmes have found growth curves to vary by resident and by milestone. Only one study has analysed medical students' growth curves for EPAs. Analysis of EPA growth curves is critical because no change in performance raises concerns for EPAs as an assessment framework. Spencer Fox Eccles School of Medicine-University of Utah students' workplace-based assessment ratings for 7 EPAs were captured at 3 time-points in years 3-4 of AY2017-2018 to AY2020-2021. MLM was used to capture EPA growth curves and determine if variation in growth curves was explained by internal medicine (IM) clerkship order. A curvilinear slope significantly captured 256 students' average ratings overtime for EPA1a-history-taking, EPA2-clinical reasoning, EPA3-diagnostics, EPA5-documentation and EPA6-presentation, and a linear slope significantly captured EPA9-teamwork ratings, p ≤ 0.001. Growth curves were steepest for EPA2-clinical reasoning and EPA3-diagnostics. Growth curves varied by students, p < 0.05 for all EPA ratings, but IM clerkship rotation order did not significantly explain the variance, p > 0.05. The increase in ratings from Year 3 to Year 4 provides validity evidence for use of EPAs in an assessment framework. Students may benefit from more curriculum/skills practice for EPA2-clinical reasoning and EPA3-diagnostics prior to year 3. Variation in student's growth curves is important for coaching and skill development; a one size fits all approach may not suffice.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e13623Informations de copyright
© 2023 Association for the Study of Medical Education and John Wiley & Sons Ltd.
Références
Accreditation Council for Graduate Medical Education. Milestones bibliography. Published December 2021. Accessed August 1, 2022. https://www.acgme.org/globalassets/pdfs/milestones/milestones-bibliography---december-2021-final.pdf
Association of American Medical Colleges. Core entrustable professional activities for entering residency: curriculum developers' guide. Published 2014. Accessed August 1, 2022.
Shorey S, Lau TC, Lau ST, Ang E. Entrustable professional activities in health care education: a scoping review. Med Educ. 2019;53(8):766-777. https://doi.org/10.1111/medu.13879
Meyer EG, Chen HC, Uijtdehaage S, Durning SJ, Maggio LA. Scoping review of entrustable professional activities in undergraduate medical education. Acad Med. 2019;94(7):1040-1049. https://doi.org/10.1097/ACM.0000000000002735
Tanaka P, Park YS, Roby J, Ahn K, Kakazu C, Udani A, et al. Milestone learning trajectories of residents at five anesthesiology residency programs. Teach Learn Med. 2021;33(3):304-313. https://doi.org/10.1080/10401334.2020.1842210
Curran PJ, Obeidat K, Losardo D. Twelve frequently asked questions about growth curve modeling. J Cogn Dev. 2010;11(2):121-136. https://doi.org/10.1080/15248371003699969
Ramsay CR, Grant AM, Wallace SA, Garthwaite PH, Monk AF, Russell IT. Statistical assessment of the learning curves of health technologies. Health Technol Assess. 2001;5(12): 1-79. https://doi.org/10.3310/hta5120
Howard NM, Cook DA, Hatala R, Pusic MV. Learning curves in health professions education simulation research. Simul Healthc. 2021;16(2):128-135. https://doi.org/10.1097/SIH.0000000000000477
Pusic MV, Boutis K, Pecaric MR, Savenkov O, Beckstead JW, Jaber MY. A primer on the statistical modelling of learning curves in health professions education. Adv Health Sci Educ Theory Pract. 2017;22(3):741-759. https://doi.org/10.1007/s10459-016-9709-2
Hatala R, Gutman J, Lineberry M, Triola M, Pusic M. How well is each learner learning? Validity investigation of a learning curve-based assessment approach for ECG interpretation. Adv Health Sci Educ Theory Pract. 2019;24(1):45-63. https://doi.org/10.1007/s10459-018-9846-x
Mema B, Mylopoulos M, Tekian A, Park YS. Using learning curves to identify and explain growth patterns of learners in bronchoscopy simulation: a mixed-methods study. Acad Med. 2020;95(12):1921-1928. https://doi.org/10.1097/ACM.0000000000003595
Pusic M, Pecaric M, Boutis K. How much practice is enough? Using learning curves to assess the deliberate practice of radiograph interpretation. Acad Med. 2011;86(6):731-736. https://doi.org/10.1097/ACM.0b013e3182178c3c
Park YS, Hamstra SJ, Yamazaki K, Holmboe E. Longitudinal reliability of milestones-based learning trajectories in family medicine residents. JAMA Netw Open. 2021;4(12):e2137179. https://doi.org/10.1001/jamanetworkopen.2021.37179
Violato C, Cullen MJ, Englander R, Murray KE, Hobday PM, Borman-Shoap E, et al. Validity evidence for assessing entrustable professional activities during undergraduate medical education. Acad Med. 2021;96(7S):S70-S75. https://doi.org/10.1097/ACM.0000000000004090
Thurstone LL. The learning curve equation. Psychol Monogr. 1919;26(3):i-51. https://doi.org/10.1037/h0093187
Ericsson KA, Krampe RT, Tesch-Romer C. The role of deliberate practice in the acquisition of expert performance. Psychol Rev. 1993;100(3):363-406. https://doi.org/10.1037/0033-295X.100.3.363
Ericsson KA. Acquisition and maintenance of medical expertise: a perspective from the expert-performance approach with deliberate practice. Acad Med. 2015;90(11):1471-1486. https://doi.org/10.1097/ACM.0000000000000939
Heck RH, Thomas SL, Tabata LN. Multilevel and longitudinal modeling with IBM SPSS 2nd ed. New York City, NY: Routledge; 2013.
Hoffman L. Longitudinal analysis: modeling within-person fluctuation and change 1st ed. New York City, NY: Routledge; 2015.
Pleugh JL. A practical guide to multilevel modeling. J Sch Psychol. 2010;48(1):85-112. https://doi.org/10.1016/j.jsp.2009.09.002
Raykov T, Marcoulides GA. A first course in structural equation modeling 2nd ed. Lawrence Erlbaum Associates Inc; 2006.
Krupat E. Critical thoughts about the core entrustable professional activities in undergraduate medical education. Acad Med. 2018;93(3):371-376. https://doi.org/10.1097/ACM.0000000000001865
Tekain A. Are all EPAs really EPAs? Med Teach. 2017;39(3):232-233. https://doi.org/10.1080/0142159X.2016.1230665
Van Der Vleuten CPM, Schuwirth LW. Assessing professional competence: from methods to programmes. Med Educ. 2005;39(3):309-317. https://doi.org/10.1111/j.1365-2929.2005.02094.x
Baig LA, Violato C, Crutcher RA. Assessing clinical communication skills in physicians: are the skills context specific or generalizable. BMC Med Educ. 2009;9(1):22. https://doi.org/10.1186/1472-6920-9-22
Schuwirth L. Is assessment of clinical reasoning still the holy grail? Med Educ. 2009;43(4):298-300. https://doi.org/10.1111/j.1365-2923.2009.03290.x
Norman GR, Tugwell P, Feightner HW, Muzzin L. Knowledge and clinical problem-solving ability. Med Educ. 1985;19(5):344-356. https://doi.org/10.1111/j.1365-2923.1985.tb01336.x
McBee E, Ratcliffe T, Schuwirth L, O'Neill D, Meyer H, Madden SJ, et al. Context and clinical reasoning. Perspect Med Educ. 2022;7(4):256-263. https://doi.org/10.1007/S40037-018-0417-X