Preuve de la validité du score de la qualité de l’évaluation pour l’apprentissage : une mesure de qualité pour les commentaires des superviseurs dans la formation médicale fondée sur les compétences

Auteurs-es

DOI :

https://doi.org/10.36834/cmej.74860

Résumé

Contexte : Dans la formation médicale fondée sur les compétences (FMFC), l’évaluation programmatique s’appuie sur les commentaires narratifs des superviseurs en lien avec les activités professionnelles confiables (EPA). En revanche, la qualité de ces commentaires n’est pas évaluée. Il existe des preuves de la validité du score QuAL (qualité de l’évaluation pour l’apprentissage, Quality of Assessment for Learning en anglais) pour l’évaluation de l’utilité des commentaires de rétroaction courts lors de la supervision par observation directe.

Objectif : Nous avons tenté de démontrer la validité du score QuAL aux fins de l’évaluation de la qualité des commentaires narratifs des superviseurs pour une APC en interrogeant les principaux utilisateurs finaux des rétroactions : les résidents, les conseillers pédagogiques et les membres du comité de compétence.

Méthodes : En 2020, les auteurs ont sélectionné au hasard 52 commentaires narratifs anonymisés dans deux bases de données d’APC en médecine d’urgence au moyen d’un échantillonnage intentionnel. Six collaborateurs (deux résidents, deux conseillers pédagogiques et deux membres de comités de compétence) ont été recrutés dans chacun des quatre programmes de résidence en médecine d’urgence (Saskatchewan, McMaster, Ottawa et Calgary) pour évaluer ces commentaires à l’aide d’un score d’utilité et du score QuAL.  La corrélation entre l’utilité et le score QuAL a été calculée à l’aide du coefficient de corrélation de Pearson. Les sources de variance et la fiabilité ont été calculées à l’aide d’une étude de généralisabilité.

Résultats : Tous les collaborateurs (n=24) ont réalisé l’étude complète.  Le score QuAL présentait une corrélation positive élevée avec le score d’utilité parmi les résidents (r=0,80) et les conseillers pédagogiques (r=0,75) et une corrélation modérément élevée parmi les membres du comité de compétence (r=0,68).  L’étude de généralisation a révélé que la principale source de variance était le commentaire, ce qui indique que l’outil a fonctionné avec une efficacité égale pour tous les évaluateurs.

Conclusion : Le score QuAL peut servir de mesure des résultats pour l’évaluation des superviseurs par les programmes, et de ressource pour le perfectionnement du corps professoral.

Statistiques

Chargement des statistiques…

Bibliographies de l'auteur-e

Sim Singh, University of Saskatchewan

Sim Singh, BSc, MD Candidate is a medical student at the University of Saskatchewan, Saskatoon, SK, Canada

Brent Thoma, University of Saskatchewan

Brent Thoma, MD, MA, MSc is an associate professor, Department of Emergency Medicine, University of Saskatchewan, Saskatoon, SK, Canada. He is also a clinician educator, Royal College of Physicians and Surgeons of Canada

Catherine Patocka, University of Calgary

Catherine Patocka, MD, MHPE is a clinical associate professor, Department of Emergency Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Warren Cheung, University of Ottawa

Warren J. Cheung, MD, MMEd is an associate professor, Department of Emergency Medicine, University of Ottawa, Ottawa, ON, Canada. He is also a Clinician Educator, Royal College of Physicians and Surgeons of Canada, Ottawa, ON, Canada.

Sandra Monteiro, McMaster University

Sandra Monteiro, PhD is an associate professor, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada. She is also Director of Scholarship at the Centre for Simulation Based Learning and Scientist, McMaster Education Research, Innovation, and Theory (MERIT), Hamilton, ON, Canada.

Teresa M Chan, McMaster University

Teresa M. Chan, MD, MHPE is an associate professor, Divisions of Emergency Medicine and Education and Innovation in the Department of Medicine, McMaster University, Hamilton, ON, Canada. She is also associate dean, continuing professional development within the Faculty of Health Sciences and clinician scientist, McMaster Education Research, Innovation, and Theory (MERIT) at McMaster University in Hamilton, ON, Canada.

Références

Frank JR, Snell LS, Cate OT, et al. Competency-based medical education: theory to practice. Med Teach. 2010 Aug;32(8):638-45. https://doi.org/10.3109/0142159X.2010.501190

Lockyer J, Carraccio C, Chan MK, et al. Core principles of assessment in competency-based medical education. Med Teach. 2017 Jun 3;39(6):609-16. https://doi.org/10.1080/0142159X.2017.1315082

Cheung WJ, Patey AM, Frank JR, Mackay M, Boet S. Barriers and enablers to direct observation of trainees' clinical performance: a qualitative study using the theoretical domains framework. Acad Med. 2019 Jan;94(1):101-14. https://doi.org/10.1097/ACM.0000000000002396

Ginsburg S, van der Vleuten C, Eva KW, Lingard L. Hedging to save face: a linguistic analysis of written comments on in-training evaluation reports. Adv Health Sci Educ. 2016 Mar;21(1):175-88. https://doi.org/10.1007/s10459-015-9622-0

Scarff CE, Bearman M, Chiavaroli N, Trumble S. Keeping mum in clinical supervision: private thoughts and public judgements. Med Educ. 2019 Feb;53(2):133-42. https://doi.org/10.1111/medu.13728

Sherbino J, Bandiera G, Doyle K, et al. The competency-based medical education evolution of Canadian emergency medicine specialist training. CJEM. 2020 Jan;22(1):95-102. https://doi.org/10.1017/cem.2019.417

Thoma B, Hall AK, Clark K, et al. evaluation of a national competency-based assessment system in emergency medicine: a CanDREAM study. J Grad Med Educ. 2020 Aug;12(4):425-34.

https://doi.org/10.4300/JGME-D-19-00803.1

Chan TM, Sherbino J, Mercuri M. Nuance and noise: lessons learned from longitudinal aggregated assessment data. J Grad Med Educ. 2017 Dec;9(6):724-9. https://doi.org/10.4300/JGME-D-17-00086.1

Cook DA, Kuper A, Hatala R, Ginsburg S. When assessment data are words: validity evidence for qualitative educational assessments. Acad Med. 2016 Oct;91(10):1359-69. https://doi.org/10.1097/ACM.0000000000001175

Ginsburg S, van der Vleuten CPM, Eva KW. The hidden value of narrative comments for assessment: a quantitative reliability analysis of qualitative data. Acad Med. 2017 Nov;92(11):1617-21. https://doi.org/10.1097/ACM.0000000000001669

Thoma B, Caretta-Weyer H, et al. Becoming a deliberately developmental organization: using competency based assessment data for organizational development. Med Teach. 2021 Jul 3;43(7):801-9. https://doi.org/10.1080/0142159X.2021.1925100

Chan TM, Sebok-Syer SS, Sampson C, Monteiro S. The Quality of Assessment of Learning (Qual) score: validity evidence for a scoring system aimed at rating short, workplace-based comments on trainee performance. Teach Learn Med. 2020 May 26;32(3):319-29. https://doi.org/10.1080/10401334.2019.1708365

Cook DA, Brydges R, Ginsburg S, Hatala R. A contemporary approach to validity arguments: a practical guide to Kane's framework. Med Educ. 2015 Jun;49(6):560-75. https://doi.org/10.1111/medu.12678

Tri-Council Policy Statement 2018. Available from: https://ethics.gc.ca/eng/tcps2-eptc2_2018_chapter2-chapitre2.html

Bismil R, Dudek NL, Wood TJ. In-training evaluations: developing an automated screening tool to measure report quality. Med Educ. 2014 Jul;48(7):724-32. https://doi.org/10.1111/medu.12490

Monteiro S, Sullivan GM, Chan TM. Generalizability theory made simple(r): an introductory primer to g-studies. J Grad Med Educ. 2019 Aug 1;11(4):365-70. https://doi.org/10.4300/JGME-D-19-00464.1

Schober P, Boer C, Schwarte LA. Correlation coefficients: appropriate use and interpretation. Anesth Analg. 2018 May;126(5):1763-8. https://doi.org/10.1213/ANE.0000000000002864

Streiner DL. Starting at the beginning: an introduction to coefficient alpha and internal consistency. J Pers Assess. 2003 Feb;80(1):99-103. https://doi.org/10.1207/S15327752JPA8001_18

Vleuten CPM, Norman GR, Graaff E. Pitfalls in the pursuit of objectivity: issues of reliability. Med Educ. 1991 Mar;25(2):110-8. https://doi.org/10.1111/j.1365-2923.1991.tb00036.x

Watling CJ, Ginsburg S. Assessment, feedback and the alchemy of learning. Med Educ. 2019 Jan;53(1):76-85. https://doi.org/10.1111/medu.13645

Ginsburg S, van der Vleuten CP, Eva KW, Lingard L. Cracking the code: residents' interpretations of written assessment comments. Med Educ. 2017 Apr;51(4):401-10. https://doi.org/10.1111/medu.13158

Sebok-Syer SS, Klinger DA, Sherbino J, Chan TM. Mixed messages or miscommunication? investigating the relationship between assessors' workplace-based assessment scores and written comments: Acad Med. 2017 Dec;92(12):1774-9. https://doi.org/10.1097/ACM.0000000000001743

Acai A, Li SA, Sherbino J, Chan TM. Attending emergency physicians' perceptions of a programmatic workplace-based assessment system: the McMaster Modular Assessment Program (McMAP). Teach Learn Med. 2019 Aug 8;31(4):434-44. https://doi.org/10.1080/10401334.2019.1574581

Cheung WJ, Chan TM, Hauer KE, et al. CAEP 2019 Academic Symposium: got competence? best practices in trainee progress decisions. CJEM. 2020 Mar;22(2):187-93. https://doi.org/10.1017/cem.2019.480

Hodges B. Assessment in the post-psychometric era: Learning to love the subjective and collective. Med Teach. 2013 Jul;35(7):564-8. https://doi.org/10.3109/0142159X.2013.789134

Chan TM, Paterson QS, Hall AK, et al. Outcomes in the age of competency-based medical education: Recommendations for emergency medicine training in Canada from the 2019 symposium of academic emergency physicians. CJEM. 2020 Mar;22(2):204-14. https://doi.org/10.1017/cem.2019.491

Chan T, Sebok-Syer S, Thoma B, Wise A, Sherbino J, Pusic M. Learning analytics in medical education assessment: the past, the present, and the future. Promes S, editor. AEM Educ Train. 2018 Apr;2(2):178-87. https://doi.org/10.1002/aet2.10087

Ginsburg S, Gingerich A, Kogan JR, Watling CJ, Eva KW. Idiosyncrasy in assessment comments: do faculty have distinct writing styles when completing in-training evaluation reports? Acad Med. 2020 Nov;95(11S):S81-8. https://doi.org/10.1097/ACM.0000000000003643

Dudek NL, Marks MB, Bandiera G, White J, Wood TJ. Quality in-training evaluation reports-does feedback drive faculty performance? Acad Med. 2013 Aug;88(8):1129-34. https://doi.org/10.1097/ACM.0b013e318299394c

Zhang R. Automated assessment of medical training evaluation text. AMIA Annu Symp Proc. 2012;1459-68.

Ötleş E, Kendrick D, Solano QP, et al. Using natural language processing to automatically assess feedback quality: findings from three surgical residencies. Acad Med. 2021 May 4; Publish Ahead of Print. Available from: https://journals.lww.com/10.1097/ACM.0000000000004153 [Accessed May 31, 2021].

Ross S, Hamza D, Zulla R, Stasiuk S, Nichols D. Development of and preliminary validity evidence for the EFeCT feedback scoring tool. J Grad Med Educ. 2022 Feb 1;14(1):71-9. https://doi.org/10.4300/JGME-D-21-00602.1

ten Cate O, Regehr G. the power of subjectivity in the assessment of medical trainees: Acad Med. 2019 Mar;94(3):333-7. https://doi.org/10.1097/ACM.0000000000002495

Gomez-Garibello C, Young M. Emotions and assessment: considerations for rater-based judgements of entrustment. Med Educ. 2018 Mar;52(3):254-62. https://doi.org/10.1111/medu.13476

Watling C, LaDonna KA, Lingard L, Voyer S, Hatala R. 'Sometimes the work just needs to be done': socio-cultural influences on direct observation in medical training. Med Educ. 2016 Oct;50(10):1054-64. https://doi.org/10.1111/medu.13062

Gingerich A, Regehr G, Eva KW. Rater-based assessments as social judgments: rethinking the etiology of rater errors: Acad Med. 2011 Oct;86:S1-7. https://doi.org/10.1097/ACM.0b013e31822a6cf8

Ginsburg S, Kogan JR, Gingerich A, Lynch M, Watling CJ. taken out of context: hazards in the interpretation of written assessment comments. Acad Med. 2020 Jul;95(7):1082-8. https://doi.org/10.1097/ACM.0000000000003047

Téléchargements

Publié-e

2022-08-16

Comment citer

1.
Woods R, Singh S, Thoma B, Patocka C, Cheung W, Monteiro S, Chan TM. Preuve de la validité du score de la qualité de l’évaluation pour l’apprentissage : une mesure de qualité pour les commentaires des superviseurs dans la formation médicale fondée sur les compétences. Can. Med. Ed. J [Internet]. 16 août 2022 [cité 21 nov. 2024];13(6):19-35. Disponible à: https://dev.journalhosting.ucalgary.ca/index.php/cmej/article/view/74860

Numéro

Rubrique

Recherch Originale

Articles les plus lus du,de la,des même-s auteur-e-s

1 2 3 > >>