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Comparing 2 Approaches for the File Review of Residency Applications
- Source :
- J Grad Med Educ
- Publication Year :
- 2021
- Publisher :
- Journal of Graduate Medical Education, 2021.
-
Abstract
- Background The residency selection process relies on subjective information in applications, as well as subjective assessment of applications by reviewers. This inherent subjectivity makes residency selection prone to poor reliability between those reviewing files. Objectives We compared the interrater reliability of 2 assessment tools during file review: one rating applicant traits (ie, leadership, communication) and the other using a global rating of application elements (ie, curriculum vitae, reference letters). Methods Ten file reviewers were randomized into 2 groups, and each scored 7 general surgery applications from the 2019–2020 cycle. The first group used an element-based (EB) scoring tool, while the second group used a trait-based (TB) scoring tool. Feedback was collected, discrimination capacities were measured using variation in scores, and interrater reliability (IRR) was calculated using intraclass correlation (ICC) in a 2-way random effects model. Results Both tools identified the same top-ranked and bottom-ranked applicants; however, discrepancies were noted for middle-ranked applicants. The score range for the 5 middle-ranked applicants was greater with the TB tool (6.43 vs 3.80), which also demonstrated fewer tie scores. The IRR for TB scoring was superior to EB scoring (ICC [2, 5] = 0.82 vs 0.55). The TB tool required only 2 raters to achieve an ICC ≥ 0.70. Conclusions Using a TB file review strategy can facilitate file review with improved reliability compared to EB, and a greater spread of candidate scores. TB file review potentially offers programs a feasible way to optimize and reflect their institution's core values in the process.
- Subjects :
- medicine.medical_specialty
020205 medical informatics
Intraclass correlation
MEDLINE
Internship and Residency
Reproducibility of Results
02 engineering and technology
General Medicine
Random effects model
Global Rating
03 medical and health sciences
Inter-rater reliability
0302 clinical medicine
0202 electrical engineering, electronic engineering, information engineering
medicine
Humans
Medical physics
030212 general & internal medicine
Psychology
Reliability (statistics)
Original Research
Subjects
Details
- ISSN :
- 19498357 and 19498349
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- Journal of Graduate Medical Education
- Accession number :
- edsair.doi.dedup.....27f026aada951ac08be3f56a7d18e090
- Full Text :
- https://doi.org/10.4300/jgme-d-20-00619.1