Orthopedic Surgery Residency Program Website Content and Accessibility During the COVID-19 Pandemic: Observational Study
Bibliographic record
Abstract
BACKGROUND: The exceptional competitiveness of the orthopedic surgery specialty, combined with the unclear impact of the COVID-19 pandemic on residency recruitment, has presented significant challenges to applicants and residency program directors. With limited in-person opportunities in the 2020-2021 application cycle, applicants have been pressed to gauge chances and best fit by browsing program websites. OBJECTIVE: The aim of the study was to assess the accessibility and content of accredited orthopedic surgery residency program websites during the COVID-19 pandemic. METHODS: Using the online database of the Electronic Residency Application Service (ERAS), we compiled a list of accredited orthopedic surgery residency programs in the United States. Program websites were evaluated across four domains: program overview, education, research opportunities, and application details. Each website was assessed twice in July 2020, during a period of adjustment to the COVID-19 pandemic, and twice in November 2020, following the October ERAS application deadline. RESULTS: A total of 189 accredited orthopedic surgery residency programs were identified through ERAS. Of these programs, 3 (1.6%) did not have functional website links on ERAS. Data analysis of content in each domain revealed that most websites included program details, a description of the didactic curriculum, and sample rotation schedules. Between the two evaluation periods in July and November 2020, the percentage of program websites containing informative videos and virtual tours rose from 12.2% (23/189) to 48.1% (91/189; P<.001) and from 0.5% (1/189) to 13.2% (25/189; P<.001), respectively. However, the number of programs that included information about a virtual subinternship or virtual interview on their websites did not change. Over the 4-month period, larger residency programs with 5 or more residents were significantly more likely to add a program video (P<.001) or virtual tour (P<.001) to their websites. CONCLUSIONS: Most residency program websites offered program details and an overview of educational and research opportunities; however, few addressed the virtual transition of interviews and subinternships during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".