Postgraduate-Year-1 Residents’ Perceptions of Social Media and Virtual Applicant Recruitment: Cross-sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: The dissemination of information about residency programs is a vital step in residency recruitment. Traditional methods of distributing information have been printed brochures, websites, in-person interviews, and increasingly, social media. Away rotations and in-person interviews were cancelled, and interviews were virtual for the first time during the COVID-19 pandemic. OBJECTIVE: The purpose of our study was to describe postgraduate-year-1 (PGY1) residents' social media habits in regard to residency recruitment and their perceptions of the residency programs' social media accounts in light of the transition to virtual interviews. METHODS: A web-based 33-question survey was developed to evaluate personal social media use, perceptions of social media use by residency programs, and perceptions of the residency program content. Surveys were sent in 2021 to PGY1 residents at Mayo Clinic in Arizona, Florida, and Minnesota who participated in the 2020-2021 interview cycle. RESULTS: Of the 31 program directors contacted, 22 (71%) provided permission for their residents to complete the survey. Of 219 residents who received the survey, 67 (30%) completed the survey. Most respondents applied to a single specialty, and greater than 61% (41/67) of respondents applied to more than 30 programs. The social media platforms used most regularly by the respondents were Instagram (42/67, 63%), Facebook (36/67, 54%), and Twitter (22/67, 33%). Respondents used the program website (66/67, 99%), residents (47/67, 70%), and social media (43/67, 64%) as the most frequent resources to research programs. The most commonly used social media platforms to research programs were Instagram (38/66, 58%), Twitter (22/66, 33%), and Doximity (20/66, 30%). The type of social media post ranked as most interesting by the respondents was "resident life outside of the hospital." In addition, 68% (39/57) of the respondents agreed or strongly agreed that their perception of a program was positively influenced by the residency program's social media account. CONCLUSIONS: In this multispecialty survey of PGY1 residents participating in the 2020-2021 virtual interview season, respondents preferred Instagram to Twitter or Facebook for gathering information on prospective residency programs. In addition, the program website, current residents, and social media platforms were the top-ranked resources used by prospective applicants. Having an up-to-date website and robust social media presence, particularly on Instagram, may become increasingly important in the virtual interview environment.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".