ArticleCureus2023
Over-Application and Interviewing in the 2021 United States Primary Care Virtual Recruitment Season.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The Relative Influence of Program Signaling, Geographic Preferences, and In-State Status in Determining Odds of Interview Invitation in Residency Selection.Journal of graduate medical education · 2025Article
- Practical Tips for Undergraduate Medical Education Advisors in Residency Application Signaling.Journal of medical education and curricular developmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance Over-application and interviewing are believed to be widespread in residency recruitment. These may have increased during the 2021 virtual recruitment season. The increase does not correspond to an increase in available residency positions and likely results in more interviews with low probabilities of yielding matches. Prior work demonstrates that such marginal interviews are identifiable ‑ from key explanatory factors like same-state for interviewee and program ‑ in sufficient volume to allow programs to substantially decrease interviews. Objective To evaluate the importance of same-state relationships in primary care and to determine the extent of over-interviewing in the 2021 virtual recruitment season. Design The National Resident Matching Program and Thalamus merged match (outcomes) and interview (explanatory variables) data from primary care specialties (family medicine, internal medicine, pediatrics). Data were analyzed by logistic regression, trained on the 2017-2020 seasons, and projected on the 2021 season for testing. Setting The setting was the 2017-2021 main residency matches. Participants This comprised 4,442 interviewees applying to 167 residency programs in primary care. Intervention This included the transition to virtual recruitment from in-person recruitment in the 2021 residency recruitment season. Measurements A total of 20,415 interviews and 20,791 preferred programs with program and interviewee characteristics and match outcomes were included. Results Same-state geographic relations predicted match probability in primary care residency interviews better than medical school/residency affiliation, with 86.0% of interviewees matching consistently with their preferences for the same state. Same-state was more effective than medical school affiliations with programs in predicting matching. Eliminating interviews with less than a 5% probability of matching (upper 95% prediction limit) removed 31.5% of interviews. Conclusions and relevance The large number of low-match probability interviews demonstrates over-interviewing in primary care. We suggest that programs eliminate interview offers to applications falling below their chosen match probability threshold.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.