ArticleBMC medical education2025
Factors influencing United States residency interview rates among African international medical graduates.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Impact of current U.S. visa policies on Nigerian medical students and physicians seeking graduate medical education.BMC medical education · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSecuring a residency position in the United States remains a significant challenge for International Medical Graduates (IMGs), particularly those from African countries. Although African IMGs contribute to approximately 25% of the U.S. physician workforce, they face unique barriers such as limited access to U.S. clinical experience, visa restrictions, and perceptions of lower-quality medical education. To enhance applicant visibility and improve equity in the selection process, the Association of American Medical Colleges (AAMC), through the Electronic Residency Application Service (ERAS), introduced program signaling and geographic preferencing. This study evaluates the impact of these mechanisms on interview outcomes for African IMGs during the 2023–2024 and 2024–2025 residency application cycles.
methodsA descriptive cross-sectional study was conducted among African IMGs who participated in the 2023–2024 and 2024–2025 NRMP Match. Logistic regression analysis was used to examine the association between applicant characteristics and the likelihood of receiving an above-average number of residency interviews.
resultsA total of 222 respondents participated, with most from Nigeria (77.7%), followed by Ghana, Cameroon, and other countries. The most preferred regions were Middle Atlantic (44.6%), East North Central (35.9%), and South Atlantic (29.2%). Applicants signaled an average of 12.5 programs and received 5.1 interview invitations on average. Of these, 2.9 interviews came from programs in preferred regions. On average, 2.1 interviews came from signaled programs within preferred regions, while 1.3 were from signaled programs outside those regions. Factors influencing program signaling included historical acceptance of African IMGs (73.9%), geographic preference (48.2%), and networking (38.7%). Higher interview rates were associated with recent graduation (≤ 5 years), no USMLE step failures, and Step 2 CK scores ≥ 249.
conclusionProgram signaling and geographic preferencing allowed applicants to express interest more directly but did not independently improve interview outcomes. Enhancing match success for African IMGs will require targeted strategies, including greater access to U.S. clinical experiences and strengthened USMLE preparation support.
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.