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Background <p>The residency matching process has become increasingly competitive across surgical subspecialties, with "interview hoarding" exacerbating resource inefficiencies and systemic inefficiencies in candidate selection. Traditional reliance on non-standardized metrics—particularly USMLE Step 1 scores, institutional prestige, and geographic connections—has further compounded equity concerns in the matching ecosystem. Preference signaling mechanisms have emerged as a standardized solution to enhance both matching efficiency and fairness, though current evidence remains limited by single-specialty studies and insufficient examination of long-term match outcomes.</p> Methods <p>Studies on the preference signaling mechanism in surgical subspecialties published after 2020 were retrieved from PubMed, Embase, and CENTRAL databases. Eleven high-quality retrospective cohort studies involving 10,448 applicants were included. Meta-analysis was performed to compare interview and match rates between signal and non-signal groups, with subgroup analyses assessing the impacts of specialty, data source, and other factors.</p> Results <p>Totally, eleven studies with 10,488 patients were included for meta-analyses. The interview rate in the signal group was 9.30 times higher than that in the non-signal group (95% CI 7.72–10.89), though substantial heterogeneity was observed across specialties (<i>I</i><sup>2</sup> = 96.5%). Orthopedics demonstrated the strongest signaling effect (OR = 18.05), while general surgery showed the weakest (OR = 4.53). Studies based on program directors’ data revealed a larger effect size (OR = 34.74). Pooled analysis of four studies showed the match rate in the signal group was 6.76 times higher than that in the non-signal group (95% CI 2.88–10.65), with moderate heterogeneity (<i>I</i><sup>2</sup> = 65%).</p> Conclusions <p>This meta-analysis confirms that the preference signaling mechanism significantly enhances interview rates and match rates in resident matching, demonstrating dual value in optimizing efficiency and promoting equity across surgical specialties. By providing cross-specialty evidence for system optimization, this study advances the preference signaling system toward greater efficiency and fairness in the residency matching process.</p>

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The impact of preference signaling on interview and match rate for surgical match in resident education: a meta-analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月24日

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  • Ying Xu,
  • Yan Lin,
  • Mingyue Wang,
  • Changjun Wang,
  • Qiang Sun,
  • Yidong Zhou

摘要

Background

The residency matching process has become increasingly competitive across surgical subspecialties, with "interview hoarding" exacerbating resource inefficiencies and systemic inefficiencies in candidate selection. Traditional reliance on non-standardized metrics—particularly USMLE Step 1 scores, institutional prestige, and geographic connections—has further compounded equity concerns in the matching ecosystem. Preference signaling mechanisms have emerged as a standardized solution to enhance both matching efficiency and fairness, though current evidence remains limited by single-specialty studies and insufficient examination of long-term match outcomes.

Methods

Studies on the preference signaling mechanism in surgical subspecialties published after 2020 were retrieved from PubMed, Embase, and CENTRAL databases. Eleven high-quality retrospective cohort studies involving 10,448 applicants were included. Meta-analysis was performed to compare interview and match rates between signal and non-signal groups, with subgroup analyses assessing the impacts of specialty, data source, and other factors.

Results

Totally, eleven studies with 10,488 patients were included for meta-analyses. The interview rate in the signal group was 9.30 times higher than that in the non-signal group (95% CI 7.72–10.89), though substantial heterogeneity was observed across specialties (I2 = 96.5%). Orthopedics demonstrated the strongest signaling effect (OR = 18.05), while general surgery showed the weakest (OR = 4.53). Studies based on program directors’ data revealed a larger effect size (OR = 34.74). Pooled analysis of four studies showed the match rate in the signal group was 6.76 times higher than that in the non-signal group (95% CI 2.88–10.65), with moderate heterogeneity (I2 = 65%).

Conclusions

This meta-analysis confirms that the preference signaling mechanism significantly enhances interview rates and match rates in resident matching, demonstrating dual value in optimizing efficiency and promoting equity across surgical specialties. By providing cross-specialty evidence for system optimization, this study advances the preference signaling system toward greater efficiency and fairness in the residency matching process.