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Record W4413164203 · doi:10.3390/healthcare13161987

Addressing the Leadership Gap: A Systematic Review of Asian American Underrepresentation in Orthopaedic Surgery

2025· review· en· W4413164203 on OpenAlexaboutno aff
Ahmed Nadeem-Tariq, Matthew Michelberger, Christopher J. Fang, Jeffrey Lucas Hii, Sukanta Maitra, Brock Wentz

Bibliographic record

VenueHealthcare · 2025
Typereview
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsSubspecialtyMedicineHealth equityDiversity (politics)Gender disparityLeadership developmentAsian americansMedical educationMentorshipPsychologyFamily medicinePolitical scienceEthnic groupPublic relationsNursingPublic healthDemographySociology

Abstract

fetched live from OpenAlex

Background: While Asian American individuals are well represented in medical schools in the United States, their advancement to senior positions within the field of orthopaedic surgery is disproportionately low. This underrepresentation not only limits diversity in leadership but also constrains the development of people-centred systems that reflect the needs of an increasingly diverse patient population. Objectives: This study systematically examines Asian American representation across the orthopaedic surgery professional pipeline, focusing on disparities between training-level representation and advancement into both faculty and leadership positions., and framing these gaps as a health equity concern. Methods: A comprehensive literature search for peer-reviewed original research articles was conducted via PubMed, EBSCO Open Research, Wiley Online Library, Google Scholar, and ScienceDirect. The potential articles were screened against prespecified eligibility criteria, and risk of bias was assessed using the Newcastle–Ottawa Scale (NOS). Data were then systematically extracted and analysed. Results: This analysis included 20 research articles investigating Asian American representation in orthopaedic surgery. The results demonstrated an underrepresentation of Asian Americans in orthopaedic leadership positions despite improvements in training programme representation with subspecialty clustering in adult reconstruction and spine. Asian American surgeons were less likely to occupy academic and leadership roles than their non-Asian American peers. Across studies, underrepresentation was consistently observed, with effect size estimates indicating a substantial disparity (e.g., pooled risk difference = 0.19; 95% CI [0.12, 0.28]) in those studies reporting comparative outcomes. Similarly, while Asian Americans in residency programmes increased, this growth did not translate proportionally to faculty advancement. In contrast, Asian women face compounded barriers, particularly in subspecialties like spine surgery. These inequities undermine workforce inclusivity and may reduce cultural and linguistic concordance with patients. Conclusions: Despite having strong representation in orthopaedic training programmes, Asian Americans are disproportionately absent from leadership positions. This poses a challenge to equity in surgical education and patient-centred care. To promote equity in leadership, focused mentorship, clear promotion processes, and institutional reform are necessary to address structural barriers to career advancement, this will reflect the diversity of both the workforce and populations served.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.108
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0190.020
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.604
GPT teacher head0.511
Teacher spread0.093 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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