Linguistic exclusion in orthopedic research: Cultural adaptation, multilingual innovations, and pathways to global health equity

Abstract

This editorial critically evaluated the recent study by AlMousa et al, which examined the impact of the Arabic version of the American Academy of Orthopedic Surgeons Foot and Ankle Outcomes Questionnaire (AAOS-FAOQ) on postoperative quality of life and recovery in Arabic-speaking patients with traumatic foot and ankle injuries. In the context of systemic linguistic exclusion in orthopedic research—where English-language journals dominated most publications and non-English-speaking populations faced dual barriers of trial underrepresentation and semantic distortions (e.g., mistranslations of terms like "joint instability" in Arabic)—AlMousa et al's work highlighted the transformative potential of culturally adapted methodologies. Their rigorous four-stage adaptation framework validated the Arabic AAOS-FAOQ as a reliable tool, enhancing ecological validity and reducing bias in patient-reported outcomes. However, limitations such as regional specificity (Gulf-centric sampling) and short follow-up periods (4 months) underscored broader challenges in non-English research: Redundant studies, prolonged hospital stays for limited English proficiency patients, and underrepresentation of certain ethnic groups in trials. To dismantle linguistic hegemony, we proposed semantic reconstruction (e.g., integrating culturally specific indicators like "prayer posture"), dialect-aware neural translation, and World Health Organization led terminology standardization. In line with these proposed solutions, AlMousa et al’s study exemplified how language-sensitive adaptations could bridge equity gaps, while future efforts would need to balance cultural specificity with cross-study comparability through AI-driven multilingual databases and policy mandates for cultural adaptation roadmaps.

Key Words: Linguistic exclusion; Orthopedic research; Cultural adaptation; Patient-reported outcomes; Health disparities

Core Tip: The dominance of English in orthopedic research perpetuated systemic linguistic exclusion, marginalized non-English-speaking populations and compromised global health equity. Culturally adapted tools, such as the Arabic version of the American Academy of Orthopedic Surgeons Foot and Ankle Outcomes Questionnaire, combined with artificial intelligence driven dialect recognition and policy reforms, are essential for enhancing inclusivity, mitigating bias, and addressing disparities in evidence-based medicine.

TO THE EDITOR

The hegemony of English in orthopedic research had evolved into a quantifiable systemic linguistic exclusion with global ramifications. Analytical data on academic publishing trends (2010-2016) revealed a widening linguistic power gradient: The proportion of English-language journals surged from 77.1% to 87.3%, with English publications demonstrating statistically superior impact factors compared to non-English counterparts[1,2]. Among the orthopedic journals indexed in Scopus, a substantial proportion are published in English-speaking countries, and nearly all require submissions in English. This practice effectively excludes the clinical insights of approximately 650 million non-English speakers, thereby contributing to what can be termed a "silent evidence chain". Clinical trial design exacerbated exclusion through dual filtration mechanisms: (1) Participation filtering: Patients with limited English proficiency (LEP) are less likely to participate in orthopedic randomized controlled trials[3,4]; and (2) Conceptual filtering: Semantic distortion can occur, for example, direct translations may lead Arabic dialect speakers to misinterpret "joint instability" as "mental weakness"[5], therefore compromising the ecological validity of patient-reported outcomes.

In orthopedic research, the economic and clinical consequences of language exclusion are significant. Language barriers can result in redundant trials, leading to unnecessary resource consumption. Furthermore, patient-reported outcome measures that lack cultural adaptation may introduce systematic biases, compromising the validity of research findings[6]. Notably, LEP is associated with adverse clinical outcomes, including prolonged hospital stays, higher readmission rates, and increased medical costs[7,8]. These disparities extend beyond orthopedics; for instance, Hispanic populations remain underrepresented in vaccine trials, resulting in unmet health needs due to insufficient evidence[9]. A retrospective cohort study examining electronic health records of 2793 gynecological cancer patients revealed that LEP patients were 71% less likely to participate in clinical trials compared to fluent English speakers (participation rate of 2.2% vs 7.5%)[4]. In summary, addressing language barriers is crucial for reducing economic waste and mitigating clinical inequalities in global healthcare systems.

This article aims to elucidate the issue of systematic disruption in the evidence chain within orthopedic research, which can be attributed to the overwhelming predominance of English as the lingua franca in the scientific community. By analyzing the profound impact of language exclusion, it advocates for the establishment of a multilingual evidence-based medicine framework to address the "silent evidence chain" affecting 650 million non-English-speaking patients. This initiative seeks to facilitate the transformation of global orthopedic research towards a paradigm of linguistic equity.

Arabic, the mother tongue of over 420 million people globally, had been historically marginalized in orthopedic research due to the absence of validated assessment tools[9]. This deficiency has limited the participation of Arabic-speaking patients in clinical studies and introduced biases into global health data. AlMousa et al[10] developed an Arabic version of the American Academy of Orthopedic Surgeons Foot and Ankle Outcomes Questionnaire (AAOS-FAOQ) using a rigorous four-stage cross-cultural adaptation framework (forward translation, back translation, expert consensus, and pre-testing), achieving conceptual equivalence. The questionnaire demonstrated strong convergent validity with the Short-Form 36 (SF-36) physical function and pain subscales, and both test-retest reliability and internal consistency met established standards. Their work underscored how language-centered cultural adaptation can enhance research inclusivity and reduce bias, providing a reliable tool for postoperative occupation-oriented rehabilitation[11], breaking down language barriers, and marking a significant milestone in orthopedic equity research.

However, the study sample was confined to the Arabian Gulf region, did not include the minimal clinically important difference[12], and had a short follow-up period (4 months). These limitations may affect the tool's cross-dialect universality and long-term prognosis assessment. Future research should verify regional applicability through multi-center collaboration, integrate responsiveness indicators, and extend the follow-up period to at least 12 months. Additionally, efforts should be made to promote policy support for cross-cultural research to ensure global equity in evidence-based medicine.

To further optimize the Arabic version of AAOS-FAOQ, a two-stage semantic reconstruction approach can be adopted. In the first stage, "shoe comfort" can be expanded into a comprehensive indicator that includes "sandals adaptability" (suitable for the majority of the population in the Gulf region) and "maintaining prayer posture," which is crucial for the functional assessment of Muslim patients. In the second stage, a three-axis dialect matrix (Gulf/Levantine/Maghrebi Arabic) can be employed, combined with neural machine translation to address semantic distortion issues[13,14]. These interventions can enhance test-retest reliability and follow-up compliance. Furthermore, appropriate policy support is essential: Academic journals should mandate the submission of cultural adaptation technology roadmaps (including dialect sensitivity analysis matrices); health departments should implement cultural narrative reconstruction projects using localized patient education videos to enhance treatment compliance; and the World Health Organization should lead the establishment of cross-cultural mapping protocols for orthopedic terms (such as breaking down "range of motion" into culturally specific indicators like "prone and kneeling angles"). These policy interventions can construct a new evidence production paradigm, transforming the binary opposition between cultural validity and scientific rigor into a symbiotic relationship.

While advocating for policy support, the urgent issue of language inequality within the scientific publishing system must be addressed immediately. The scientific publishing industry currently faces a dual challenge: Maintaining the technical efficiency of English as the lingua franca of academia while fulfilling its ethical responsibility to dismantle language barriers. Although English serves as the universal language in the scientific community and facilitates global dissemination and cross-border collaboration—as evidenced by its correlation with higher citation rates and visibility—its dominance systematically marginalizes non-English-speaking researchers and patients. Journals offering multilingual publication options, such as bilingual abstracts or full-text translations, can help mitigate this disparity. However, such initiatives encounter significant practical obstacles, including exponential growth in translation costs (particularly for minority languages), difficulties in recruiting qualified bilingual editors/reviewers, and the risk of fragmenting readership across languages[15,16]. Moreover, monolingual non-English journals risk limited international reach, perpetuating the "silent evidence chain." To address this challenge, the dynamic bilingual publishing model offers a promising solution: By simultaneously releasing both the author's native language version and the standardized English version, it aims to balance knowledge dissemination efficiency with cultural inclusiveness. This approach aligns with United Nations Educational, Scientific and Cultural Organization’s advocacy for multilingualism in science and contributes to safeguarding linguistic diversity. Nonetheless, its feasibility hinges on institutional funding and well-designed policy support.

The core challenge in pursuing linguistic equity in orthopedic research lies in balancing cultural specificity with cross-study comparability. Functional assessment tools for knee arthroplasty, such as the WOMAC or KOOS questionnaires, include daily activity indicators like "climbing stairs" and "using a Western-style toilet." When these tools are directly applied in rural areas of Asia or Africa, significant cultural applicability issues arise, indicating the need for structural reconstruction rather than simple translation. Meanwhile, the predicament of low-resource languages continues to intensify—most medical translation tools do not support Arabic dialects, creating a "language desert" in the field of evidence generation.

Breaking this deadlock requires bold innovation: Developing artificial intelligence capable of recognizing local dialects such as the Berber term "camel gait"; establishing decentralized multilingual experimental databases to facilitate knowledge sharing while safeguarding cultural data sovereignty; and leveraging blockchain technology to facilitate real-time translation and cross-platform verification of clinical trial data in underrepresented languages, thereby mitigating the English-language dominance on platforms such as ClinicalTrials.gov. Undoubtedly, future orthopedic research will belong to the new knowledge production paradigm that can simultaneously handle cultural depth and technological breadth (Table 1).

Table 1 Proposed directions for future research on linguistic equity in orthopedic studies.

Research focus	Research methods	Challenge
Cultural adaptability optimization	Multicenter cross-dialect validation study; Long-term follow-up (≥ 12 months)	Challenges in cross-regional coordination; Resource allocation for longitudinal follow-up
Semantic reconstruction technology	Design of a three-axis dialect matrix for comprehensive linguistic analysis; Advanced optimization in neural machine translation systems	Insufficient dialect corpora resources; High costs of AI training for medical translation
Dynamic bilingual publishing	Blockchain-supported real-time translation verification; bilingual metadata indexing	Translation quality assurance; Fragmentation of the reader group
Technical support for low-resource languages	AI-driven dialect speech recognition; Decentralized terminology database development	Low-resource language training data scarcity; Technical commercialization challenges
Innovative patient engagement mechanisms	Localized educational video development	Cultural sensitivity management; Production cost control
Data sovereignty-sharing equilibrium	Smart contract-governed data access	Techno-ethical governance frameworks; Transjurisdictional legal harmonization