Aug 2026· Theory and Practice in Language Studies· Vol 16, pp. 2569-2581· 0 citations
TL;DR
A systematic literature review methodology guided by the PRISMA framework suggests that AI-based tools, when used alongside human-led translation workflows, may help expand access to high-quality medical translations for Arabic-speaking populations.
Abstract
Translating medical texts from English to Arabic is challenged by terminological inconsistency, register variation, and uneven methodological practices, with direct implications for patient safety and medical education in Arabic-speaking countries. This study adopted a systematic literature review methodology guided by the PRISMA framework. Five major databases—Scopus, ERIC, SpringerLink Nature, Nature, and BMC—were searched to identify relevant studies published between 2015 and 2025. A total of 22 studies were included and analysed to map publication trends, translation procedures, the use of digital technologies, and implications for medical education. The findings show that most research has focused on instrument development, with particular attention to patient safety and the translation of clinical instruments and leaflets. The analysis further reveals that only a very limited number of studies have examined the use of technology and artificial intelligence in this field. The review suggests that AI-based tools, when used alongside human-led translation workflows, may help expand access to high-quality medical translations for Arabic-speaking populations.
English-medium instruction (EMI) dominates Jordanian medical education, yet its equity implications and consequences for assessment validity remain poorly evidenced, particularly after the disruptions of the COVID-19 pandemic. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, this review searched Scopus, Web of Science, ERIC, and PubMed for peer-reviewed work published between 2000 and 2024. A total of 34 studies met inclusion criteria after mixed methods appraisal tool (MMAT) quality appraisal and were analyzed through thematic synthesis. The evidence reveals a structural paradox: EMI supports international academic integration while disadvantaging students from Arabic-medium secondary schools by conflating English proficiency with medical competence. The lexical and morphological complexity of medical English increases cognitive demands and became more pronounced during pandemic-related online teaching. Students rely on code-switching and morphological analysis as coping strategies, but neither is recognized in policy or assessment. The review delivers the first PRISMA-aligned synthesis of EMI in Jordanian medical education, proposes the Jordanian Medical English Corpus (JoMEC) as a corpus-based diagnostic for measuring lexical burden, and reframes EMI equity as a measurable issue of assessment validity rather than a normative concern alone. Findings support bilingual scaffolding and validity-oriented assessment reform to advance equity in medical education across Jordan and comparable Middle East and North Africa (MENA) contexts.
Hassan Mohammad Bani-Issa, Norsofiah Abu Bakar, M. Daud et al.· International Journal of Eva...· 0 citations
Website localization from English to Arabic entails linguistic, cultural, technical, and physical considerations. This current study aims to examine only the translation errors considerations when localizing English medical websites into Arabic. This study makes the argument that, in order to achieve a consistent and appropriate translation of medical words into Arabic, medical localization calls for a multidisciplinary approach comprising linguists, medical experts, and software engineers. Additionally, it emphasizes how crucial it is to grasp the linguistic aspects of the target language in order to properly comprehend medical terminology. The research emphasizes the importance of careful preparation, coordination, and stakeholder collaboration to successfully localize medical websites from English to Arabic. Examining the linguistic aspects proposed by Olvera Lobo & Castillo-Rodríguez (2019) will be the focus of the methods section of this study. This study finds many translation issues in all of the examined websites when localizing the preface pages from English into Arabic.
Mohannad Sayaheen· Journal of humanities and so...· 0 citations
A review of journal articles published between 2020 and 2024 that discuss the design, effectiveness, perception, and lexicographical quality of Arabic digital dictionaries identifies research gaps regarding the integration of artificial intelligence and deeper linguistic features into Arabic digital dictionaries.
Nadela Yusrizal, Asep Sopian, Mia Nurmala· 0 citations
The integration of machine translation (MT) and artificial intelligence into translation workflows has significantly transformed professional practice, particularly in high-stakes domains such as medical translation. This study investigates professional translators’ perspectives on post-editing (PE) and translation quality assessment (TQA) in English–Romanian medical translation. Drawing on structured interviews and thematic analysis, the findings indicate that MT is primarily used as a support tool due to persistent issues related to terminology and contextual accuracy. Post-editing is considered essential, though often applied without structured adherence to standards such as ISO 18587, while TQA models are unevenly implemented in practice. The study also identifies a significant gap between academic training and professional requirements, particularly regarding technological and domain-specific competences. These findings highlight the need for a more integrated and practice-oriented approach to translator training in the Romanian context.
Z. Kovács, Daniel Dejica· Scientific Bulletin of the P...· 0 citations
Medical terminology in the “Arab 111” curriculum varies in its use within the educational context, which may affect students’ comprehension and understanding. Therefore, this study seeks to examine the suitability of these terms from a pragmatic perspective and their relationship to the effectiveness of scientific communication. Medical terminology possesses multiple contextual dimensions and is not confined solely to the scientific context among physicians, patients, and society. Pragmatics thus focuses on the way these terms are employed in everyday communication, since their circulation requires simplification to suit non-specialists. Moreover, misunderstanding medical terminology may lead to errors in diagnosis or treatment, making it essential to achieve a balance between scientific accuracy and ease of understanding in order to improve medical communication. The study reveals that the difference does not lie in the term itself, but rather in its pragmatic function within discourse. Some terms are used metaphorically or in an extended sense beyond their original medical practices, which normally provide them with semantic stability. Therefore, it is important to train students in strategies for presenting medical terminology through effective communication, while also teaching the distinction between technical medical terminology and simplified language directed to patients. The pragmatics of medical terminology contributes to preparing a generation that is more aware and capable of dealing with medical concepts in both academic and practical life. It is also necessary to relate medical terminology to realistic life examples that enhance learners’ comprehension, retention, and understanding.
Nuwair Abdullah Khalaf Al-Anzi· UB Journal for Humanities· 0 citations
This review focuses on how artificial intelligence has been used to support English medical writing among non-native English speakers. The purpose was not to list every available tool, but to identify what the existing literature shows about their uses, benefits, limitations, and risks. Searches were conducted in Google Scholar, Scopus, and PubMed with terms related to artificial intelligence, medical or healthcare writing, and non-native English users. The search first produced 978 records. After duplicate removal, title and abstract screening, and full-text assessment, 24 sources were included in the review. These sources mainly discussed four forms of AI support: grammar and style checking, terminology and lexical assistance, summarisation or simplification, and large language model-based drafting or revision. Across the reviewed literature, AI tools were most often linked to grammar correction, vocabulary choice, readability, writer confidence, and the simplification of medical information for non-specialist readers. These benefits were useful but mostly short-term. Many studies used small samples, brief periods of tool use, or outcome measures that could not show whether learners became better independent writers. It is safer to view AI as a writing support tool rather than a replacement for teachers, supervisors, or writing instruction. Its use in English medical writing education should be guided by clear rules, disclosure of AI assistance, and careful checking factual accuracy in medical text.
W. Shen, Afendi Hamat, Anis Nadiah Che Abdul Rahman et al.· Arab World English Journal· 0 citations
