Bridging the Gap: Translated Medical Education to Support Cystic Fibrosis Centers From Non‐English Speaking Countries
BACKGROUND: The European Cystic Fibrosis Society (ECFS) develops education resources to support members; however, these are almost exclusively in English. Many barriers to translation exist, including cost and time. Artificial intelligence (AI) provides an opportunity to support translation and address such barriers. This study aimed to pilot the use of AI-generated translation of ECFS e-learning modules and evaluate the quality. METHODS: An AI translation program was used to create subtitles of ECFS peer-reviewed education modules. Two independent native language speakers with extensive cystic fibrosis (CF) healthcare experience were identified and tasked with reviewing, editing, and validating. This was followed by the development and circulation of an online evaluation survey assessing users' views on quality. RESULTS: Education packages, each consisting of six subtitled modules, were created in three languages: Ukrainian, Romanian, and Turkish. For each language, corrections to the AI-generated translation by the independent native speakers were essential. Evaluation was conducted in two countries. Eighteen completed surveys were received. Results indicated high levels of accuracy for the final modules, and feedback was very positive regarding the utility and range of topics. CONCLUSION: The use of novel AI-generated translation shows promise and proved quick and affordable. However, quality of translation was variable, highlighting the critical role of collaborating with native-speaking CF experts to ensure linguistic accuracy. This project highlights the importance of interdisciplinary collaborative efforts between ECFS Education, the Twinning Project, CF Europe, and patient organizations. Further, it demonstrates both the feasibility and practicality of generating effective multilingual educational modules using AI.
Authors
- Katarina Stepankova
- Yasemi̇n Gökdemi̇r (ORCID: https://orcid.org/0000-0002-0853-7932)
- Halyna Makukh (ORCID: https://orcid.org/0000-0001-7749-5353)
- Hilde De Keyser
- Chris Smith (ORCID: https://orcid.org/0009-0003-8948-4741)
- H. Chadwick (ORCID: https://orcid.org/0000-0002-8022-5490)
- M. Krasnyk
- K. Hill (ORCID: https://orcid.org/0000-0001-5561-8893)
- Fulya Özdemi̇rci̇oğlu (ORCID: https://orcid.org/0000-0002-2570-1837)
- Csilla-Eniko Szabo
- Ilknur Gorgun
- Claire Francis
- Pavel Drevinek
- Oana Voivod
- Daniel G. Peckham
Institutions
- Brighton and Sussex Medical School (GB)
- Queen's University Belfast (GB)
- University of Leeds (GB)
- Lviv University (UA)
- Iuliu Hațieganu University of Medicine and Pharmacy (RO)
- Charles University (CZ)
- Leeds Teaching Hospitals NHS Trust (GB)
- Clinical Emergency Hospital Bucharest (RO)
- Cystic Fibrosis Trust (GB)
- Royal Alexandra Children's Hospital (GB)
- Turkish Society of Hematology (TR)
- University Hospital in Motol (CZ)
- Emmanuel Cancer Foundation (US)
- Together (US)
- Slovak Public Health Association (SK)
- Office of Patient Care Services (US)
- Marmara University (TR)
Publication Details
- Journal
- Pediatric Pulmonology
- Published
- 2026-07-30
- DOI
- https://doi.org/10.1002/ppul.71764
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00