ArticlePediatric pulmonology2026
Bridging the Gap: Translated Medical Education to Support Cystic Fibrosis Centers From Non-English Speaking Countries.
Article in Pediatric pulmonology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Bridging the Gap: Translated Medical Education to Support Cystic Fibrosis Centers From Non-English Speaking Countries.Pediatric pulmonology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
backgroundThe 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.
methodsAn 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.
resultsEducation 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.
conclusionThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.