Published on in Vol 2, No 1 (2017): Jan-Jun

Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material

Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material

Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material

Authors of this article:

Xuewei Chen1 Author Orcid Image ;   Sandra Acosta2 Author Orcid Image ;   Adam E Barry3 Author Orcid Image

Journals

  1. Tatara N, Hammer H, Mirkovic J, Kjøllesdal M, Andreassen H. Associations Between Immigration-Related User Factors and eHealth Activities for Self-Care: Case of First-Generation Immigrants From Pakistan in the Oslo Area, Norway. JMIR Public Health and Surveillance 2019;5(3):e11998 View
  2. Vieira L, O’Hagan M, O’Sullivan C. Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases. Information, Communication & Society 2021;24(11):1515 View
  3. Turner A, Choi Y, Dew K, Tsai M, Bosold A, Wu S, Smith D, Meischke H. Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study. JMIR Public Health and Surveillance 2019;5(1):e11171 View
  4. Chen X, Goodson P, Acosta S, Barry A, McKyer L. Assessing Health Literacy Among Chinese Speakers in the U.S. with Limited English Proficiency. HLRP: Health Literacy Research and Practice 2018;2(2) View
  5. Thonon F, Fahmi S, Rousset-Torrente O, Bessonneau P, Griffith J, Brown C, Chassany O, Duracinsky M. Promoting HIV, Hepatitis B Virus, and Hepatitis C Virus Screening Among Migrants With a Language Barrier: Protocol for the Development and Evaluation of an Electronic App (Apidé). JMIR Research Protocols 2021;10(5):e22239 View
  6. Ji X, Chow E, Abdelhamid K, Naumova D, Mate K, Bergeron A, Lebouché B. Utility of mobile technology in medical interpretation: A literature review of current practices. Patient Education and Counseling 2021;104(9):2137 View
  7. Shlobin N, Punchak M, Boyke A, Beestrum M, Gutzman K, Rosseau G. Language and Geographic Representation of Neurosurgical Journals: A Meta-Science Study. World Neurosurgery 2022;166:171 View
  8. Alotaibi H, Salamah D. The impact of translation apps on translation students’ performance. Education and Information Technologies 2023;28(8):10709 View
  9. Lamont-Mills A, Bayliss L, Christensen S, Arias S. Online suicidal thoughts and/or behaviours talk: A scoping review protocol. PLOS ONE 2022;17(10):e0276776 View
  10. Olani A, Olani A, Muleta T, Rikitu D, Disassa K. Impacts of language barriers on healthcare access and quality among Afaan Oromoo-speaking patients in Addis Ababa, Ethiopia. BMC Health Services Research 2023;23(1) View
  11. Herrmann-Werner A, Loda T, Zipfel S, Holderried M, Holderried F, Erschens R. Evaluation of a Language Translation App in an Undergraduate Medical Communication Course: Proof-of-Concept and Usability Study. JMIR mHealth and uHealth 2021;9(12):e31559 View
  12. Kasperė R, Horbačauskienė J, Motiejūnienė J, Liubinienė V, Patašienė I, Patašius M. Towards Sustainable Use of Machine Translation: Usability and Perceived Quality from the End-User Perspective. Sustainability 2021;13(23):13430 View
  13. Zappatore M, Ruggieri G. Adopting machine translation in the healthcare sector: A methodological multi-criteria review. Computer Speech & Language 2024;84:101582 View
  14. Hudelson P, Chappuis F. Using Voice-to-Voice Machine Translation to Overcome Language Barriers in Clinical Communication: An Exploratory Study. Journal of General Internal Medicine 2024;39(7):1095 View
  15. Krenn C, Semlitsch T, Zipp C, Lengauer S, Shao L, Schreck T, Bedek M, Kupfer C, Albert D, Kubicek B, Siebenhofer A, Jeitler K. Customization options in consumer health information materials on type-2 diabetes mellitus—an analysis of modifiable features in different types of media. Frontiers in Public Health 2024;12 View
  16. Kido H, Saeki S, Hiraiwa M, Yasunaga M, Tomizawa R, Honda C, Fukuoka T, Minamitani K. Plain language in the healthcare of Japan: a systematic review of “plain Japanese”. Global Health Journal 2024;8(3):113 View
  17. Lee N, Lee K. Travelers’ viewpoints on machine translation using Q methodology: a perspective of consumption value theory. Information Technology & Tourism 2024;26(4):611 View
  18. Ugas M, Calamia M, Tan J, Umakanthan B, Hill C, Tse K, Cashell A, Muraj Z, Giuliani M, Papadakos J. Evaluating the feasibility and utility of machine translation for patient education materials written in plain language to increase accessibility for populations with limited english proficiency. Patient Education and Counseling 2025;131:108560 View