Exploring the Role of Machine Translation in Improving Health Information Access for Linguistically Diverse Populations

Abstract

Linguistic diversity poses significant challenges to accessing healthcare information, leading to health disparities among different population groups. This research examines the role of machine translation in improving health information access for linguistically diverse populations. By breaking down language barriers, machine translation systems enable individuals to access vital health-related content in their preferred language. Moreover, machine translation facilitates effective communication between patients and healthcare professionals who speak different languages, enhancing diagnosis, treatment, and overall care. In the context of remote telemedicine and telehealth services, machine translation ensures equitable access to healthcare, especially for languages with limited interpreter resources. Additionally, machine translation plays a crucial role in disseminating health education and awareness materials, empowering individuals to make informed decisions about their health. It promotes health equity by democratizing access to information, ultimately contributing to reducing health disparities. However, it is important to acknowledge the limitations of machine translation, such as its challenges in handling complex medical terminology and cultural nuances. Therefore, machine translation should be used as a complement to human translation and interpretation services. This research highlights the potential of machine translation as a valuable tool in improving health information access for linguistically diverse populations, emphasizing the need for continued research and development in this area to ensure optimal healthcare outcomes for all.