They noted that machine translation tools made errors when translating medical information. With regard to the machine translation accuracy, previous studies assessed the translation product provided by Babel Fish and Google Translate websites using only writing inputs. Here, machine translation refers to automated computer translations powered by algorithms.īesides usability, accuracy is another important criterion for evaluating machine language translation tools. The authors found that the participants perceived the xprompt app as useful for basic communication with non-German speaking patients. Similarly, Albrecht et al examined the usage experience of a mobile translation app (xprompt) among nursing staff in Germany. Based on their findings, the authors concluded that the Google Translation App might be a viable tool for addressing language barriers and improving health communication when human interpreters were not available. Abreu and Adriatico reported positive reactions from both the audiologists and the Spanish-speaking clients. In a study conducted by Abreu and Adriatico, the researchers investigated the experience of using the Google Translation App among a group of US audiologists and Spanish speaking patients/parents/guardians when they were communicating with each other. Previous studies have examined the usability of mobile language translation apps among clinicians and patients. For example, language translation errors lead to misunderstandings about medical prescriptions as well as misdiagnoses and mistreatments. However, translation inaccuracy has the potential to adversely impact information’s meaning and lead to negative health consequences. For instance, translation mobile apps might improve their understanding of health information and access to health resources. Smartphones with machine translation apps are efficient tools for helping populations with LEP overcome language barriers. Further, about three-quarters (73%) of the Hispanic smartphone owners have used their phones to search for health-related information, compared to 58% white and 67% black. There are no significant differences in smartphone ownership among different racial/ethnic groups. Such voice recognition features were developed from computerized systems. For instance, iTranslate is a mobile app available for mobile phones with Apple, Android, and Windows systems that instantly translates text or voice inputs and converts them into text and voice outputs. These smartphone owners can access various apps including machine language translation apps. In the United States, smartphone ownership increased from 35% of the population in 2011 to 72% in 2016. One potential tool for facilitating language communication between patients and health care providers is technology, specifically mobile phones. For diabetes patients who have LEP, negative health outcomes include poor glycemic control and diabetic retinopathy. For instance, individuals with LEP are more likely to take inaccurate medication dosages, have poor health status, spend additional money and time utilizing health care services, experience unsatisfactory events with health care providers, make improper health choices, and have limited access and use of preventive health care services. These language barriers, as many studies have pointed out, might lead to health disparities and poor health outcomes. Populations with LEP encounter numerous health communication challenges due to barriers related to language proficiency. In brief, because Hispanic and Chinese Americans are more likely to have LEP, communication challenges arising from language barriers might impact the quality of the health services and information they receive. ![]() LEP refers to any person age 5 or older who self-reported speaking English less than “very well”. Approximately 43.7% Hispanics and 55.7% Chinese Americans speak English less than “very well” and would be considered having limited English proficiency (LEP). Further, the highest percentages of individuals who speak no English are Hispanics and Chinese Americans. Over 21% of the US population speaks a language other than English at home. Ĭompared to other ethnic groups, Hispanics and Chinese Americans are also more likely to have low English proficiency. From 1997-2014, diabetes rates increased 103% for Asian Americans and 60% for Hispanics. ![]() According to the Centers for Disease Control and Prevention (CDC), 29.1 million people (9.3% of the US population) have diabetes 12.8% Hispanics and 9% Asian Americans above 20 years old were diagnosed with diabetes, compared to 7.6% non-Hispanic whites. Diabetes is a major health crisis for Hispanics and Asian Americans.
0 Comments
Leave a Reply. |