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Mixing languages within a sentence or a conversation is a common practice among many speakers of multiple languages. Language mixing found in multilingual speakers with aphasia has been suggested to reflect deficits associated with the brain lesion. In this paper, we examine language mixing behaviour in multilingual people with aphasia to test the hypothesis that the use of language mixing reflects a communicative strategy. We analysed connected language production elicited from 11 individuals with aphasia. Words produced were coded as mixed or not. Frequencies of mixing were tabulated for each individual in each of her or his languages in each of two elicitation tasks (Picture sequence description, Narrative production). We tested the predictions that there would be more word mixing: for participants with greater aphasia severity; while speaking in a language of lower post-stroke proficiency; during a task that requires more restricted word retrieval; for people with non-fluent aphasia, while attempting to produce function words (compared to content words); and that there would be little use of a language not known to the interlocutors. The results supported three of the five predictions. We interpret our data to suggest that multilingual speakers with aphasia mix words in connected language production primarily to bypass instances of word-retrieval difficulties, and typically avoid pragmatically inappropriate language mixing.
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http://dx.doi.org/10.1080/02699206.2019.1584646 | DOI Listing |
J Imaging Inform Med
September 2025
Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Large language models (LLMs) have been successfully used for data extraction from free-text radiology reports. Most current studies were conducted with LLMs accessed via an application programming interface (API). We evaluated the feasibility of using open-source LLMs, deployed on limited local hardware resources for data extraction from free-text mammography reports, using a common data element (CDE)-based structure.
View Article and Find Full Text PDFJ Pediatr Surg
September 2025
Harvard Medical School, Boston, MA, United States; Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center, Mass General Brigham, Boston, MA, United States. Electronic address:
Introduction: Large language models (LLMs) have been shown to translate information from highly specific domains into lay-digestible terms. Pediatric surgery remains an area in which it is difficult to communicate clinical information in an age-appropriate manner, given the vast diversity in language comprehension levels across patient populations and the complexity of procedures performed. This study evaluates LLMs as tools for generating explanations of common pediatric surgeries to increase efficiency and quality of communication.
View Article and Find Full Text PDFPLoS Negl Trop Dis
September 2025
Universitat Oberta de Catalunya, Barcelona, Spain.
Background: Originally adapted from a paper-based guide for skin-related neglected tropical diseases (NTDs), version 3.0.0 of the World Health Organization (WHO) SkinNTDs app aims to strengthen disease surveillance and frontline health worker capacity in NTD-endemic settings.
View Article and Find Full Text PDFCurr Pharm Teach Learn
September 2025
Pharmaceutical Care Research Group, School of Pharmacy, University College Cork, Cork, Ireland.
Introduction: Pharmacy students were given the opportunity to participate in an online video-recorded objective structured clinical examination (OSCE) with pharmacist feedback. This study aimed to evaluate their views and experiences regarding this initiative and reviewing the recording.
Methods: Third year undergraduate pharmacy students (n = 68) were invited to participate in a formative video-recorded OSCE station online, followed by a one-to-one feedback discussion with a pharmacist facilitator.
J Med Internet Res
September 2025
Washington University in St. Louis, 660 South Euclid Avenue, Campus Box 8054, St Louis, MO, United States, 1 3142737801.
Background: Clinical communication is central to the delivery of effective, timely, and safe patient care. The use of text-based tools for clinician-to-clinician communication-commonly referred to as secure messaging-has increased exponentially over the past decade. The use of secure messaging has a potential impact on clinician work behaviors, workload, and cognitive burden.
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