Background: Migration is increasing worldwide. In previous research into people with cancer from culturally and linguistically diverse backgrounds, interpreter accuracy, professionalism and continuity have emerged as key concerns for patients. Little is known about interpreters' perceptions of their role and the challenges they face. This study aimed to obtain their perspective.
Methods: Thirty interpreters (Greek n = 7, Chinese n = 11, and Arabic n = 12) participated in four focus groups which were audio-taped, transcribed and analysed for themes using N-Vivo software.
Results: Skills as an interpreter were broadly perceived as conveying information accurately, being confidential and impartial. Three broad dilemmas faced by interpreters emerged: accuracy versus understanding; translating only versus cultural advocacy and sensitivity; and professionalism versus providing support. Some saw themselves as merely an accurate conduit of information, while others saw their role in broader terms, encompassing patient advocacy, cultural brokerage and provision of emotional support. Perceived challenges in their role included lack of continuity, managing their own emotions especially after bad news consultations, and managing diverse patient and family expectations. Training and support needs included medical terminology, communication and counselling skills and debriefing. Interpreters suggested that oncologists check on interpreter/patient's language or dialect compatibility; use lay language and short sentences; and speak in the first person.
Conclusions: Resolving potential conflicts between information provision and advocacy is an important area of cross-cultural communication research. Further training and support is required to enhance interpreters' competence in managing delicate situations from a professional, cultural and psychological perspective; and to assist doctors to collaborate with interpreters to ensure culturally competent communication. Ultimately, this will improve interpreters' well-being and patient care.
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http://dx.doi.org/10.1007/s00520-010-1046-z | DOI Listing |
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
J Imaging Inform Med
January 2025
Department of Radiation Oncology, Henry Ford Health, Detroit, MI, USA.
Automatic segmentation of angiographic structures can aid in assessing vascular disease. While recent deep learning models promise automation, they lack validation on interventional angiographic data. This study investigates the feasibility of angiographic segmentation using in-context learning with the UniverSeg model, which is a cross-learning segmentation model that lacks inherent angiographic training.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFJ Youth Adolesc
January 2025
Department of Social Work, the Chinese University of Hong Kong, Hong Kong, China.
Considering the potential detrimental impact of poverty on psychological development and the resulting harmful cycles, implementing poverty alleviation interventions is necessary for children and adolescents. Although several meta-analyses have demonstrated the effectiveness of monetary poverty reduction programs, there remains a significant gap in understanding how multidimensional poverty reduction strategies boost psychological development. This meta-analysis aims to address this gap by disclosing the impact of multifaceted anti-poverty interventions on the psychological development of children and adolescents.
View Article and Find Full Text PDFSci Rep
January 2025
Emergency Department, The State Key Laboratory for Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Variation in the incidence, survival rate and factors associated with survival after cardiac arrest in China is reported. Some studies have tried to fill the knowledge gap regarding the epidemiology of cardiac arrest in China but were unable to identify reasons for the reported differences. Therefore, the purpose of this study was to describe Chinese management of cardiac arrest, particularly from the perspective of compression, ventilation, monitoring, treatment, and extracorporeal cardiopulmonary resuscitation.
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