Children adopted from China represent the single largest group of internationally adopted children in this country. Because the adoptive families typically do not speak any Chinese language or dialect, most of these children experience an abrupt shift in their language environment. How age of adoption affects the course of English language development of children adopted from China is the focus of this study. All of the children in this study were either infants or toddlers at the time of adoption and all came from the same orphanage. The results showed that the older children (toddlers) were at both an advantage and a disadvantage when it came to English language development. The advantage of being older was that they learned faster. The disadvantage of being older was that there was more for them to learn to become age-appropriate in their English language development. There was, however, no evidence to suggest that the language switch from a Chinese- to an English-language environment was a formidable obstacle for either the infants or the toddlers.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1055/s-2005-864214 | DOI Listing |
JMIR Res Protoc
January 2025
College of Nursing, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Background: TheKeep.Ca was built to facilitate engagement with those experiencing cancer in Manitoba, Canada. Constructed between 2020 and 2024 with a group of patient advisors, the website includes information on engagement activities including research participation, the patient advisor role, and how those experiencing cancer can access these Manitoba activities.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJCO Clin Cancer Inform
January 2025
Department of Radiology, Dr BRAIRCH, All India Institute of Medical Sciences, New Delhi, India.
Purpose: To explore the perceived utility and effect of simplified radiology reports on oncology patients' knowledge and feasibility of large language models (LLMs) to generate such reports.
Materials And Methods: This study was approved by the Institute Ethics Committee. In phase I, five state-of-the-art LLMs (Generative Pre-Trained Transformer-4o [GPT-4o], Google Gemini, Claude Opus, Llama-3.
Database (Oxford)
January 2025
Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON CA K1A 0C6, Canada.
It is well-known that the use of vocabulary in phenotype treatments is often inconsistent. An earlier survey of biologists who create or use phenotypic characters revealed that this lack of standardization leads to ambiguities, frustrating both the consumers and producers of phenotypic data. Such ambiguities are challenging for biologists, and more so for Artificial Intelligence, to resolve.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!