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Purpose: Pediatricians are the first professionals to provide guidance about language development to families with young children and referrals for those who may have a language or communication disorder. One-quarter of children in the United States are dual language learners (DLLs), yet there is little information about pediatrician's readiness to provide culturally and linguistically responsive care for these children. This pilot study sought to examine pediatricians' knowledge of bilingual language development and its relation to the provision of language and literacy promotion and developmental surveillance for Latine DLLs.
Method: Sixty-seven pediatricians at two academic pediatric clinics completed a survey asking about their knowledge about bilingual language development, Spanish proficiency, and provision of culturally effective health care to Latine DLLs. Analyses examined mean levels of these variables as well as relationships between knowledge, proficiency, and practices.
Results: On average, pediatricians' responses to the knowledge-based questions agreed with the evidence 69% of the time. Only 29% of pediatricians said they felt comfortable counseling Latine parents on bilingual language development, and 75% indicated they had difficulty recognizing signs of a language or communication disorders in Latine children from Spanish-speaking homes. Multiple regressions showed that pediatricians with higher Spanish proficiency and those with greater knowledge of bilingual language development provided more culturally and linguistically responsive care to Latine DLLs.
Conclusions: We identified significant gaps in pediatricians' knowledge about bilingual language development that were associated with their practice patterns. Results highlight the need for incorporating training about bilingual language development into pediatric education and increasing the number of providers that speak languages other than English.
Supplemental Material: https://doi.org/10.23641/asha.29954468.
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http://dx.doi.org/10.1044/2025_AJSLP-24-00572 | DOI Listing |
Neotrop Entomol
September 2025
Dept of Entomology, Federal Univ of Viçosa, Viçosa, MG, Brazil.
The fruit fly Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae) is one of the main pests in apple orchards. Artificial neural networks (ANNs) are tools with good ability to predict phenomena such as the seasonal dynamics of pest populations. Thus, the objective of this work was to determine a prediction model for the seasonal dynamics of A.
View Article and Find Full Text PDFMamm Genome
September 2025
Department of Animal Health and Anatomy, Center for Animal Biotechnology and Gene Therapy, Universitat Autònoma de Barcelona, Travessera Dels Turons, 08193, Cerdanyola del Vallès, Barcelona, Spain.
The mouse remains the principal animal model for investigating human diseases due, among other reasons, to its anatomical similarities to humans. Despite its widespread use, the assumption that mouse anatomy is a fully established field with standardized and universally accepted terminology is misleading. Many phenotypic anatomical annotations do not refer to the authority or origin of the terminology used, while others inappropriately adopt outdated or human-centric nomenclature.
View Article and Find Full Text PDFEndocr J
September 2025
Institute of Liberal Arts and Science, Kanazawa University, Kanazawa, Japan.
GPT-4o, a general-purpose large language model, has a Retrieval-Augmented Variant (GPT-4o-RAG) that can assist in dietary counseling. However, research on its application in this field remains lacking. To bridge this gap, we used the Japanese National Examination for Registered Dietitians as a standardized benchmark for evaluation.
View Article and Find Full Text PDFBMJ Open
September 2025
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada
Objective: This study validates the previously tested Screening for Poverty And Related social determinants to improve Knowledge of and access to resources ('SPARK Tool') against comparison questions from well-established national surveys (Post Survey Questionnaire (PSQ)) to inform the development of a standardised tool to collect patients' demographic and social needs data in healthcare.
Design: Cross-sectional study.
Setting: Pan-Canadian study of participants from four Canadian provinces (SK, MB, ON and NL).
Cardiol Rev
September 2025
Department of Medicine, New York Medical College, Valhalla, NY.
Atrial fibrillation (AF) is a prevalent and complex cardiac arrhythmia requiring multifaceted management strategies. This review explores the integration of large language models (LLMs) and machine learning into AF care, with a focus on clinical utility, privacy preservation, and ethical deployment. Federated and transfer learning methods have enabled high-performance predictive modeling across distributed datasets without compromising data security.
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