This study examined the extent to which early intervention (EI) speech-language pathologists (SLPs) use and recommend language input strategies for caregivers of children with language delays and the child factors associated with these decisions. Participants included 213 SLPs who completed an online survey. Wilcoxon signed-rank tests, Friedman's analyses of variance, and Spearman correlations were used to determine the extent to which EI SLPs used and recommended language input, child factors that influenced recommendations and input, and relationships between SLPs' self-reported strategies and recommendations to caregivers. EI SLPs reported recommending expanding on child utterances more than other strategies. EI SLPs reported using grammatical input more than telegraphic input and recommended grammatical phrases as children made gains in spoken language. Language strategies used by SLPs inconsistently aligned with their recommendations to caregivers. Results underscore the importance of evaluating recommendations to caregivers in the context of EI.
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http://dx.doi.org/10.1177/10538151221086512 | DOI Listing |
Pflugers Arch
January 2025
School of Life Sciences, Technical University of Munich, 85354, Freising, Germany.
Personalised nutrition (PN) as a new endeavour emerged in the background of the human genome project with the ease to analyse genetic heterogeneity. First commercial offers with recommendations for diet and lifestyle changes, usually based on a few polymorphisms, entered markets soon after the presentation of the human genome blueprint. Although PN has seen many attempts, meanwhile, with the inclusion of other biomedical measures such as microbiome and/or continuous glucose monitoring, scientific assessments of such approaches in various settings revealed limited success.
View Article and Find Full Text PDFSci Rep
January 2025
Nanfang College Guangzhou, Guangzhou, 510970, China.
Named Entity Recognition (NER) is an essential component of numerous Natural Language Processing (NLP) systems, with the aim of identifying and classifying entities that have specific meanings in raw text, such as person (PER), location (LOC), and organization (ORG). Recently, Deep Neural Networks (DNNs) have been extensively applied to NER tasks owing to the rapid development of deep learning technology. However, despite their advancements, these models fail to take full advantage of the multi-level features (e.
View Article and Find Full Text PDFEur J Neurosci
January 2025
Institute of Neuroscience (IONS), UCLouvain, Brussels, Belgium.
Experiencing music often entails the perception of a periodic beat. Despite being a widespread phenomenon across cultures, the nature and neural underpinnings of beat perception remain largely unknown. In the last decade, there has been a growing interest in developing methods to probe these processes, particularly to measure the extent to which beat-related information is contained in behavioral and neural responses.
View Article and Find Full Text PDFBehav Sci (Basel)
January 2025
School of Foreign Languages, Ocean University of China, Qingdao 266005, China.
Collocations typically refer to habitual word combinations, which not only occur in texts but also constitute an essential component of the mental lexicon. This study focuses on the mental lexicon of Chinese learners of English as a foreign language (EFL), investigating the representation of collocations and the influence of input frequency and L2 proficiency by employing a phrasal decision task. The findings reveal the following: (1) Collocations elicited faster response times and higher accuracy rates than non-collocations.
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