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Purpose: Research on early language development has primarily used two categories to group at-risk children, differing by the age at which risk is identified. Late talkers are toddlers with late onset of language development, some of whom may catch up with peers. Developmental language disorder is used to refer to children above the age of 4 years. To this day, the longitudinal relationship between the two categories remains unclear. In this study, we explored early language trajectories in a large birth cohort using exploratory methodology to gain better understanding of the types and prevalence of language trajectories from 14 months to 5 years of age, with particular interest in risk trajectories that cluster statistically.
Method: We conducted latent profile analysis (LPA) on seven language variables collected between 1 and 5 years of age ( = 1,281). Multinomial logistic regression procedure was used to identify child and family characteristics that predicted profile memberships.
Results: The LPA yielded three profiles of language development described as , , and Female sex, longer duration of pregnancy, and higher maternal socioeconomic status increased the odds of belonging to the stable high-language profile, whereas male sex and not being first born increased the odds of belonging to persistent low language profile.
Conclusions: Contrary to previous research, we did not observe increasing or decreasing profiles, suggesting that toddler language difficulties tend to persist at age 5 years, at least in this birth cohort. This suggests commencing language intervention early instead of the wait-and-see approach.
Supplemental Material: https://doi.org/10.23641/asha.29441471.
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http://dx.doi.org/10.1044/2025_JSLHR-24-00767 | DOI Listing |
Mol Ther Methods Clin Dev
June 2025
Precision Safety, Pharma Product Development, Roche Innovation Center Basel, CH-4070 Basel, Switzerland.
Adeno-associated virus (AAV) vectors are widely used in gene therapy, particularly for liver-targeted treatments. However, predicting human-specific outcomes, such as transduction efficiency and hepatotoxicity, remains challenging. Reliable models are urgently needed to bridge the gap between preclinical studies and clinical applications.
View Article and Find Full Text PDFBackground: Transforming Clinical Practice Guideline (CPG) recommendations into computer readable language is a complex and ongoing process that requires significant resources, including time, expertise, and funds. The objective is to provide an extension of the widely used GIN-McMaster Guideline Development Checklist (GDC) and Tool for the development of computable guidelines (CGs).
Methods: Based on an outcome from the Human Centered Design (HCD) workshop hosted by the Guidelines International Network North America (GIN-NA), a team was formed to develop the checklist extension.
Front Psychol
August 2025
Faculty of Information Technology, Monash University, Melbourne, VIC, Australia.
Psychology's crises (e.g., replicability, generalisability) are currently believed to derive from Questionable Research Practices (QRPs), thus scientific misconduct.
View Article and Find Full Text PDFAJO Int
October 2025
Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall Street, Ann Arbor, MI, 48105, USA.
Purpose: Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine Program (MI-SIGHT) was developed to facilitate access to glaucoma and eye disease screening and improve attendance at recommended follow-up in underserved communities. MI-SIGHT offered free eye disease screenings, low-cost glasses and for those who screened positive for glaucoma, personalized education, and language-concordant coaching grounded in motivational interviewing. The primary aims of this study were 1) To explore barriers to eye care among Latine participants with limited English proficiency (LEP) who screened positive for glaucoma, 2) to understand whether and how the MI-SIGHT program facilitated access to care and 3) to understand participant experience in MI-SIGHT to inform the development of future interventions.
View Article and Find Full Text PDFRev Cardiovasc Med
August 2025
Cardiovascular Surgery Department, Ankara Bilkent City Hospital, 06800 Ankara, Turkey.
Background: This study aimed to investigate the performance of two versions of ChatGPT (o1 and 4o) in making decisions about coronary revascularization and to compare the recommendations of these versions with those of a multidisciplinary Heart Team. Moreover, the study aimed to assess whether the decisions generated by ChatGPT, based on the internal knowledge base of the system and clinical guidelines, align with expert recommendations in real-world coronary artery disease management. Given the increasing prevalence and processing capabilities of large language models, such as ChatGPT, this comparison offers insights into the potential applicability of these systems in complex clinical decision-making.
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