Previous studies suggest that lexical competence is an important factor that influences reading skills and spelling accuracy in primary school children. Understanding the relationship between these skills will provide valuable insights to improve reading and writing enhancement and intervention strategies. The aim of this pre-post longitudinal study is to examine the effectiveness of an enhancement program, in which there are activities proposed through a narrative and metacognitive methodology, designed to develop the cognitive processes of lexical acquisition and its effects on reading and writing ability. A total of 74 primary school children (M-age = 7.04 years) participated in the research. They were divided into groups: experimental, which carried out the enhancement, and control groups, which carried out the typical school program. The results show that children who carried out the enhancement obtained higher scores in reading skills, specifically in reading accuracy and text comprehension and spelling accuracy, in comparison with their peers in the control group. These results suggest that strengthening the lexical semantic pathway, as theorized by Coltheart's two-way model, can lead to improved reading comprehension and diminished reading errors and spelling inaccuracies.
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http://dx.doi.org/10.3390/children10081416 | DOI Listing |
J Echocardiogr
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Division of Cardiology, Department of Internal Medicine, Keimyung University Dongsan Medical Center, Keimyung University School of Medicine, 1035 Dalgubeol-Daero, Dalseo-Gu, Daegu, 42601, Republic of Korea.
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Oncol Ther
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Coordinator of the International Head and Neck Scientific Group, Padua, Italy.
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Am J Sports Med
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Department of Orthopaedic Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.
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Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).
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