The Rey-Osterrieth Complex Figure (ROCF; Rey 1941; Osterrieth, 1944) is frequently used in the neuropsychological assessment of children and adults. The present study was designed, in part, to examine the impact of providing organizational scaffolding to young children being tested with the ROCF. To this end, 6-, 7-, and 8-year-old children were administered the test either in the standard fashion, or using a format in which the 18 key elements of the figure were introduced sequentially. Participants included 132 children who were randomly assigned to the standard or step-by-step administration groups. Significantly higher accuracy and organization scores for both copy and recall were seen with the step-by-step format than with the standard format, even though children in the step-by-step condition took less time to execute their drawings. Retention of encoded information was not affected by age or testing format. The fact that 6-year-olds in the step-by-step condition performed as well as, or better than, 8-year-olds in the standard condition suggests that the primary problem young children experience with the ROCF lies with organizational strategy formation. Advantages of using the Step-by-step ROCF in clinical practice are discussed.
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BMC Pediatr
January 2025
Department of Medical Laboratory Sciences, School of Allied Health Sciences, Kampala International University Western Campus, P. O. Box 71, Bushenyi, Uganda.
In spite of the commendable global Pneumococcal Conjugate Vaccine (PCV) coverage in the last two decades, completion and timeliness of receipt of all the required doses are still below target. In Uganda, the 3 + 0 PCV regimen has been reported to have a steady decline in the completion rate and the reasons for the delayed completion are unidentified. This study aimed at assessing the influence of socio-demographic factors on delayed PCV completion among young children.
View Article and Find Full Text PDFJ Exp Psychol Gen
January 2025
Centre for Perception and Cognition, School of Psychology, University of Southampton.
It has been claimed that deliberately making errors while studying, even when the correct answers are provided, can enhance memory for the correct answers, a phenomenon termed the derring effect. Such deliberate erring has been shown to outperform other learning techniques, including copying and underlining, elaborative studying with concept mapping, and synonym generation. To date, however, the derring effect has only been demonstrated by a single group of researchers and in a single population of participants.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Introduction: Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the generic genotyping workflows are unable to accurately infer copy numbers and complete genotypes of individual KIR genes from next-generation sequencing data. Thus, specialized genotyping tools are needed to genotype this complex region.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Cancer is the second leading cause of death, significantly threatening human health. Effective treatment options are often lacking in advanced stages, making early diagnosis crucial for reducing mortality rates. Circulating tumor cells (CTCs) are a promising biomarker for early detection; however, their automatic detection is challenging due to their heterogeneous size and shape, as well as their scarcity in blood.
View Article and Find Full Text PDFPeerJ Comput Sci
November 2024
School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.
Named entity recognition (NER) is a crucial task in natural language processing, particularly challenging in the legal domain due to the intricate and lengthy nature of legal entities. Existing methods often struggle with accurately identifying entity boundaries and types in legal texts. To address these challenges, we propose a novel sequence-to-sequence framework designed specifically for the legal domain.
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