The construct of engagement provides a holistic lens for understanding how children interact with learning activities, with distinct behavioral, emotional-affective, and cognitive components forming a multidimensional engagement profile for each child. As the understanding of engagement and recognition of its complexity grow, a pressing need has emerged for a synthetic, coherent review that simultaneously integrates extant literature and clarifies the conceptualization of engagement, identifies its key facilitators and consequences, and proffers a theoretical framework that elaborates on how engagement functions. Using a developmental-contextual approach, this article integrates empirical and theoretical scholarship to illustrate how engagement is produced by developmental and relational processes involving transactions across multiple ecologies. The integrative model of engagement offers a comprehensive perspective on the multiple pathways-psychological, cognitive, social, and cultural-underlying the development of children's engagement. Conceptualizing engagement as a multidimensional construct shaped by interactions between an individual and the environment enriches the field's understanding of the personal, contextual, and sociocultural factors that foster or undermine engagement. This framing also enhances understanding of the psychosocial mechanisms through which learning environments influence engagement. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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http://dx.doi.org/10.1037/amp0000522 | DOI Listing |
Sleep
January 2025
UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN - Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted Memory Reactivation (TMR), involving cueing learned material during post-training sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and post-training sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during post-training sleep affects performance gains and delayed microstructural remodeling, using both standard Diffusion Tensor Imaging (DTI) and advanced Neurite Orientation Dispersion & Density Imaging (NODDI).
View Article and Find Full Text PDFEval Rev
January 2025
Global Development Network, Lanzhou University and Director of Evaluation, New Delhi, India.
Official development agencies are increasingly supporting civil society lobby and advocacy (L&A) to address poverty and human rights. However, there are challenges in evaluating L&A. As programme objectives are often to change policies or practices in a single institution like a Government Ministry, L&A programmes are often not amenable to large-n impact evaluation methods.
View Article and Find Full Text PDFJ Prev (2022)
January 2025
Faculty of Health Sciences, Valencian International University, Pintor Sorolla 21, 46002, Valencia, Spain.
Chemsex is a specific practice of sexualized drug use (SDU), linked mainly to the group of men who have sex with men (MSM). This practice has become a public health problem due to the increase in sexually transmitted infections and HIV. However, there are groups and aspects that require greater visibility and research.
View Article and Find Full Text PDFMol Neurobiol
January 2025
Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, Guangxi, China.
Dysregulation of long non-coding RNAs (lncRNAs) is implicated in the pathophysiology of ischemic stroke (IS). However, the molecular mechanism of the lncRNA SERPINB9P1 in IS remains unclear. Our study aimed to explore the role and molecular mechanism of the lncRNA SERPINB9P1 in IS.
View Article and Find Full Text PDFPharmacoeconomics
January 2025
Belgian Health Care Knowledge Centre, Brussels, Belgium.
Background: Forecasting future public pharmaceutical expenditure is a challenge for healthcare payers, particularly owing to the unpredictability of new market introductions and their economic impact. No best-practice forecasting methods have been established so far. The literature distinguishes between the top-down approach, based on historical trends, and the bottom-up approach, using a combination of historical and horizon scanning data.
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