This study examined whether immersive virtual reality (VR) supports second-language vocabulary learning in school-aged children compared to passive computer-based training. Seventy-three Swedish middle-school students learned novel words by assembling objects in VR and by viewing object assembly on a computer screen in a crossover design. Word recall was tested after each condition, and individual differences in language aptitude and sustained attention were assessed. Overall, recall was higher after computer-based training than VR. However, sustained attention was the strongest predictor of learning outcomes, and the difference between conditions was (marginally) significant only for children with higher sustained attention. No VR behavioural measures (gaze, assembly time, rotation) explained learning outcomes. These findings suggest that VR may not universally enhance vocabulary learning but could benefit learners with specific attentional profiles. Further research should explore how VR design and training duration influence language acquisition in school settings.
Maja Rudling, Theodor Rumetshofer, Jens Nirme et al.
INTRODUCTION: Children who have sustained a serious injury or who have a chronic health condition, such as diabetes or epilepsy, may have their school performance adversely impacted by the condition, treatment of the condition and/or time away from school. Examining the potential adverse impact requires the identification of children most likely to be affected and the use of objective measures of education performance. This may highlight educational disparities that could be addressed with learning support. This study aims to examine education performance, school completion and health outcomes of children in New South Wales (NSW), Australia, who were hospitalised with an injury or a chronic health condition compared with children who have not been hospitalised for these conditions. METHOD AND ANALYSIS: This research will be a retrospective population-level case-comparison study of hospitalised injured or chronically ill children (ie, diabetes, epilepsy, asthma or mental health conditions) aged ≤18 years in NSW, Australia, using linked health and education administrative data collections. It will examine the education performance, school completion and health outcomes of children who have been hospitalised in NSW with an injury or a chronic health condition compared with children randomly drawn from the NSW population (matched on gender, age and residential postcode) who have not been hospitalised for these conditions. ETHICS AND DISSEMINATION: The study received ethics approval from the NSW Population Health Services Research Ethics Committee (2018HRE0904). Findings from the research will be published in peer-reviewed journals and presented at scientific conferences.
Rebecca J Mitchell, Cate M Cameron, Reidar P. Lystad et al.
OBJECTIVE: To determine the effect of postural education on the learning and postural habits of elementary school children without physical intervention. METHODS: We searched PubMed, Lilacs, SciELO, Cochrane, and Science Direct data bases and reference lists of studies in February 2020. The eligibility criteria were randomized clinical trials related to the effect of postural education in children aged between 6 and 12 years old. Two authors independently assessed trials for inclusion and risk of bias: randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. Data were extracted in standardized tables including information on author, publication year, country, sample size, age, sex, intervention characteristics, outcome measurements and results. RESULTS: We found seven clinical trials (involving 2,568 children) for the review. The studies were conducted between 2000 and 2018: four in Belgium, two in Spain, and one in Germany. All seven included trials underwent evaluation: only one had a clear process of randomization and allocation concealment. All included studies were judged as having high risk of bias in at least one domain or have concerns for multiple domains. CONCLUSIONS: The positive effects of acquired knowledge and postural habits found in the studies cannot be used to reliably support postural education in elementary school children due to a high risk of bias in the evaluated studies.
Paola Janeiro Valenciano, Fabíola Unbehaun Cibinello, Jéssica Caroliny de Jesus Neves et al.
This systematic review provides a comprehensive overview of child sexual abuse prevalence globally, along with an examination of the effectiveness of school-based prevention education programmes for primary school-aged children. These prevention programmes utilise social cognitive learning theories to teach children the importance of identifying and responding to abusive situations. A total of 676 papers were evaluated with 13 Randomised Controlled Trial (RCT) or cluster RCT design studies identified as meeting the study's inclusion criteria. These studies were published in English between January 2000 and May 2022, and focus on outcomes of school-based prevention programmes designed for primary school-aged children (5–12 years old). To ensure a comprehensive and academically rigorous analysis, the following databases were included: Science Direct, Web of Science, Scopus, the American Psychiatric Association (APA) PsycINFO, Ovid Medline, and Embase. The studies reviewed aim to evaluate the effectiveness of various child sexual abuse prevention programmes in improving children's knowledge and recognition of, and response to potentially unsafe situations. In terms of outcomes and results, the interventions have significantly impacted knowledge, skills, confidence, and awareness in the short and long term. These studies used different intervention methods, including mobile applications, personal safety programmes, and protective behaviour programmes, delivered in various formats such as web-based, textbooks, and in-person sessions. This systematic review highlights the importance of child sexual abuse prevention programmes in schools and the need for further research.
ABSTRACT: Current automated pain assessment methods only focus on infants or youth. They are less practical because the children who suffer from postoperative pain in clinical scenarios are in a wider range of ages. In this article, we present a large-scale Clinical Pain Expression of Children (CPEC) dataset for postoperative pain assessment in children. It contains 4104 preoperative videos and 4865 postoperative videos of 4104 children (from 0 to 14 years of age), which are collected from January 2020 to December 2020 in Anhui Provincial Children's Hospital. Moreover, inspired by the dramatic successful applications of deep learning in medical image analysis and emotion recognition, we develop a novel deep learning-based framework to automatically assess postoperative pain according to the facial expression of children, namely Children Pain Assessment Neural Network (CPANN). We train and evaluate the CPANN with the CPEC dataset. The performance of the framework is measured by accuracy and macro-F1 score metrics. The CPANN achieves 82.1% accuracy and 73.9% macro-F1 score on the testing set of CPEC. The CPANN is faster, more convenient, and more objective compared with using pain scales according to the specific type of pain or children's condition. This study demonstrates the effectiveness of deep learning-based method for automated pain assessment in children.
Abstract Throughout the pandemic Chile implemented a series of public health mandates restricting mobility and high social-contact activities with a goal of reducing disease spread. In this paper, we study the impact of one of these policies-central planner variation in school reopenings on labor market outcomes. We examine how access to supervised care for children in school affected mothers’ labor supply and show that mothers increased labor force participation anywhere from 2.6 to 21.0 percentage points (ppts) as schools reopened. As mothers came back to the labor force, however, unplanned disruptions decreased their ability to stay actively engaged in work and increased their take up of leave from work, an artifact of unanticipated sick children and quarantine policies that particularly affected mothers who were secondary earners in the household. Conditional on being in the labor force, having a teenager buffered both mothers and fathers from work disruptions; parents were more likely to be actively working and less likely to be on leave. Our findings support a theory that parental labor supply is sensitivity to disruptions in the care of children but also depends on household composition and each parent’s role beyond gender. Policies that encourage consistent formalized systems of care and learning for children will not only benefit children, but also a second-earner’s ability to re-enter the labor force and advance at work. JEL: J13, J16, J22
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a considerably common childhood-onset neurodevelopmental disorder, often associated with socio-behavioral and academic difficulties. There is an increased risk for development of a range of future problems such as psychiatric disorders, difficulties in employment, and relationships. The aim of this study was to know the prevalence and determinants of ADHD among primary school children in district Dehradun and to assess the learning difficulties and classroom behavior in these students. MATERIALS AND METHODS: In this cross-sectional study, overall, 228 students (aged 6–12 years) studying in a primary school were assessed for ADHD after seeking the written informed consent from their parents. The data were analyzed using Excel sheet and SPSS software (22.0 version). For all qualitative measures, frequency and percentages were calculated, and for quantitative measures, mean and standard deviation were calculated. For analysis of categorical values, Chi-square test was used. P < 0.05 was considered statistically significant. RESULTS: The prevalence of ADHD was found to be 11.8% based on the teacher tool only and 1.75% based on the parent and teacher tools combined. ADHD was found to be significantly more in males. Inattention was the most prevalent subtype of ADHD, and children screened positive for ADHD had significant learning difficulties at various levels. CONCLUSION: The possibility of ADHD in students with academic difficulties should not be ignored as children with ADHD usually face significant problems at school such as learning difficulties and have been shown to be at increased risk for a broad range of negative outcomes. Early identification and treatment of ADHD can significantly reduce the rates of some of these poor outcomes. Screening these children in the early years will help the parents, children, teachers, and community at large.
Gurpreet Kaur Chawla, Ruchi Juyal, Deep Shikha et al.
Purpose Intervention provided to school-age children with developmental language disorder often relies on the provision of performance feedback, yet it is unclear whether children with this disorder benefit from feedback-based learning. The study evaluates the effect of performance feedback on learning in children with developmental language disorder. Method Thirteen 8- to 12-year-old children with developmental language disorder and 14 age- and gender-matched children with typical language development completed two learning tasks whose objective was to pair nonword novel names with novel objects. The two tasks differed in the presence of performance feedback to guide learning. Learning outcomes on immediate and follow-up tests were compared between the feedback-based and feedback-free tasks. Additionally, an electrophysiological marker of feedback processing was compared between children with and without developmental language disorder. Results Children with developmental language disorder demonstrated poorer learning outcomes on both tasks when compared with their peers, but both groups achieved better accuracy on the feedback-free task when compared with the feedback-based task. Within the feedback-based task, children were more likely to repeat a correct response than to change it after positive feedback but were as likely to repeat an error as they were to correct it after receiving negative feedback. While children with typical language elicited a feedback-related negativity with greater amplitude to negative feedback, this event-related potential had no amplitude differences between positive and negative feedback in children with developmental language disorder. Conclusions Findings indicate that 8- to 12-year-old children benefit more from a feedback-free learning environment and that negative feedback is not as effective as positive feedback in facilitating learning in children. The behavioral and electrophysiological data provide evidence that feedback processing is impaired in children with developmental language disorders. Future research should evaluate feedback-based learning in children with this disorder using other learning paradigms.
Abstract Nature-based learning within the primary school curriculum offers numerous potential benefits. However, there is a lack of clarity about how school grounds can be designed to enable effective nature-based learning. There is also little knowledge of how specific features within green school grounds contribute to specific desirable outcomes, such as improved academic performance or health. To address this gap, a systematised review of peer-reviewed academic literature was undertaken, with 173 databases searched from January to December 2021. The search included studies of nature-based learning on school grounds and literature concerned with the design of green school grounds for fostering nature connectedness and broader educational outcomes for primary school children aged 5 to 11. No date or geographical restrictions were applied. Of a total of 285 articles initially identified, 11 matched the inclusion criteria. Results from these indicate significant research gaps on the design of green learning spaces in schools. While studies note apparent positive links between nature-based learning in school grounds and improved subject-specific learning, wellbeing, and nature connectedness, there is very little empirical evidence of how specific design features are linked to specific outcomes. Furthermore, the current evidence base is poorly representative of different social, cultural, and geographical contexts and not fully reflective of all primary schooling ages. The challenging contexts of urban schools and schools with small footprints are also inadequately addressed. These findings indicate an urgent need for increased research to guide the design of school grounds for the implementation of nature-based learning programmes for primary school learners.
BACKGROUND: Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children. METHODS AND FINDINGS: Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered. CONCLUSIONS: To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.
