The pandemic of coronavirus disease-19 starting from Wuhan city of Hubei province in China has engulfed the entire world with adverse effects in terms of loss of human lives and stagnation in economies of most of the countries including the developed ones. One important aspect of this ongoing pandemic is its effect on children and their health round the globe. Apart from its direct effect in terms of morbidity and mortality caused by the illness itself, the indirect effect of the pandemic due to disruption of routine health services, closure of schools, isolation, and quarantining of the diseased and suspected persons, prolonged period of being indoors due to lockdown imposed by most of the countries which are having a more dreadful impact on children’s health and psychological well-being, which is an alarming sign.
Abstract The nutrition and care received in childhood can have a profound impact on the adult life of an individual. Governments and the United Nations have emphasized proper care and nutrition for children, and the Sustainable Development Goals have targeted the elimination of stunting and wasting of children under the age of 5 by 2030. However, South Asia is lagging behind in this metric; the World Bank has noted that about 32 percent of Indian children under age of 5 is stunted, while the world average is 22 percent. While a number of studies have looked into ways of improving well-being of a child, and women’s empowerment, the relationship between patriarchy and children well-being has not been extensively studied. In this paper, we use data from the 2019 Demographic and Health Survey of India to study this relationship. We modify the patriarchy index outlined in Singh et al (2022) and use it in our paper. Our primary dependent variable is the standardized height-for-age percentile. We find that patriarchy negatively affects child height in the northern parts of India, and among certain religious groups. We theorize that culture of the land together with religion of the household impacts how patriarchy affects child height.
AbstractWhat does it mean to be a (female) child in the city of Baku, Azerbaijan? How can we critically interpret the girls’ understandings of well-being considering different forms of compliance with unequal social orders? What conclusions may be drawn from understandings of well- being about the nature of welfare state structures and there-in children’s specific positioning? To answer this question, we conducted qualitative interviews with 13 girls during their various leisure activities. The study shows that parents and in particular mothers are children’s key reference persons, while there are hardly any spaces the girls can explore or reference persons outside their immediate families. The article reconstructs how the 13 girls view the social practices of adults and how they relate these practices to their own perceptions of well-being. We inductively reconstruct different forms of compliance, i.e., the extent to which social practices are consistent with the symbolic representations (norms and values) of a specific social order and specific relations of power and hegemony. The analysis shows how girls make differentiations between adult social practices based on their knowledge orders: some practices they justify through a sort of complicity with adultist structures (competent compliance), others they must accept due to their own vulnerabilities as children (compliance and constitutive vulnerability), still others irritate, are rejected, or sabotaged (fragile compliance).
Christine Hunner-Kreisel, Nigar Nasrullayeva, Stefan Kreisel et al.
Armed conflict represents one of the most profound threats to the health, development, education, and future well-being of children and adolescents. Unlike adults, children experience war during critical periods of physical growth, neurological development, emotional maturation, education, and social formation. The consequences therefore extend beyond immediate injury or death and may influence nutrition, sleep, mental health, cognitive development, physical activity, education, family functioning, and long-term social participation. This comprehensive narrative review examines the multidimensional effects of armed conflict on children and adolescents, integrating evidence from child health, developmental science, mental health, public health, education, physical activity, sport science, resilience research, and humanitarian intervention literature. Particular attention is given to direct physical consequences, indirect health effects, psychological trauma, chronic stress, sleep disruption, developmental consequences, displacement, disruption of education and healthcare, nutrition, physical inactivity, and the potential role of sport and structured physical activity as protective environments. The review also examines evidence concerning resilience and interventions for conflict-affected children, emphasizing that resilience is not an individual trait alone but a dynamic process influenced by family, school, community, social protection, education, healthcare, and opportunities for safe physical activity. A contemporary case study concerning Iran in 2026 is included to illustrate how children may be directly affected in schools and civilian environments. The case study incorporates official UNICEF reporting and findings presented by the Independent International Fact-Finding Mission on Iran concerning the Minab school and Lamerd sports-center attacks. The evidence indicates that protecting children during armed conflict requires an integrated approach extending beyond emergency medical care. Child protection, education continuity, mental-health and psychosocial support, nutrition, sleep, physical activity, sport, family support, healthcare access, and protection of civilian infrastructure should be considered interconnected components of child health.
Early childhood classrooms are developmentally heterogeneous, making instruction and classroom management inseparable challenges. This study examined how differentiated instruction was enacted within science-based learning and how teachers perceived and managed the resulting classroom dynamics. A qualitative multi-site case study was conducted across four early childhood education institutions in Brebes Regency, Central Java, Indonesia. Participating teachers were purposively selected because they implemented differentiated instruction, used inquiry-oriented science activities, and had at least two years of early childhood teaching experience. Data were generated through non-participant classroom observations, semi-structured interviews, and analysis of daily lesson plans and instructional materials, then examined thematically. Three interconnected findings emerged. First, differentiation was enacted through adjusted task complexity, flexible grouping, varied hands-on activities, and responsive scaffolding. Second, these practices were associated with more sustained engagement, clearer routines and transitions, and less need for reactive behavior correction, suggesting that instructional design functioned as a form of proactive classroom management. Third, teacher competence and instructional flexibility supported implementation, whereas planning time and high teacher–child ratios constrained individualized support. The study proposes that differentiated science learning can support classroom management when differentiation, inquiry, routines, and responsive interaction are deliberately aligned. The findings offer implications for teacher professional learning, lesson planning, staffing, and inclusive early childhood practice.
Nurnaningsih Nurnaningsih, Edi Waluyo, Deni Setiawan
Background Smartphone addiction is closely associated with adolescents’ mental health and educational outcomes. Current research lacks comprehensive machine learning studies for predicting smartphone addiction factors, and studies examining relationships between various factors including mediation effects are also insufficient. Methods A cross-sectional survey was conducted among 3,405 adolescents in China (1,853 boys, 54.4%; 1,552 girls, 45.6%; mean age = 14.50 years, SD = 1.18). Eight machine learning algorithms (Linear Regression, Ridge Regression, Random Forest, XGBoost, LightGBM, CatBoost, Support Vector Regression, Bayesian Ridge Regression) were employed with SHAP analysis for interpretability. Predictive variables included demographic characteristics, social support, experiential avoidance, self-efficacy, and emotional symptoms. Baron and Kenny’s method was used for mediation effect analysis. Results Linear models demonstrated optimal performance (R 2 = 0.478, RMSE = 8.66). SHAP analysis identified experiential avoidance as the strongest predictor (SHAP value = 5.472), followed by depressive symptoms (1.723), BMI category (1.438), age (1.394), and anxiety symptoms (1.337). Mediation analysis revealed that social support’s negative association with smartphone addiction (total effect = −0.231) was almost indirect (−0.252), with experiential avoidance mediating the majority of the total effect. The final model explained 49.4% of variance in smartphone addiction. Conclusion Experiential avoidance is a strong correlate of adolescent smartphone addiction and plays a mediating role in the association between social support and smartphone addiction. This finding is consistent with the “reality deficit-virtual compensation” theoretical framework. Additionally, depressive symptoms, BMI category, age, and anxiety symptoms were also independently associated with smartphone addiction.
Background: A first unprovoked seizure is a common neurological presentation in childhood, and the electroencephalogram (EEG) is recommended as a key investigation in its evaluation.Data on the EEG profile of such children from Eastern India and its relationship with early seizure recurrence remain limited.This study aimed to evaluate the seizure semiology and EEG findings in neurologically normal children presenting with a first unprovoked seizure and to determine their association with recurrence within three months.Methods: This single-centre, prospective, observational study enrolled 176 neurologically and developmentally normal children aged 1-18 years presenting with a first unprovoked seizure to a tertiary care hospital in Kolkata between May 2022 and April 2023.All children underwent EEG within 24 hours of the seizure and magnetic resonance imaging (MRI) of the brain.Participants were followed up for three months to detect seizure recurrence.Associations were tested using the chi-square test, with p<0.05 considered significant.Results: The mean age was 6.8 (±4.9) years with a male preponderance (60.2%;M:F 1.4:1).Generalized seizures occurred in 61.4% and focal seizures in 38.6% of children.An abnormal EEG was found in 58.0%, of which 79.4% showed epileptiform discharges.Among the 160 children (90.9%) who completed follow-up, seizure recurred in 45.0%.Recurrence was significantly higher in children with an abnormal EEG (58.5% vs 25.8%; p<0.001) and with focal seizure semiology (54.8% vs 38.8%; p=0.047).Conclusion: An abnormal EEG was present in more than half of children after a first unprovoked seizure and was the strongest predictor of early recurrence.EEG, particularly when combining awake and sleep recordings, is a valuable tool for risk stratification in this population.
Objective To describe pulmonary involvement in childhood-onset primary Sjögren’s syndrome (cSS). Methods This retrospective study included 17 children with cSS diagnosed at Jiangxi Provincial Children’s Hospital between August 2021 and August 2025. Patients were classified by baseline chest high-resolution computed tomography (HRCT)as normal CT (n=8) or abnormal CT (n=9); among patients with abnormal CT, 5 had interstitial lung involvement. Clinical, laboratory, radiological, and outcome data were compared. Results Among 17 children, 14 were female (82.4%), and the mean age at onset was 10.83 ± 3.12 years. Abnormal chest CT findings were detected in 9 patients (52.9%). Age at onset was younger in the abnormal CT group than in the normal CT group (9.37 ± 2.67 vs. 12.48 ± 2.88 years, P = 0.036), and was lowest in the interstitial lung involvement subgroup (8.30 ± 2.51 years, P = 0.022). This subgroup had higher total T and CD4+ T lymphocyte proportions and a lower B lymphocyte proportion P = 0.026, 0.027, and 0.023, respectively. Pleural thickening was the most common CT abnormality (77.8%), followed by ground-glass opacities and nodules >3 mm (33.3% each). Among the 5 patients with interstitial lung involvement, 3 met radiological criteria for ILD, comprising 2 with organizing pneumonia and 1 with nonspecific interstitial pneumonia. During follow-up, 3 of 7 patients with longitudinal imaging achieved complete radiological normalization, 2 improved, and 2 remained stable. Conclusion Pulmonary abnormalities were common in children with cSS. Younger onset and aberrant T/B lymphocyte subsets showed exploratory associations with pulmonary involvement, which appeared mainly inflammatory and demonstrated favorable radiological evolution during follow-up.
Background The use of electroencephalography (EEG) in automated screening of Attention-Deficit/Hyperactivity Disorder (ADHD) has created a large body of literature that suggests promising outcomes, with reported classification accuracies often above 90%. A major methodological issue suggests that a substantial part of these results are actually due to data leakage, whereby EEG epochs pertaining to the same subject end up in both training and testing sets, allowing classifiers to capitalize on features specific to the individual rather than on genuine disorder-related biomarkers. Methods We assessed the performance of three classical machine learning algorithms, namely, Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM), as well as three deep learning models: Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and CNN-BiLSTM, on a standard pediatric EEG dataset containing 121 children and 4,173 epochs. The performance of each model was compared in terms of both segment-wise cross-validation (Protocol A) and subject-wise cross-validation (without any data leakage, Protocol B).To evaluate neurotopographic plausibility without making unsupported causal assertions, we applied Deep SHapley Additive exPlanations (SHAP) to the best-generalizing architecture. Results The performance discrepancy was substantial. Under segment-wise evaluation, the SVM operating on power spectral density (PSD) features reached 90.0% accuracy (95% CI: [89.1%, 90.9%], AUC = 0.96). However, the same model dropped to 65.6% (95% CI: [62.1%, 69.1%], AUC = 0.72) under subject-wise evaluation—a statistically significant 24.4 percentage point collapse ( p < 0.001, Wilcoxon signed-rank). In contrast, deep architectures learning directly from raw EEG were resilient: the stand-alone CNN lost only 2.5 percentage points, achieving 72.7% accuracy (95% CI: [66.0%, 79.4%], AUC = 0.72, recall = 88.0%) on completely unseen participants. Post-hoc SHAP attribution identified the highest relative contributions in frontal (F3, Fz, F4) and central (Cz) electrodes, aligning with established ADHD neurophysiology. Conclusion Hand-engineered spectral features are highly vulnerable to identity leakage, whereas end-to-end convolutional models generalize across subjects with realistic, uninflated performance. Strict subject-wise validation is strongly recommended as standard practice for translational EEG research.
Background Motor skill development is a central objective of school physical education, yet the comparative effectiveness of teaching models remains unclear. Objective This systematic review and network meta-analysis compared physical education teaching models for motor skill development in school-aged children and adolescents. Methods Records were identified from Scopus ( n = 300), Web of Science ( n = 41), OpenAlex ( n = 63), and PubMed ( n = 33). After removal of 42 duplicates, 395 records were screened, 65 full texts were assessed, and 21 studies were retained in the systematic review. Thirteen studies contributed to the under-18 primary network restricted to school-based physical motor execution or sport-specific performance outcomes; 19 contributed to a broader sensitivity network. The protocol was registered in PROSPERO (CRD420261417609). Random-effects models estimated standardized mean differences (SMD) relative to Control and P -score rankings. Results The primary network contained nine treatment nodes. Hybrid Teaching Games for Understanding–Sport Education (TGfU-SE), Nonlinear pedagogy, and Functional games showed the most favorable relative effect estimates in the primary network. However, the treatment ordering was sensitive to outcome definition, participant age, and individual studies, while substantial heterogeneity, network inconsistency, sparse comparisons, and risk of bias remained. In the broad sensitivity network, Cooperative had the highest P -score and estimated effect only while the single Akil visual-motor integration study was included; the node disappeared when that study was removed. Conclusion Restricting the primary network to participants younger than 18 years improved population and outcome comparability and reduced heterogeneity, but significant inconsistency, sparse comparisons, and risk of bias preclude a definitive hierarchy. The P -score ordering should therefore be interpreted as a set of conditional effect estimates rather than proof that one teaching model is universally superior. In practice, physical education teachers should select and implement structured teaching models according to student age, learning objectives, sport content, and teaching context. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420261417609 , identifier PROSPERO (CRD420261417609).
