Context School-based nutrition interventions have the potential to promote dietary behaviors and other outcomes among children and adolescents. However, inconsistent reporting of outcomes and measurement tools limits evidence synthesis and the identification of effective intervention strategies. Objective This umbrella review aimed to synthesize the range of outcomes related to diet, health, well-being, and education reported in systematic reviews of school-based nutrition interventions, along with the measurement tools used. The findings will be used to inform the development of a Core Outcome Set (COS) to guide future evaluations in this field. Data sources We conducted a systematic search across 7 databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews, PsycINFO, CINAHL, Web of Science, and Scopus) to identify systematic reviews published from January 2018 to December 2023. Data extraction Data on outcomes related to diet, health, well-being, and education were extracted from eligible systematic reviews. When available, information on outcome measurement tools was also extracted. Additional details were retrieved from primary studies referenced within systematic reviews as needed. Data analysis Ninety-eight systematic reviews, comprising 965 unique studies, were included. Outcomes were categorized into 4 domains: (1) "diet" (68.8%), subdivided into "dietary intake" and "diet-related cognitive/attitudinal behaviors"; (2) "physical health" (44.8%), subdivided into "body composition" and "clinical/biochemical measures"; (3) "social and emotional well-being and behavior" (9.2%); and (4) "education" (6.4%). Substantial heterogeneity was observed across outcome domains, subdomains, and measurement tools, which presents challenges for evidence synthesis and limits comparability across studies. Conclusions The findings of this review underscore the need for a stakeholder-informed, context-aware COS to standardize outcome reporting in school-based nutrition interventions. Such standardization is essential to improve the comparability of research findings, enhance evidence synthesis, and facilitate the translation of evidence into policy and practice. Subsequent phases of this work will involve diverse stakeholder engagement to finalize the COS and recommend appropriate tools for outcome measurement for evaluating school-based nutrition interventions. Systematic review registration PROSPERO registration No. CRD42022378746.
Monitoring bladder filling is crucial in patients with neurogenic lower urinary tract dysfunction, particularly for safe and timely clean intermittent catheterization. Wearable ultrasound devices have recently gained attention as potential aids for continuous bladder monitoring, but they differ fundamentally from traditional bladder scanners. While portable scanners directly measure postvoid residual volume in milliliters, first-generation wearable devices using amplitude mode (A-mode) ultrasound primarily monitor bladder fullness trends and provide threshold-based alerts rather than precise quantitative volume measurements. This narrative review examines wearable ultrasound technologies in neurourology, searching PubMed, Embase, IEEE Xplore, and Google Scholar for relevant clinical studies. Most available data come from small observational studies in pediatric populations. In children with functional voiding dysfunction (FVD), devices such as SENS-U achieved sensitivities of 85%-90% for detecting bladder fullness thresholds with good correlation to urodynamic measurements. However, performance in neurogenic bladder populations is concerning: a recent study in children with neurogenic bladder reported only 46% accuracy and 13% specificity using DFree, indicating unacceptably high false-positive rates. No prospective validation studies have been conducted in adults with spinal cord injury, multiple sclerosis, or those at risk for autonomic dysreflexia. Regulatory classifications vary significantly among devices: SENS-U holds Conformité Européenne marking as a Class IIa medical device for pediatric use, while DFree is marketed as a consumer wellness product without medical device approval. EdgeFlow UW20, which employs a deep learning-based automatic bladder contour detection, recently received Ministry of Food and Drug Safety approval in Korea as a digital medical device. Currently, evidence supports considering wearable bladder monitors only for pediatric FVD under medical supervision. For neurogenic bladder populations, these devices are not recommended for routine clinical use until population-specific validation studies demonstrate adequate diagnostic accuracy. The emergence of B-mode (brightness mode) deep learning-based devices may address the fundamental limitations of first-generation A-mode technology.
Artificial intelligence (AI) is increasingly recognized as a transformative technology in healthcare, with growing evidence supporting its applicability across time-critical clinical environments. This perspective aims to evaluate the integration of AI and machine learning (ML) into pediatric emergency departments (PEDs) across three core domains: clinical decision support, stakeholder engagement, and medical education. Within clinical decision support, ML architectures have demonstrated high predictive performance across several high-acuity clinical scenarios, including triage stratification, pediatric traumatic brain injury risk classification, early sepsis detection and clinical deterioration prediction, and dermatological assessment. Model interpretability and real-world implementability remain critical prerequisites for clinical adoption, with explainability methods representing fundamental instruments to enhance transparency and stakeholder trust. Regarding stakeholder engagement, the triadic dynamic among clinicians, caregivers, and patients defines a unique communication challenge in PEDs, with large language models (LLMs) showing preliminary utility; however, stakeholder-inclusive model validation and robust data privacy protections for minors remain key challenges, particularly regarding legal ambiguities of LLM deployment in clinical pipelines. In medical education, AI-driven simulation platforms and LLM-generated adaptive curricula represent promising tools for competency-based training across pediatric emergency scenarios. Future directions emphasize the imperative of prospective multicenter validation in pediatric-specific cohorts, rigorous data quality standards addressing conformance, completeness, and plausibility, and the development of pediatric-tailored governance frameworks. Real-world implementation will require the systematic involvement of all stakeholders-including children, caregivers, clinicians, developers, and institutions-as co-designers of equitable, transparent, and safe AI systems for this uniquely vulnerable population.
Introduction Evidence suggests that Serious games (SG) can be effective for improving specific neuropsychological skills. This systematic review examines the effectiveness of SGs for training attention and executive functions (EFs) in children and the degree of "far transfer" from digital training to real-world academic and behavioral outcomes. Methods The systematic review was conducted according to the PRISMA (2020) guidelines on Scopus, PubMed, EBSCO, and Web of Science databases. Only studies on school-aged population with a pre- and post-training assessment of attention and EFs and with a control group were included. Results The screening process yielded nine relevant studies. SGs improve attention and EFs, such as working memory, cognitive flexibility and inhibition in typically developing children, as well as in children with ADHD, intellectual disabilities, behavioral disorders, autism and difficulty with inhibitory control. SGs demonstrate promising improvements primarily in near-transfer. Discussion Although the immediate benefits are evident in many cases, the transfer to untrained skills (far transfer) and the long-term effects remain limited and require further investigation. Motivation and engagement were often qualitatively inferred rather than directly measured. The effectiveness data were discussed in relation to the type of neurodevelopmental deficit.
Background/objectives Children develop the ability to construct meaning from language long before they learn to read. These foundational language processes support learning across academic contexts and form the basis for later reading and writing. However, many students, particularly those with Developmental Language Disorder (DLD), enter school with weaknesses in oral academic language that limit their ability to understand and express increasingly complex classroom discourse. Despite the central role of narrative and expository language in early instruction, explicit and systematic intervention targeting both discourse genres remains uncommon in the early grades. The purpose of this randomized controlled trial was to examine the immediate and maintained effects of a structured, small-group oral language intervention targeting both narrative and expository discourse for early elementary-age students with and without DLD. Methods Participants (N = 80) were kindergarten through second-grade students identified as having DLD or significantly weak narrative language performance and were randomly assigned to an intervention condition or business-as-usual control. Narrative outcomes were collected for all participants at pretest, posttest, and a two-month follow-up, and expository outcomes were collected at posttest. Results Results indicated statistically significant intervention effects for narrative language at posttest, with gains maintained at follow-up. Treatment effects were not moderated by language status, and subgroup analyses demonstrated large effects for students with DLD. Regression analyses indicated a non-significant intervention effect on expository outcomes. Conclusions Findings provide experimental evidence that explicit, contextualized narrative and expository language instruction delivered in brief small-group sessions can produce meaningful and durable improvements in narrative language for young children, including those with DLD.
Children with autism spectrum disorder (ASD) have significant deficits in communication, emotional recognition, perspective-taking, and social skills. Evidence from existing studies has shown that the social interaction skills of children with ASD are closely related to their theory of mind (ToM) abilities. While prior research has explored the effect of single intervention modes such as computer-assisted instruction (CAI) and the thought-bubble strategy, the efficacy of combining CAI with the thought-bubble strategy remains unclear. This study investigates the effectiveness of this multifaceted approach in fostering ToM development in children with ASD. Using a single-case design, the intervention for two children with ASD involved implementing CAI combined with the thought-bubble strategy to teach ToM skills to children with ASD, including basic beliefs, first-order beliefs and first-order false beliefs. Results indicated that both children showed an increase in their ToM abilities, evidenced by their increased tendency to use "I think/I feel" statements in everyday life, enhanced understanding of false beliefs, and a decrease in negative emotions. The thought-bubble strategy can be embedded in CAI, and the combination of these two methods facilitates the enhancement of the ToM abilities among children with ASD with good maintenance and generalization effects.
Objective To investigate the knowledge, attitudes and practices (KAP) of parents of children born moderate to late preterm (32 to <37 weeks' gestation) regarding their children's neurodevelopment. Design A cross-sectional study. Setting This study was conducted from March to June 2025 at the Second People's Hospital of Changzhou. Participants Parents of children born moderate to late preterm were surveyed in the outpatient clinic when their children were at preschool age. Interventions No. Primary and secondary outcome measures KAP scores were assessed using a questionnaire, and differences among parents were compared across different demographic characteristics. KAP scores were converted to percentages and interpreted using a 70% descriptive cut-off. Structural equation modelling was employed to investigate the inter-relationships among the KAP dimensions. Results This study included 499 participants, with a mean maternal age of 34.03±5.42 years; the majority were women (92.79%). The mean knowledge score was 7.22±3.53 (out of a possible maximum of 18), the mean attitude score was 23.91±5.16 (out of a possible maximum of 35) and the mean practice score was 25.84±5.08 (out of a possible maximum of 40). The knowledge scores correlated with the attitude (r=0.193, p<0.001) and practice (r=0.558, p<0.001) scores, while the attitude scores correlated with the practice scores (r=0.312, p<0.001). The path analysis revealed that knowledge had a direct influence on attitude (β=0.290, p=0.011) and practice (β=0.582, p=0.006). Attitude had a direct influence on practice (β=0.228, p=0.012). Knowledge also had an indirect influence on practice through its impact on attitude (β=0.066, p=0.005). Conclusion Parents' KAP scores were below the descriptive 70% sufficiency threshold, particularly for knowledge, suggesting unmet needs for clearer follow-up communication and family-centred neurodevelopmental education. Interventions should focus on strengthening family-centred education, clearer follow-up communication and parental engagement in neurodevelopmental monitoring and early intervention.
Background Autism spectrum disorder (ASD) affects approximately 25-50% of children with tuberous sclerosis complex (TSC). Early identification of ASD in this high-risk population is crucial for timely intervention but remains challenging due to the heterogeneous clinical presentation and complex interplay of genetic, neurological, and environmental factors. This study aimed to integrate longitudinal diffusion tensor imaging (DTI) metrics with early behavioral features using supervised learning algorithms to predict ASD outcomes at 36 months. Methods Data were obtained from the children enrolled in the TSC Autism Center of Excellence Research Network study. Four DTI metrics: axial diffusivity, fractional anisotropy, mean diffusivity, and radial diffusivity, were measured across 27 major white matter tracts at up to four irregular time points. To account for variability in acquisition timing, we developed a two-step data augmentation algorithm to interpolate each subject's data to standardized ages of 12, 24, and 36 months. In addition, 9 behavioral features from the ADOS-2 and ADI-R assessments at 24 months were included. Supervised learning algorithms were trained to predict ASD diagnosis at 36 months under two input settings. Results Performance of the supervised learning algorithms was evaluated with accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve as performance metrics. Regularized logistic regression models, least absolute shrinkage and selection operator and elastic net, demonstrated the most balanced overall performance across most evaluation metrics. Comparing input settings, Setting 1 (DTI at 24 months + behavioral features) achieved comparable or slightly improved performance relative to Setting 2 (DTI at 12 and 24 months + behavioral features) in predicting ASD diagnosis. Conclusion Integrating early neuroimaging and behavioral data suggests potential for prediction of ASD outcomes at 36 months in children with TSC. This multimodal machine learning framework highlights 24-month DTI and behavioral measures as key early biomarkers and demonstrates the effectiveness of regularized regression techniques for small-sample, heterogeneous clinical datasets.
Introduction Moyamoya disease (MMD) has a chronic nature which affects physical, cognitive, emotional challenges and relations with others reflecting on the quality of life (QoL) of affected children. Counseling is considered an important supportive intervention that may help children with their caregivers cope with the disease. Aim This study aims to evaluate the effect of counseling on quality of life among children with MMD and knowledge of their caregivers. Caregiver outcomes were limited to knowledge assessment. Methods A quasi-experimental single-group using paired t-test for pre-post study was conducted at a neurovascular outpatient clinic affiliated with a pediatric hospital in Egypt. A convenience sample of 30 children diagnosed with Moyamoya disease and their caregivers were included. Data were collected prior to counseling and after completion of counseling using a structured questionnaire assessing demographic characteristics and caregiver knowledge, as well as the Pediatric Quality of Life Inventory (PedsQL) for children. PedsQL was transformed to 0-100 scale where higher score means better quality of life. Results Before counseling, children demonstrated lower scores PedsQL across health and activities, child feelings, relations with others and school functions. Following the counseling, a statistically significant improvement in PedsQL scores was observed. In addition, caregiver knowledge significantly improved after counseling. A positive correlation was found between children's PedsQL scores and caregiver knowledge. Conclusion Counseling may be associated with improvements in the QoL of children with MMD and enhancement of caregiver knowledge. Further studies using controlled designs and larger samples are recommended to confirm these findings.
Introduction Pediatric femoral shaft fractures are one of the commonest injuries in early childhood and school-going children, with operative management increasing preferred in the age group of 6-13 years. The titanium elastic nailing system (TENS) is the most preferred modality in this age group, providing stable fixation and biological preservation; however, its effect on mechanical axis alignment and early functional outcome needs evaluation. In this study, we aim to analyze the effect of femur shaft fractures being managed by TENS on the mechanical axis of the lower limb and its effect on the functional outcome of the patients after a short immobilization period of 2 weeks. Materials and methods A prospective observational study was conducted at Baba Raghav Das Medical College, Gorakhpur between 2023 and 2025, including 32 children aged 6-13 years with femoral diaphyseal fracture undergoing TENS (excluding Gustillo-Anderson type IIIB/IIIC Injuries). Regular follow-up was done at 2, 6, and 12 weeks, and functional and radiological outcomes and mechanical alignment were recorded at 12 weeks using Flynn scoring criteria and orthoscanogram, respectively. Results Our study group had a mean age of 9.66 ± 2.25 years, with a higher male predilection (71.9%) and road traffic accident (43.8%) being the common mode of injury. We observed radiological union in all the patients with a mean union time of 10.88 ± 0.9 weeks, with no significant malalignment with mean medial proximal tibial angle and lateral distal femoral angle within an acceptable range, even after a short immobilization period. We observed a mean knee flexion of 112.7° ± 13.7° at 12 weeks follow-up, with 81.2% of patients having excellent and the remaining 18.8% having satisfactory outcome with no poor results. Conclusion TENS is a safe, minimally invasive, alignment-preserving modality which provides stable fixation, excellent short-term outcomes with minimal complications in 6-13 years age group, irrespective of age, gender, or fracture type.
