JAMA Pediatrics

Background Education outcomes predict life chances. However, poverty, ill-health and disability are barriers to achievement. We examined determinants of academic attainment of children with and without major congenital anomalies in state-funded mainstream schools at ages 11 and 16 (key stages [KS] 2 and 4). Methods and Findings Routinely collected electronic records for children born in Wales 01/01/1998-31/12/2007 until 31/12/2019 were linked in the Secure Anonymised Information Linkage (SAIL) Databank. Education outcomes were explored using logistic regression, adjusting for: anomalies, maternal and child deprivation, prescribing, hospitalisation, gestation length, childs sex, and special education needs (SEN) provision. Children with anomalies were less likely to achieve academic standards: however, attainment was more closely associated with affluence. At age 11, 81.87% (7167/8754) with and 93.80% (232,450/247,814) without anomalies passed (odds ratio [OR] 0.30, 95% confidence intervals [CI] 0.28-0.32). At age 16, 46.76% (2070/4427) with and 56.10% (69,732/124,300) without anomalies achieved 5 General Certificates of Secondary Education (GCSEs) at grades C-A* including English/Welsh, Maths and Science (EWMS) (OR 0.69, 0.65-0.73). Discrepancies narrowed in adjusted analyses, particularly when SEN provision was accounted: aOR 0.72 (0.66-0.78) at KS2, and aOR 0.93, (0.87-1.00) for 5 GCSEs C-A* with EWMS. These GCSEs were achieved by 29.65% (307/1034) children with anomalies and 38.42% (10,875/28,305) of unaffected children in the most deprived quintile{dagger}: in the most affluent quintile, figures were 67.57% (547/810) and 74.98% (16,978/22,644). Children with anomalies, receiving maximum SEN support, eligible for Free School Meals (FSM) were the least successful: 5/192 (2.6%) passed 5 GCSEs C-A* with EWMS, as did 37/354 (10.4%) ineligible for FSM. The strongest associations with these GCSEs were SEN statements (aOR 0.07, 0.06-0.07), FSM eligibility (aOR 0.39, 0.37-0.41), and epilepsy (aOR 0.60, 0.45-0.80). However, data were unavailable for 15-18% of children, mainly those educated outside mainstream schools, and some co-morbidities. Generalisation of findings to other countries rests with readers. Conclusions Many children with anomalies from affluent households succeeded. The children left behind lived with poverty and ill-health from congenital anomalies and/or epilepsy. SEN provision mitigated the impact of disadvantage, but poor children with anomalies were unlikely to succeed. {dagger}taking maternal Welsh Index of Multiple Deprivation (WIMD) 2014 at birth.

OBJECTIVE: Anthropometric data are critical in paediatric care, routinely assessed during clinical visits, and available in electronic health records (EHRs). We describe the feasibility of extracting anthropometric data from heterogeneous EHR systems of Swiss childrens hospitals, evaluate their availability and quality, and assess the cohorts representativeness of the general population. METHODS: In this multicentre study (SwissPedGrowth), we retrospectively collected EHRs from patients <20 years who visited hospitals in Basel, Bern, Geneva, Lausanne, Luzern, St. Gallen, or Zurich between 2017-2023. Sociodemographic, administrative, and clinical information from EHRs were provided in a standardized way by a paediatric national data stream (SwissPedHealth), including the Swiss Neighbourhood Index of Socioeconomic Position (Swiss-SEP). We counted anthropometric recordings per visit to describe availability and used a self-developed and an existing (growthcleanr) algorithm to investigate data quality. To assess representativeness, we compared sociodemographic characteristics between SwissPedGrowth and the general paediatric population in Switzerland, computed standardized differences (effect size: 0.2 small, 0.5 medium, 0.8 large), and weighted the study population to reduce differences. RESULTS: We included 477,531 patients and 2,171,633 hospital visits; 54% boys, 71% Swiss, mean Swiss-SEP 65 (SD: 11), and median age at visit 6.3 [IQR: 2.3, 11.8] years. Height recordings were available for 20% of the visits, weights for 43%, and head circumferences for 5%, with better availability for inpatient stays than outpatient or emergency visits. Combining the self-developed and existing algorithm, 4% of heights and 3% of weights were flagged as outliers and 29% of heights and 31% of weights as carried forward from previous visits or same day duplicates. Sociodemographic differences between SwissPedGrowth and the general population were small or small-to-medium and disappeared after weighting. CONCLUSION: SwissPedGrowth demonstrates feasibility of extracting high-quality anthropometric data for paediatric growth research, but challenges regarding completeness and harmonization of EHR data across Swiss hospitals remain.

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder (ADHD) includes recommending parent training in behavior management (PTBM) as first-line treatment. However, assessing guideline adherence through manual chart review is time-consuming and costly, limiting scalable and timely quality-of-care measurement. ObjectiveTo evaluate the accuracy and explainability of large language models (LLMs) in identifying PTBM recommendations in pediatric electronic health record (EHR) notes as a scalable alternative to manual chart review. Design, Setting, and ParticipantsThis retrospective cohort study was conducted in a community-based pediatric healthcare network in California consisting of 27 primary care clinics. The study cohort included children aged 4-6 years with [&ge;] 2 primary care visits between 2020-2024 and ICD-10 diagnoses of ADHD or ADHD symptoms (n=542 patients). Clinical notes from the first ADHD-related visit were included. A stratified subset of 122 notes, including all cases with model disagreement, was manually annotated to assess model performance in identifying PTBM recommendations and rank model explanations. ExposuresAssessment and plan sections of clinical notes were analyzed using three generative large language models (Claude-3.5, GPT-4o, and LLaMA-3.3-70B) to identify the presence of PTBM recommendations and generate explanatory rationales and documentation evidence. Main Outcomes and MeasuresModel performance in identifying PTBM recommendations (measured by sensitivity, positive predictive value (PPV), and F1-score) and qualitative explainability ratings of model-generated rationales (based on the QUEST framework). ResultsAll three models demonstrated high performance compared to expert chart review. Claude-3.5 showed balanced performance (sensitivity=0.89, PPV=0.95, and F1-score=0.92) and ranked highest in explainability. LLaMA3.3-70B achieved sensitivity=0.91, PPV=0.89, and F1-score=0.90, ranking second for explainability. GPT-4o had the highest PPV [0.97] but lowest sensitivity [0.82], with an F1-score of 0.89 and the lowest explainability ranking. Based on classifications from the best-performing model, Claude-3.5, 26.4% (143/542) of patients had documented PTBM recommendations at their first ADHD-related visit. Conclusions and RelevanceLLMs can accurately extract guideline-concordant clinician recommendations for non-pharmacological ADHD treatment from unstructured clinical notes while providing clear explanations and supporting evidence. Evaluating model explainability as part of LLM implementation for medical chart review tasks can promote transparent and scalable solutions for quality-of-care measurement.

ImportanceWhole genome sequencing (WGS) is increasingly used to diagnose severely ill children, yet the long-term impact of a genetic diagnosis on healthcare utilization and resource allocation remains poorly understood. ObjectiveTo determine the influence of a genetic diagnosis via WGS on long-term healthcare utilization metrics in severely ill children. DesignA retrospective cohort study using data from the Next Generation Children study (2016-2020) with record linkage and analysis of primary care records conducted between 2022 and 2024. SettingA multicenter study involving primary care and hospital records linked via the UK National Health Research Institute (NIHR) Rare Disease Bioresource, Cambridge, UK. ParticipantsA referred sample of 270 severely ill children who underwent WGS. Exposure(s)Receipt of a genetic diagnosis (87/270; 32%) compared to those who remained undiagnosed (183/270; 68%) following WGS. Main Outcome(s) and Measure(s)Comparison of 36 healthcare utilization parameters, including hospitalizations, primary care prescriptions, and diagnostic tests. ResultsAmong the 270 children analyzed, those receiving a genetic diagnosis (n=87) exhibited significantly higher overall healthcare utilization compared to undiagnosed peers (n=183). This included increased hospital admissions and outpatient visits, particularly for neurodevelopmental and seizure-related conditions. Diagnosed children received a higher volume of neurological, gastrointestinal, and nutritional prescriptions. The most pronounced differences in utilization were observed in children initially diagnosed in neonatal (NICU) or pediatric (PICU) intensive care settings. While genetic diagnosis was not associated with reduced healthcare costs during the study period, it was linked to more targeted, condition-specific medical care. Conclusions and RelevanceWGS diagnosis facilitates the integration of specialist care and the alignment of healthcare resources with the specific needs of children with complex disorders. These findings suggest that while costs may not decrease immediately, a diagnosis enables more precise and targeted clinical management. Key PointsO_ST_ABSQuestionC_ST_ABSDoes a genetic diagnosis through whole genome sequencing influence long-term healthcare utilization in severely ill children? FindingsIn this cohort study of 270 children, those who received a genetic diagnosis demonstrated significantly greater overall healthcare utilization, including more hospitalizations and targeted prescriptions, compared with undiagnosed children. MeaningA genetic diagnosis facilitates the integration of specialized, condition-specific care, helping to align healthcare resources with the individual needs of children with complex disorders.

Background Although an expansive body of evidence exists on children's mental health during the COVID-19 pandemic, it is largely restricted to the early phases and lockdowns. This study examines longitudinal changes in child and youth mental health symptoms across two years of the COVID-19 pandemic, with data collection strategically timed to capture variability in pandemic restrictions. Methods A population-based longitudinal study of 1,261 children and youth aged 4-17 years followed prospectively from January 2021 to December 2022, with five waves of data collected in Ontario, Canada. Latent growth curve modelling was used to estimate trajectories of parent-reported mental health symptoms and identify baseline and time-varying covariates associated with variable trajectories. Findings Mental health symptoms were elevated and stable during lockdowns, followed by significant reductions as pandemic restrictions loosened, particularly for oppositional defiant and inattention/hyperactivity symptoms compared to internalizing symptoms. Children without pre-existing clinician diagnosed physical, mental or neurodevelopmental conditions and those not in lockdown at baseline demonstrated relative increases in mental health symptoms during lockdowns; and girls, compared to boys, demonstrated smaller reductions in internalizing symptoms as restrictions loosened. Concurrent and lagged associations between parental distress and children's mental health symptoms varied across the pandemic. Interpretation Variation in symptom trajectories by mental health domain, gender, pandemic restrictions and pre-existing diagnosed conditions underscores the need for tailored, equity-informed pandemic planning and response. Policies designed to optimize the balance between the need to reduce viral community transmission whilst limiting pandemic lockdowns may mitigate adverse impacts on child and youth mental health. Funding Ontario Ministry of Health

Despite autism's prominent genetic etiology and early-life origins, parsing genetic effects contributing to the condition into those that operate directly (via allelic transmission to offspring) vs. indirectly (via influencing prenatal environment) remains challenging. We examined this using a novel design leveraging 3-generation family linkage in Danish national registers. The cohort included all children born in Denmark from 1998-2015 and their relatives identified through 3-generation family linkage. The analytic sample comprised full maternal cousin pairs, including parallel (children of mother's sister) and cross cousins (children of mother's brother). Exposures were diagnoses in the index mother previously associated with offspring autism; the outcome was autism diagnosis in cousins of the index child. We used Cox proportional hazards models to estimate associations separately in parallel and cross cousins, followed by comparisons of these hazard ratios to infer mechanisms. Several maternal diagnoses (e.g., postpartum hemorrhage, personality disorders, epilepsy) were associated with autism in both parallel and cross cousins, consistent with shared direct genetic effects. Other conditions (e.g., false labor, recurrent major depressive disorder, other anxiety disorders, systemic connective tissue involvement) showed stronger associations in parallel than cross cousins, supporting additional indirect genetic effects operating through the prenatal environment. Adjustment for the same diagnosis in the cousin's own mother did not substantially change estimates, providing no evidence for an additional role of non-genetic mechanisms associated with the diagnosis. These findings suggest that both direct and indirect genetic effects contribute to observed links between maternal health and offspring autism, highlighting etiologic heterogeneity and highlighting a registry-based family design to separate these pathways without genetic data.

Young people are increasingly remaining in the parental home for longer - a trend associated with poorer mental health. There is little evidence on this transition for young people with disability. We used three waves of the Australian Census Longitudinal Dataset, a 5% sample of linked Census records. Two analyses compared transitions between 2011-2016 and 2016-2021 among people 15-34y living with parents at baseline with complete data on disability and housing. The proportion of people no longer living with parents at follow-up was calculated, comparing people with and without disability, along with absolute and relative inequalities. Young people with disability were half as likely to leave the parental home as their peers without disability. Inequalities were greatest for people 25-29y (relative difference 0.41 (95%CI 0.36-0.45), living outside major cities (0.48, 0.44-0.52), or with higher income (0.53 (0.47-0.59). Patterns were consistent over time. Targeted supports are needed to enable independent living. Points of interestO_LIWe found that less people with disability leave the parental home than people without disability C_LIO_LIWe also found the gap between people with and without disability was biggest outside major cities. C_LIO_LIThis may mean people with disability in rural, regional and remote areas find it more difficult to move out of home C_LIO_LIBetter housing and income supports are needed to help young people with disability live in the way they choose C_LI

BackgroundAn upsurge in Streptococcus pyogenes infections 2022-2023 highlighted potential benefits of point-of-care tests (POCT) to support clinical pathways, prevent outbreaks, and optimise antibiotic use. ObjectivesWe conducted a pilot research study in a west London paediatric emergency department (ED) to determine whether a molecular POCT had potential to alter management in children who were also having a conventional throat swab taken for culture. MethodsChildren <16 years presenting to ED who had a throat swab requested by a clinician were invited to have a second swab taken for research purposes only. Clinical management was unaffected by the research swab result, which was processed using a molecular POCT that was not approved for use in the host NHS Trust. ResultsPrevalence of streptococcal infection was low during the study (May 2023-June 2025); swab positivity in symptomatic children was 12.8% (6/47). Overall, 38/49 (77.6%) participants who had throat swabs received antibiotics. Of those children recommended to receive antibiotics, 29/38 (76.3%) had a negative POCT. Mean time to reporting of positive throat swab culture results was 3.67 days (range 3-5 days) leading to occasional delay in treatment, although POCT identified positive results within minutes. ConclusionAntibiotic use was frequent and could be avoided or stopped by use of a rule out POCT in over three-quarters of children in the ED, if suspicion of S. pyogenes is the main driver for prescribing. POCT were easy to process and produced immediate results compared with culture, in theory enabling timely decision-making and avoiding treatment delay.

BackgroundThe epidemiology of suspected pediatric meningoencephalitis has shifted in the era of conjugate vaccines and multiplex PCR diagnostics, with viral pathogens now predominating over bacterial causes. Updated epidemiologic data are essential to adapt diagnostic and therapeutic algorithms to current clinical practice. MethodsThis retrospective single-center study included children and adolescents <18 years who underwent lumbar puncture with cerebrospinal fluid multiplex PCR for suspected central nervous system infection at a tertiary-care pediatric hospital in Germany between 2016 and 2024. Clinical, laboratory, and outcome data were extracted from electronic medical records. Cerebrospinal fluid was analyzed using the BioFire(R) FilmArray(R) Meningitis/Encephalitis Panel. Statistical analyses included descriptive statistics, nonparametric group comparisons, receiver operating characteristic analyses. ResultsAmong 1,198 included children, definite bacterial meningitis was diagnosed in 13 (1.1%), definite viral meningitis in 80 (6.7%), aseptic meningitis of unknown etiology in 131 (11.0%), confirmed/probable encephalitis in 53 (4.4%), and possible encephalitis in 34 (2.8%). Bacterial meningitis accounted for 5.8% of all meningitis cases. A causative pathogen was identified in all bacterial meningitis cases, most commonly Streptococcus pneumoniae (n = 7). Enterovirus (n = 52) and parechovirus (n = 9) predominated in viral meningitis, whereas an infectious etiology was identified in only 13 of 53 confirmed/probable encephalitis cases. The Bacterial Meningitis Score showed a sensitivity of 80.0% and a specificity of 57.6%. The recently published UK-ChiMES-pre- and post-lumbar puncture scores demonstrated sensitivities of 84.6% and 76.9% and specificities of 86.3% and 92.7%, respectively. DiscussionBacterial meningitis was rare in this contemporary cohort, while viral and etiologically unresolved infections predominated despite routine multiplex PCR diagnostics. Clinical prediction scores supported risk stratification, with the UK-ChiMES-pre-lumbar puncture score showing the most favorable balance between sensitivity and specificity and potential to guide diagnostic decisions and antiinfective therapy.

BackgroundConversational AI safety systems are primarily evaluated using message-level content monitoring, which assesses inputs and outputs in isolation. This message-by-message approach can miss interaction-level risks that emerge over extended conversations, including patterns discussed in reports of "AI psychosis." Critically, by the time users express overt psychosis-spectrum content, opportunities for intervention may be limited. ObjectiveWe investigated whether LLM responses gradually expand and connect interpretations beyond the users original concerns, a process we term structural drift. We also tested whether this drift can be detected early and automatically. MethodsWe developed an automated, LLM-adapted rubric-based prompt for seven domains of anomalous (psychosis-spectrum) experience, derived from phenomenological psychiatry to capture subtle shifts in subjective interpretation. In Part 1, we evaluated the rubric using gold-standard text excerpts (N = 484) adapted from clinically validated qualitative instruments. In Part 2, we analyzed 1,290 user-LLM response exchanges from 7 dialogues, using 3 different LLMs (5 repeats each), to measure (i) domain amplification (increasing score within a domain) and (ii) domain expansion (new domains appearing over time). ResultsAutomated scoring showed strong agreement with gold-standard excerpts (domain accuracy 82.7-98.9%; exact 0-3 agreement 63.6-82.7%). Across dialogues, we observed significant amplification in four domains (p < .05; d = 0.14-0.46) and domain expansion in 83.8% of dialogues (88/105; p < .001). ConclusionsAI responses can systematically expand and intensify users descriptions beyond their initial input. Taken together with the predictive-processing accounts of psychosis, the exposure itself may reinforce maladaptive inferences. Because drift is detectable from ordinary dialogue without clinical-style probing, this structural drift detection may support scalable, real-time monitoring for emerging risks before overt escalation.

BackgroundNewborns requiring inpatient care, particularly small and sick newborns (SSNBs), face high risk of mortality. Newborns referred from other facilities may experience worse outcomes than those born and managed within the same hospital (inborn newborns). Understanding factors contributing to this disparity in outcomes could support efforts to scale-up care and accelerate progress towards achieving Sustainable Development Goals target 3.2. MethodsData on 130,773 newborns admitted to 13 hospitals implementing with NEST360 in Kenya were obtained from the Neonatal Inpatient Dataset, between January 2019-October 2024. We described characteristics and primary diagnoses. Logistic regression was used to evaluate factors associated with mortality. ResultsAmong admissions, 114,084 (87.2%) were inborn and 16,689 (12.8%) referred. Referred newborns were more likely to be extremely preterm (6.1% vs 3.1%), have extremely low birthweight (<1,000g) (4.6% vs 2.6%) and present with respiratory distress (26.2% vs 15.0%) and hypoxia (23.2% vs 15.3%) compared to those inborn. Only 59.6% of referred newborns were admitted on first day of life compared to 80.2% inborn newborns. Unadjusted mortality among referred newborns was 29.0% compared to 11.3% in those inborn. Risk factors associated with mortality among referred newborns included being extremely low birthweight (odds ratio [OR] 13.57, 95% CI 11.19-16.44), respiratory distress (OR 4.07, 95% CI 3.77-4.39), and congenital anomalies (OR 1.66, 95% CI 1.41-1.95). Prematurity and intrapartum-related complications were also associated with increased odds of death. In multivariable analysis, being referred remained strongly associated with mortality (adjusted OR [aOR] 2.54, 95% CI 2.39-2.71). ConclusionReferred newborns had nearly three times higher odds of mortality compared to those inborn. This may highlight referral selection bias amongst this group and could also be related to inadequate pre-referral stabilisation, unsafe neonatal transportation and admission delays. If successfully implemented, a strong hub-and-spoke approach may improve care at lower levels of care and decongest receiving facilities. Overall, improving quality of care across the continuum of referral process is a cornerstone in strategies to reduce neonatal mortality towards attainment of national and global newborn survival targets. KEY FINDINGSO_ST_ABS1. WHAT WAS KNOWN?C_ST_ABSO_LINeonatal mortality remains high in sub-Saharan Africa and newborns referred from other health facilities may experience poorer outcomes than those born and managed within the same hospital. C_LIO_LIThere is limited evidence on morbidity and mortality outcomes among inborn and referred newborns. This is important to inform specialised newborn care and targeted improvements in referral. C_LI 2. WHAT WAS DONE THAT IS NEW?O_LIThis study analysed routinely collected clinical data on 130,773 newborns admitted to 13 hospitals implementing with NEST360 in Kenya between 2019 and 2024. C_LIO_LIDiagnoses outcomes and neonatal characteristics were described and compared between inborn and referred newborns. Factors associated with neonatal mortality were also examined using logistic regression analysis. C_LI 3. WHAT WAS FOUND?O_LIReferred newborns had higher unadjusted mortality rate than inborn newborns (29.0% vs 11.3%; p<0.001), with 3 times higher odds of death in univariable logistic regression analysis (OR 3.20, 95% CI 3.08-3.33). C_LIO_LIReferred newborns were more clinically vulnerable at admission and had higher proportions of extreme prematurity (6.1% vs 3.1%), very preterm birth (14.0% vs 8.6%), and extremely low birthweight (4.6% vs 2.6%). Among both groups, key risk factors associated with mortality included birthweight, gestational age, respiratory distress, hypothermia, and clinical diagnoses. C_LIO_LIAmong referred newborns some of the risk factors associated with mortality included being extremely low birthweight (OR 13.57, 95% CI 11.19-16.44), respiratory distress (OR 4.07, 95% CI 3.77-4.39), congenital anomalies (OR 1.66, 95% CI 1.41-1.95), and intrapartum-related complications (OR 1.35, 95% CI 1.20-1.52). C_LI 4. WHAT NEXT?O_LIStrengthen neonatal referral systems through clearer referral criteria, improved pre-referral stabilisation, better neonatal transport, and prompt triage on arrival at receiving hospitals. Routine clinical data should be used to monitor referral processes and outcomes and to guide continuous quality improvement. C_LIO_LIFurther research is needed to capture referral to admission time, transport characteristics, and quality of pre-referral stabilisation. Linking neonatal admission data with maternal records and assessing outcomes beyond hospital discharge would also improve understanding of referral pathways and long-term outcomes. C_LI

BackgroundHome disciplinary practices shape childrens health and development. Yet, comprehensive, up-to-date global evidence on their levels, trends, and socioeconomic and regional inequalities remains limited. This study provides the first global prevalence estimates of both violent and non-violent forms of discipline, examining regional disparities, variations by child and family characteristics, and changes over time. MethodsWe drew from 176 nationally-representative Multiple Indicator Cluster Surveys and Demographic and Health Surveys, collected between 2005 and 2023 across 83 low- and middle-income and 5 high-income countries (N= 1,544,000 1-14y-olds). We estimated weighted prevalence estimates for all types of discipline (exclusively or only non-violent, physical and severe physical punishment, emotional violence, exclusively or only physical punishment, exclusively or only emotional violence, both physical and emotional violence). Disparities by child age, sex, residence, maternal education, household wealth, and world regions were computed. We also assessed changes over time for countries with multiple surveys. ResultsOnly 19.1% of children experienced exclusively non-violent discipline; 55.0% and 12.7% physical and severe physical punishment; and 64.0% emotional violence. Violent discipline was highest among 6-9y-olds, in Sub-Saharan Africa, and in poorer households. Sex differences were more limited. Use of only non-violent discipline slightly increased in 26 countries, while physical and emotional violence decreased in 33 and 31 countries, respectively. Yet, in some countries, violent discipline increased over time. ConclusionsDespite policy efforts to increase its use, exclusive non-violent discipline remains low, and violent methods are widespread. Targeted and context-specific interventions for specific age groups and poorer households curb violence exposure at home.

Introduction Social media is a central part of young people's lives, yet research on its mental health effects remains mixed. We posit that these inconsistencies stem in part from treating youth as a homogeneous group, obscuring distinct behavioral patterns associated with divergent mental health and wellbeing trajectories. Objectives This study aimed to: (1) explore heterogeneity in social media engagement styles among U.S. youth aged 15-24; and (2) examine how these engagement styles are embedded within a broader system of mental health, wellbeing, emotional regulation, belonging, family and neighborhood context, and stress and adversity. Methods Data were drawn from a 2024 nationally representative cross-sectional survey of 2,563 U.S. youth, conducted as part of the Youth Mental Health Tracker initiative. We employed unsupervised clustering to identify five distinct social media engagement profiles. Subsequently, we used Bayesian network-based causal discovery to examine (a) upstream factors that emerge as drivers of engagement styles and (b) downstream outcomes influenced by profile membership in the learned system. Results Five profiles were identified: the Perpetually Plugged-In (31.3%), characterized by near-constant multifaceted social media use, for both positive and negative purposes across multiple domains of life; the Burned-Out Browsers (21.9%), with high exposure to negative and comparison-based content with frequent attempts to disengage; the Practical Navigators (20.7%) who engage in structured, goal-oriented use focused on learning, hobbies, and maintaining connections; the Positive Engagers (13.6%) with high social and identity-driven engagement; and the Light Touch Users (12.5%) who have low overall engagement and limited reliance on social media for connection, identity, or support. Causal analyses revealed that the Perpetually Plugged-In and Burned-Out Browsers had the worst mental health and wellbeing, with their engagement driven by different reasons. While both engagement profiles were influenced by similar psychosocial risk factors, they were distinguished by their dominant drivers: contemporaneous social stressors (bullying, discrimination, and emotional dysregulation) for Perpetually Plugged-In youth, versus adverse childhood experiences for Burned-Out Browsers. In contrast, Positive Engagers reported high social media engagement alongside the highest levels of social wellbeing, using social media for identity exploration and social support within a context of low cumulative stress and adversity. Conclusions Findings suggest that youth social media risk is not driven by intensity of use alone, but by the interaction between engagement style and offline emotional and social conditions. Policies focused solely on restricting access risk overlooking these differences and may inadvertently sever important sources of connection for many youth. Strategies should identify experiential risk signals while strengthening supportive contexts that enable healthier engagement. Overall, youth social media use is best understood as part of a broader psychosocial system, and recognizing this heterogeneity is essential for designing more targeted, equitable, and evidence-based interventions.

PurposeWhile genomic testing is integral to pediatric inborn errors of immunity (IEI) care, few studies have examined strategies to support its optimal delivery. This study aimed to characterize a pediatric IEI cohort and assess the impact of implementing a mainstream model-of-care (MoC). Materials/MethodsComprehensive chart audit was conducted for patients ([&le;]18y) who received IEI genomic testing in Queensland, Australia, from 2017-2025. Descriptive analyses captured demographic and clinical characteristics, genomic testing and results, and management outcomes. Inferential analyses assessed changes in genomic practices pre-MoC (<2021) and post-MoC ([&ge;]2021). Results322 patients met eligibility criteria (n=481 genomic test). Diagnostic yield (27.6%) varied by testing indication, with the highest rate among phagocytic defects (n=4/4;100%) and severe combined immunodeficiency (n=8/10;80%). Very-early-onset inflammatory bowel disease had the lowest diagnostic yield (n=3/68;4.4%), prompting changes to testing criteria. Molecular diagnosis resulted in management changes for 90.5% patients. Genomic testing was widely used pre-MoC (n=251 genomic tests). All outcomes significantly improved pre-and post-MoC (p<0.05): duplicate testing decreased (13.9% to 0%); variants of uncertain significance reduced (37.7% to 7.1%); informed consent documentation increased (70.5% to 88.4%); and diagnostic yield increased (16.2% to 27.4%). ConclusionTargeted interventions are needed to support delivery of genomic testing and strengthen service effectiveness.

Previous research links Adverse Childhood Experiences (ACEs) with problem gambling, but most studies rely on retrospective reporting and focus narrowly on maltreatment, overlooking adversities such as parental mental health issues. Using data on 3794 young adults in the Avon Longitudinal Study of Parents and Children, we examined longitudinal associations between 10 prospectively measured ACEs (individually and cumulatively), and moderate-risk/problem gambling (Problem Gambling Severity Index >=3) at ages 17, 20 and 24, adjusted for socioeconomic and other background factors. Population attributable fractions (PAFs) estimated proportions of cases potentially attributable to ACEs. Most ACEs were associated with higher odds of moderate-risk/problem gambling across ages (24/30 estimates) after adjustment, though effect sizes were generally small (median adjusted odds ratio [aOR] 1.31, interquartile range 1.24-1.59), and confidence intervals (CIs) wide. Sexual abuse showed the strongest association (aORs 2.4-4.2, CIs 0.5-10.5), while bullying and parental conviction were associated at ages 17 and 20 only, parental separation age 24 only. Evidence for a dose-response relationship was weak. PAFs suggested ACEs accounted for up to 12% of moderate-risk/problem gambling cases. These findings highlight potential impacts of ACEs on later gambling behaviour, but imprecise estimates suggest findings should be interpreted cautiously and strengthened through larger datasets and meta-analyses.

Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) frequently co-occur with overlapping symptoms. We investigated whether automated behavioral analysis during a clinician-child interview can identify distinct, objective features of the two disorders. Analyzing audio-video recordings of 2,341 youths (ages 5-22) in a broad community sample, multivariate models revealed that language difficulties often attributed to ADHD are primarily explained by age, cognitive ability, or co-occurring ASD. Increased motor activity specifically marked hyperactive-impulsive ADHD, but not ASD or inattentive ADHD. ASD was uniquely characterized by divergent narrative production and perspective-taking, alongside a distinct vocal profile of higher pitch and intensity, despite structurally intact language. While these digital behavioral measures correlate with most diagnostic categories and age, the joint analysis effectively separates the effects of ASD from ADHD. These findings show that scalable digital assessment from recorded clinical interviews can disentangle overlapping ASD and ADHD diagnoses into domain-specific behavioral signatures.

BackgroundCaregiver skills training programmes are well-researched in the fields of autism and intellectual disability, but children with motor disorders such as cerebral palsy remain underrepresented despite their high prevalence. These caregivers face unique challenges, and group programmes may provide family-centred care through information provision, problem-solving and peer support. MethodsSystematic searches of five databases (CINAHL, Medline, Embase, PsychINFO and ERIC) were conducted for interventional studies of group programmes aiming to improve the skills, confidence and wellbeing of caregivers of children with neurodisability focusing on motor disorders. Data were extracted on study and intervention characteristics and outcomes. Risk of bias was assessed, effect sizes calculated, and results summarised descriptively using forest plots. ResultsOf 6093 studies identified, 21 studies met inclusion criteria (nine randomised-controlled trials, two quasi-experimental and ten pre-post designs). Most reported on programmes developed in resource-constrained settings and addressed caregiver skills, coping strategies, or health-promoting behaviours. Outcomes were grouped according to caregiver wellbeing, caregiver skills and confidence, and social support and family functioning. Child outcomes were reported separately. Most caregiver outcomes showed positive effects, though most studies had high risk of bias due to self-reported outcomes and lack of blinding of intervention allocation and outcome measurement. DiscussionGroup-based training programmes show promise for improving caregiver skills and wellbeing. Clinicians and stakeholders in high-income countries may learn from these innovations in low-resource settings. Future research should strengthen protocol reporting, address attrition, control for confounding factors, and establish a core set of caregiver-reported outcomes to better capture programme impact. Systematic review registrationPROSPERO registration CRD42024595002

BackgroundOrganization, time management, and planning (OTMP) difficulties are associated with academic underachievement. OTMP skills training programs are effective in reducing OTMP deficits and improving academic performance. A randomized controlled trial of Homework, Organization, and Planning Skills (HOPS) for students ages 11-14 (1) found it to be effective with medium to large effects. In that study, HOPS was provided by counselors employed by the research team. This study is a replication examining HOPS under more authentic conditions when providers are employed by schools serving enrolled students. The primary aim is to evaluate HOPS offered by school providers in relation to treatment-as-usual/waitlist (TAU/WL). To respond to limited school resources post-COVID-19, HOPS is also provided by research team members, creating the opportunity to replicate the findings from the prior trial (1) and explore differential effectiveness when HOPS is implemented by school vs. research providers. MethodsStudents in about 30 schools serving students ages 11-14 will be enrolled. Schools are randomly assigned to HOPS vs. TAU/WL on a 2:1 ratio. Students assigned to HOPS schools are randomly assigned to a school vs. research provider on a 1:1 basis. Providers receive two hours of training and additional assistance on request. Child outcomes related to OTMP skills, homework, and academic performance are assessed at post-treatment, 6-month (from baseline) follow-up, and 12-month follow-up. HOPS sessions are video recorded for fidelity coding. Potential effect modifiers include student ADHD, oppositional defiant, and internalizing symptoms, and family socioeconomic level. Analyses will use mixed effects modeling. The goal of the study is to enroll 135 participants, yielding a minimal detectable effect size of 0.50, within the expected range based on prior research. DiscussionThe study is unique in examining intervention implementation and effectiveness when intervention is provided under authentic practice conditions. Trial RegistrationThis study was registered with clinicaltrials.gov (NCT04465708).

UK-based quantitative research on the health and education outcomes of Unaccompanied Asylum-Seeking Children (UASC) remains limited, especially at national level. Linked administrative data provide an unprecedented opportunity to study these outcomes among UASC. This paper lays a foundation for further research, particularly examining the influence of socio-demographic, legal and environmental factors on UASCs health and educational outcomes. We described the UASC population with a first recorded episode of local authority care between 1st April 2005 and 31st March 2021 in ECHILD, which gathers national records for England, by age, gender, ethnicity, region, and placement type. We calculated linkage rates between the social care and educational dataset, estimating how many UASC were recorded as being enrolled in state-funded schools. We also assessed how many of those linked to the school dataset was linked to National Health Service (NHS) datasets. Finally, we explored how linkage rates between social care, education, and NHS datasets vary by socio-demographic factors and placement type. There were 37,170 UASC recorded in the ECHILD of which 32,570 (88%) were male and 24,290 (65%) aged 16 - 17 years. We found 7,740 (21%) UASC recorded as being enrolled in state funded schools, of whom 6,690 (88%) were also linked to NHS data. The linkage rate for UASC in the social care to health datasets was therefore 19%. Of those 16-17 years at entry in social care, 4% (1,060/24,290) were recorded as enrolled in school compared to 50% (6,390/12,880) under 16 years. Linkage to the school, and subsequently to the NHS dataset, wholly depends on enrolled state-funded education, excluding College and Sixth-form education. Despite this limitation, we characterised a national cohort of 6,890 UASC in England whose social care, education, and health outcomes can be examined.

Mechanistic understanding and biomarkers of gonadotropin-releasing hormone antagonist treatment effect in paedophilic disorder are absent but may enhance outcomes and reduce sexual-offending risk. 52 help-seeking self-referred Swedish men with paedophilic disorder enrolled in a double-blinded, placebo-controlled, randomized clinical trial. Participants underwent task-based fMRI before, and two weeks after, subcutaneous injection of 120mg of degarelix or equal volume of placebo. fMRI blood-oxygen-level-dependent activation was compared between child and adult (child>adult) stimuli in task-derived regions of interest. Primary outcome was within region-of-interest child>adult activation change, whereas secondary outcomes correlated region-of-interest child>adult activation change to change in clinical measurements of risk, paedophilic interest, sexual preoccupation, hyper- and hyposexuality. 19 degarelix and 22 placebo participants had sufficient fMRI data quality. Reductions in paedophilic interest were strongly correlated with increased child>adult cerebellar (vermis) region-of-interest activation following degarelix (r=-0.740, p<0.001) but not placebo (r=0.183, p=0.41; between-group correlation coefficient z=3.347, p<0.001). Treatment did not significantly change child>adult region-of-interest activity. Post hoc analysis indicated that baseline autism symptoms correlated with degarelix-induced changes in paedophilic interest (r=0.717, p<0.001; between-group correlation coefficient z=2.958, p=0.003) and cerebellar activation (r=-0.581, p=0.01; between-group correlation coefficient z=-1.930, p=0.05). Increased child>adult cerebellar activation was associated with degarelix-induced reductions of paedophilic interest, suggesting cerebellar activity as mechanistically important to, and a prospective biomarker of, degarelix treatment effect. Additionally, autism symptoms may inform treatment prediction. Together, these findings have mechanistic and clinical implications for degarelix treatment of paedophilic disorder. EU clinical trials register identifier: 2014-000647-32 https://www.clinicaltrialsregister.eu/ctr-search/trial/2014-000647-32/SE, registered on 05/06/2014.