Excessive screen time is associated with developmental, behavioral, and health risks in children. Despite growing concern, no validated tool currently exists in any language to identify screen overexposure in routine clinical practice.To validate a novel screening tool for detecting screen overexposure among children and adolescents aged 0 to 18 during primary care consultations. The primary outcome was the tool’s diagnostic accuracy in identifying screen overexposure, defined by physicians' clinical assessment. Secondary outcomes included internal and external validity, user acceptability, and identification of risk factors.This was a prospective, multicenter, cross-sectional validation study conducted between December 2023 and March 2024. A total of 439 children aged 0 to 18 years were recruited by 74 primary care physicians and 3 child health institutions in France. The tool was originally developed during a previous thesis through a systematic literature review and Delphi consensus process.A threshold score of 6 out of 21 was identified as the optimal cutoff for screen overexposure, yielding a sensitivity of 96% and specificity of 74.1%. The tool’s total score correlated strongly with clinician assessment (AUC = 0.925; 95% CI, 0.899–0.951; p < .001). Age-specific thresholds were established, and weighted scoring was proposed for each age group. Physicians rated the tool as easy to use, well integrated into clinical practice, and effective in initiating discussions with families. Known risk and protective factors (e.g., maternal education, screen rules, outdoor space) were confirmed.In the absence of a gold standard, the score was created by expert consensus. The combination of the two sub-scores, usage (where, when, how much, how?) and warning signs, makes it possible to refine the identification of at-risk situations.This study validates the first screening tool for screen overexposure in children, designed for use in everyday primary care settings. The tool meets a widely recognized clinical need and provides a practical method to support prevention, early detection, and family education in pediatric consultations.

Adverse Childhood Experiences (ACEs) are stresses that children may suffer while growing up. In Europe 4 in 10 adults have suffered ACEs as children and the health burden is estimated at 24.6 million Disability-Adjusted Life Years (DALYs) in Europe alone.The Center for Disease Control (CDC), the World Health Organization (WHO), and others have put out guidelines for prevention and treatment of ACEs in order to decrease the lifetime morbidity from these trauma.1) To review the important scientific literature on ACEs. 2) To identify simple interventions that can be implemented in the primary care setting to help patients with disability due to ACEs.Books, journal articles, lay material, and internet searches were done to collate the important principles of ACEs and treatment as pertains to primary care providers (PCPs).WHO strategies include 1) policy and legislation, 2) strengthening families, 3) education and life skills, 4) support services, and 5) muti-component programs. Education and life skills have been shown to be particularly helpful. One university, Penn State, USA has over 20 years’ experience in teaching resilience to at-risk youth, showing success in helping youth cope with stress and decrease anxiety.ACE’s and its disabling effects can be diminished in our society. Both primary prevention and secondary prevention are effective in decreasing ACEs and its associated disability. Primary prevention can be achieved by enhancing social services to families and parents. Secondary prevention can be achieved by teaching resiliency to young people.ACEs and the disability of ACEs are staggeringly high and show no signs of retreat. PCPs who interact with patients on a regular basis are in an ideal position to identify and refer patients who suffer from ACEs for appropriate mitigating treatment. Together as first line responders we can help our patients who have suffered trauma, while helping create programs to prevent future generations from the same struggles.

Screen exposure has become increasingly pervasive in childhood, with growing evidence linking excessive use to behavioral difficulties, sleep disturbances, and adverse physical health outcomes.To assess, in children aged 5 to 10 years, the relationship between daily screen exposure and indicators of behavior, sleep quality, and body weight.A cross-sectional observational study is being conducted from  september 2025- december 2026. The sample expects to include up to  200 children aged 5–10 years, recruited through elementary schools. Parents or primary caregivers complete an anonymous questionnaire including sociodemographic data, average daily screen time (weekdays and weekends), the Strengths and Difficulties Questionnaire (SDQ), an adapted Sleep Quality Scale, and parent-reported weight and height. Descriptive statistics were performed, and correlations were calculated between screen time, behavior, sleep variables, and body weight.The results are preliminary. To date, 52 children have been included in the analysis. A preliminary index of screen-related behaviors was constructed (10 Likert-type items, α = 0.90), along with a preliminary index of sleep problems (25 items, α = 0.84). Among the 39 children with available weight data, no significant association was observed between weight and the behavior index (Spearman ρ = 0.02; p = 0.91), and only a trend toward a negative association was noted between weight and sleep problems (ρ = –0.31; p = 0.056). In contrast, a moderate and statistically significant positive correlation was found between sleep problems and screen-related behaviors in the current sample (ρ = 0.46; p < 0.001), indicating that children showing greater sleep disturbance also tend to present more dysregulated screen-related behaviors. Further results will be updated as data collection progresses.These preliminary findings reinforce existing evidence linking excessive screen time to behavioral and sleep dysregulation. The correlation with BMI is modest, further responses are needed to draw deeper conclusions.Provisional results appear to indicate that screen time among children aged 5–10 years is above recommended levels and is associated with behavioral difficulties, disrupted sleep patterns, and a tendency toward higher BMI. Once finished this study aims to highlight the need for ongoing clinical monitoring and parental guidance on healthy technology use during childhood.

Early language skills are critical for cognitive and socioemotional development and are routinely monitored in primary care. The COVID-19 pandemic exacerbated vulnerabilities in early childhood, with recent estimates from a middle-income Latin American country indicating that developmental delay has risen to approximately 28%. Despite this alarming increase, there is limited population-based evidence identifying the determinants of language delay in young children in the region. This study aims to address this evidence gap.To estimate the prevalence of language delay among children aged 12–42 months and to identify structural, underlying, and proximal determinants associated with delay using nationally representative data from a 2018 health and nutrition survey.A cross-sectional analytical design was applied to data from 8,446 children. Language development was assessed using caregiver-reported items adapted from the MacArthur–Bates Communicative Development Inventories. Explanatory variables followed the UNICEF early childhood development framework. Analyses included survey-weighted descriptive statistics, design-adjusted bivariate tests, and multivariable logistic regression models. Sensitivity analyses and collinearity diagnostics ensured robustness.Language delay affected 14.5% of children before the pandemic. Structural inequities were evident: delay was more frequent among children living in poverty, in rural settings, and in households with inadequate sanitation. Underlying determinants included lower maternal education and limited participation in early childhood programs. Proximal determinants showed the strongest associations. Lower cognitive stimulation (HOME score below the median), fewer types of toys, reduced access to children’s books, and less engagement in interactive activities (reading, storytelling, singing) were all linked to significantly higher odds of delay. Each additional hour of daily screen exposure increased odds of delay (aOR ~1.07). Male sex and older child age were consistent predictors. Effects were more pronounced among children experiencing stunting.Findings reveal deep socioeconomic and environmental gradients in early language development. The sharp post-pandemic increase in developmental delay (28%) reinforces the urgency of strengthening early identification and caregiver-support strategies within primary care.Language delay is a substantial and socially patterned public health challenge in a middle-income Latin American country. Integrating structured developmental monitoring and targeted family support into primary care could help mitigate widening post-pandemic developmental inequalities.

Early expressive vocabulary is a key indicator of child development and is routinely monitored in primary care. However, many middle-income settings lack population-based normative references to detect children at risk of language delay. No national expressive vocabulary norms previously existed for children aged 12–42 months in a middle-income Latin American country.To establish age-specific expressive vocabulary percentiles using MacArthur-Bates Communicative Development Inventories (MB-CDI) Short Forms and to estimate the prevalence of low language development in children aged 12–42 months in a middle-income Latin American country.This study analyzed data from a nationally representative health and nutrition survey conducted in 2018, including 4,652 children aged 12–42 months. Expressive vocabulary was assessed using three 50-item MB-CDI Short Forms across three age groups (12–18, 19–30, 31–42 months). Children with conditions potentially affecting neurodevelopment were excluded from norm construction. Generalized Additive Models for Location, Scale, and Shape (GAMLSS) were used to generate smooth percentile curves (P10, P25, P50, P75, P90). Demographic correlates of low vocabulary, defined as scoring below the 10th percentile, were examined.Vocabulary increased steadily with age in all percentiles. Median expressive vocabulary rose from 24 to 33 words (12–18 months), 12 to 32 words (19–30 months), and 18 to 30 words (31–42 months). Low language development affected 14.6% of children. Girls showed slightly higher scores in younger groups, though differences were not significant at older ages. Lower maternal education was strongly associated with higher prevalence of low vocabulary. Ceiling effects were observed at younger ages and were addressed using Beta-inflated models.This study provides the first population-based expressive vocabulary norms for young children in a middle-income Latin American country. The results highlight meaningful developmental variability and sociodemographic disparities relevant for early detection in primary care.MB-CDI Short Forms, combined with percentile-based norms, offer a feasible and culturally appropriate tool for identifying children at risk of language delay in primary care settings in a middle-income Latin American country. Incorporating expressive vocabulary monitoring into routine child health evaluations can support early intervention and reduce developmental inequities.

Given the ubiquity of touch screens and applications, the American Academy of Pediatrics revised its recommendations for the use of interactive screens in 2016, advising against their use before 18 months of age (compared to 24 months previously).The aim of this study was to describe touch screen exposure and associated factors in XXX children aged 0-36 months.Cross-sectional descriptive epidemiological study were conducted between August 2017 and August 2018. Questionnaires were distributed to parents of children aged 0-36 months who consulted general practitioners in the XXX region. Data were collected on exposure to touch screens, socio-demographic characteristics and parental feelings. Ethical approval and data protection compliance were secured, and informed consent was obtained.44 investigators were recruited and 395 questionnaires were collected. Three quarters of the children were exposed to a touch screen, mainly passively and accompanied. The child's age was correlated with greater exposure in terms of frequency (p = 0.001) and duration (p = 0.006). Other factors associated with more frequent exposure were grandparent care (p = 0.03), mother's lack of employment (p = 0.049) and parents' positive perception of screens (p < 0.001). These risk factors remained significant on multivariate analysis. There was no significant association between exposure to touch screens and child's gender, parents' age or parents' socio-professional categories.This study was the first in XXX to examine the link between childcare arrangements and children’s screen exposure. It achieved its intended statistical power and benefited from a multicentre design. However, some age and socio-professional groups were under-represented, and the robustness of the findings was limited by several biases, including selection, recall, social desirability, comprehension and geographical misclassification. The findings generally aligned with the international literature, but they also highlighted a novel association: higher touchscreen exposure among children cared for by grandparents.The high exposure to touch screens among young children in the XXX was consistent with the existing literature. Childcare by grandparents emerged as a significant factor for increased exposure. These findings highlight the importance of informing parents and grandparents about recommendations for screen use, with general practitioners playing a key role in prevention.

Attention-deficit/hyperactivity disorder (ADHD) affects 3–5% of children in XXX. Diagnosis is frequently delayed due to limited access to specialists and variability in clinical practices. As the first point of contact for families, general practitioners (GPs) play a pivotal role in early detection but often lack screening tools adapted to the realities of primary care.To identify, evaluate, and compare the diagnostic performance of ADHD screening tools for children and adolescents in the context of family medecine.A narrative literature review was conducted using a PRISMA-inspired approach. Searches of PubMed, Embase, the Cochrane Library, and Google Scholar (January 2015 – May 2025) identified studies involving children aged 6–18 years that evaluated ADHD screening or diagnostic tools applicable to general practice. Out of 166 references, 10 articles were retained after independent dual screening and critical appraisal.Three categories of instruments were identified. DSM-based scales (Conners, Vanderbilt, SNAP-IV, ADHD-RS) demonstrated good sensitivity (70–85%) but variable specificity (60–80%), which improved when combining reports from multiple informants.Broadband scales (SWAN, CBCL, CABI) assess both symptom severity and comorbidities; notably, the CABI offers free access and strong predictive validity (AUC ≈ 0.93). Short questionnaires (PSC, SDQ) are practical for rapid pre-screening in general practice but show limited specificity (< 60%) and should not be used in isolation.No single tool provides sufficiently reliable screening on its own. The most effective approach in primary care is a two-step strategy: (1) an initial pre-screening with a brief questionnaire (PSC or ASQ), followed by (2) a concise DSM-based scale (SNAP-IV or ADHD-RS) to quantify symptoms. A broadband scale (such as the CABI or CBCL) can be added when comorbidities are suspected. The general practitioner’s role is to identify children requiring specialist assessment and ensure follow-up within a structured care pathway, which could include a dedicated, coded consultation to synthesize clinical and screening data before referral.Standardized rating scales complement clinical evaluation and support earlier detection of ADHD in primary care. Future research should aim to develop validated, time-efficient tools tailored to general practice and to promote the use of accessible digital formats that facilitate their routine implementation.