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Adequate social functioning during childhood requires context-appropriate social decision-making. To make such decisions, children rely on their social norms, conceptualized as cognitive models of shared expectations. Since social norms are dynamic, children must adapt their models of shared expectations and modify their behavior in line with their social environment. This study aimed to investigate children’s abilities to use social information to adapt their fairness norm and to identify the computational mechanism governing this process. Thirty children (7–11 years, M = 7.9 SD = 0.85, 11 girls) played the role of Responder in a modified version of the Ultimatum Game–a two-player game based on the fairness norm–in which they had to choose to accept or reject offers from different Proposers. Norm adaptation was assessed by comparing rejection rates before and after a conditioning block in which children received several low offers. Computational models were compared to test which best explains children’s behavior during the game. Mean rejection rate decreased significantly after receiving several low offers suggesting that children have the ability to dynamically update their fairness norm and adapt to changing social environments. Model-based analyses suggest that this process involves the computation of norm-prediction errors. This is the first study on norm adaptation capacities in school-aged children that uses a computational approach. Children use implicit social information to adapt their fairness norm to changing environments and this process appears to be supported by a computational mechanism in which norm-prediction errors are used to update norms.

This study investigated the prospective links between sleep in infancy and preschoolers' cognitive performance. Mothers of 65 infants completed a sleep diary when infants were aged 1 year, and children completed two subscales of the Wechsler Preschool and Primary Scale of Intelligence at 4 years, indexing general cognitive ability and complex executive functioning. Consistent with hypotheses, children getting higher proportions of their sleep at night as infants were found to perform better on executive functions, but did not show better general cognition. Relations held after controlling for family socioeconomic status and prior cognitive functioning. These findings suggest that the special importance of sleep for higher order cognition, documented among adults, may appear very early in life.

Pediatric traumatic brain injury (TBI) can lead to adverse emotional, social, and behavioral consequences. However, outcome is difficult to predict due to significant individual variability, likely reflecting a complex interaction between injury- and child-related variables. Among these variables are genetically determined individual differences, which can modulate TBI outcome through their influence on neuroplasticity mechanisms. In this study, we examined the effect of Val66Met, a common polymorphism of the brain-derived neurotrophic factor gene known to be involved in neuroplasticity mechanisms, on behavioral symptoms of mild TBI (mTBI) sustained in early childhood. This work is part of a prospective, longitudinal cohort study of early TBI. The current sample consisted of 145 children between ages 18 and 60 months assigned to one of three participant groups: mild TBI, orthopedic injury, or typically developing children. Participants provided a saliva sample to detect the presence of the Val66Met polymorphism, and the Child Behavior Checklist was used to document the presence of behavioral symptoms at 6- and 18-months post-injury. Contrary to our initial hypothesis, at 6 months post-injury, non-carriers of the Val66Met polymorphism in the mTBI group presented significantly more internalizing symptoms (e.g., anxiety/depression and somatic complaints) than Val66Met carriers, who were similar to orthopedically injured and typically developing children. However, at 18 months post-injury, all children with mTBI presented more internalizing symptoms, independent of genotype. The results of the study provide evidence for a protective effect of the Val66Met polymorphism on internalizing behavior symptoms 6 months after early childhood mTBI.

Socio-emotional skills, including social competence and social cognition, form the basis for robust relationships and wellbeing. Despite their importance, these skills are poorly defined and measured, particularly in children with developmental vulnerabilities. As a consequence, targets for effective management and treatment remain unclear. We aimed to i) phenotype social competence and social cognition in typically developing children (TDC) and in children with neurodevelopmental or mental health disorders (clinical groups) and ii) establish the relationships between these child-direct measures and parent ratings of social competence and behavior. Using a multi-site, cross-sectional study design, we recruited 513 TDC and 136 children with neurodevelopmental (autism spectrum disorder [ASD], attention deficit hyperactivity disorder [ADHD]) or mental health (Anxiety Disorder [ANX]) diagnoses (age range 5-15 years). We administered the Paediatric Evaluation of Emotions, Relationships and Socialisation (PEERS) to children, and parents completed standardised questionnaires rating children's socio-emotional function. Standardised parent questionnaires revealed a global pattern of everyday socio-emotional impairment that was common to all clinical groups, while PEERS identified disorder-specific socio-cognitive profiles for children with ASD, ADHD and ANX. Compared to TDCs, children with ASD demonstrated global socio-cognitive impairment. Children with ADHD were impulsive, demonstrating difficulties managing speed accuracy trade-offs. Children with ANX exhibited slowed social decision-making, but otherwise intact skills. Standardized parent questionnaires of child socio-emotional function reveal differences between children with typical and atypical development, but do not yield disorder-specific, socio-emotional profiles. In contrast, findings from the PEERS objective assessment suggest that that ASD, ADHD and ANX are associated with distinct socio-cognitive phenotypes, to more accurately guide and target management and treatment of impaired social competence.

As the first step of social information processing, visual encoding underlies the interpretation of social cues. Faces, in particular, convey a large amount of affective information, which can be subsequently used in the planning and production of adaptive social behaviors. Sociomoral reasoning is a specific social skill that is associated with engagement in appropriate social behaviors when faced with dilemmas. Previous studies using eye tracking suggest that visual encoding may play an important role in decision-making when individuals are faced with extreme moral dilemmas, but it is not known if this is generalizable to everyday situations. The main objective of this study was to assess the contribution of visual encoding to everyday sociomoral reasoning using eye tracking and ecological visual dilemmas. Participants completed the SocioMoral Reasoning Aptitude Level (SoMoral) task while their eye movements and pupil dilation were recorded. While visual encoding was not a predictor of sociomoral decision-making, sociomoral maturity was predicted by fixation count. Thus, in an ecological context, visual encoding of social cues appears to be associated with sociomoral maturity: the production of a justification is associated with volitional encoding strategies. Implications with regards to the dual-process theory of sociomoral reasoning and social information processing are discussed.

The terminology used to describe components of social cognition lacks clarity and specificity. Recent studies have tried to reach consensus on definitions of social cognition based on expert opinion. These efforts resulted in semantically well-defined terms and distinct concepts, but it remains unclear whether these terms also align with empirical data and existing theoretical models of social cognition. In this commentary, we examine whether the proposed definitions for social cognition are supported by clinical observations and the extant knowledge base on the underlying neural substrates of these skills. In addition, we consider how the proposed definitions align with existing theoretical models of social cognition. We argue that consensus should not be based solely on expert opinion. Therefore, we propose an updated biopsychosocial model of social cognition that integrates proposed expert definitions with a theoretical model of social cognition based on empirical data: the Hierarchical Interdependent Taxonomy of Social cognition (HITS) model. The HITS model guides future research, helps to address the poor construct validity that has been revealed for several tests of social cognition, and provides a framework for the assessment of social cognition.

Background Digital health technologies are increasingly used by healthcare professionals working in pediatric hospital and rehabilitation settings. Multiple factors may affect the implementation and use of digital health technologies in these settings. However, such factors have not been identified in a multidisciplinary, pediatric context. The objective of this study was to describe actual use and to identify the factors that promote or hinder the intention to use digital health technologies (mobile learning applications, virtual/augmented reality, serious games, robotic devices, telehealth applications, computerized assessment tools, and wearables) among pediatric healthcare professionals. Methods An online survey evaluating opinions, current use, and future intentions to use digital health technologies was completed by 108 professionals at one of Canada’s largest pediatric institutes. Mann-Whitney U tests were used to compare the attitudes of healthcare professionals who intend to increase their use of digital health technologies and those who do not. Linear regression analyses were used to determine predictors of usage success. Results Healthcare professionals reported mostly using mobile and tablet learning applications ( n  = 43, 38.1%), telehealth applications ( n  = 49, 43.4%), and computerized assessment tools ( n  = 33, 29.2%). Attitudes promoting the intention to increase the use of digital health technologies varied according to technology type. Healthcare professionals who wished to increase their use of digital health technologies reported a more positive attitude regarding benefits in clinical practice and patient care, but were also more critical of potential negative impacts on patient-professional relationships. Ease of use ( β  = 0.374; p  = 0.020) was a significant predictor of more favorable usage success. The range of obstacles encountered was also a significant predictor ( β  = 0.342; p  = 0.032) of less favorable evaluation of usage success. Specific factors that hinder successful usage are lack of training ( β  = 0.303; p  = 0.033) and inadequate infrastructure ( β  = 0.342; p  = 0.032). Conclusions When working with children, incorporating digital health technologies can be effective for motivation and adherence. However, it is crucial to ensure these tools are implemented properly. The findings of this study underscore the importance of addressing training and infrastructure needs when elaborating technology-specific strategies for multidisciplinary adoption of digital health technologies in pediatric settings.

Brain injury during early childhood may disrupt key periods of neurodevelopment. Most research regarding mild traumatic brain injury (mTBI) has focused on school-age children. We sought to characterize the incidence and healthcare utilization for mTBI in young children presenting to U.S. emergency departments (ED). The Nationwide Emergency Department Sample was queried for children age 0–6 years with mTBI from 2016 to 2019. Patients were excluded for focal or diffuse TBI, drowning or abuse mechanism, death in the ED or hospital, Injury Severity Score > 15, neurosurgical intervention, intubation, or blood product transfusion. National estimates included 1,372,291 patient visits: 63.5% were two years or younger, 57.5% were male, and 69.4% were injured in falls. The most common head injury diagnosis was “unspecified injury of head” (83%); this diagnosis decreased in frequency as age increased, in favor of a concussion diagnosis. Most patients were seen at low pediatric volume EDs (64.5%) and non-children's hospital EDs (86.2%), and 64.9% were seen at a non-teaching hospital. Over 98% were treated in the ED and discharged home. Computed tomography of the head and cervical spine were performed in 18.7% and 1.6% of patients, respectively, less often at children's hospitals (OR = 0.55, 95%CI = 0.41–0.76 for head and OR = 0.19, 95%CI = 0.11–0.34 for cervical spine). ED charges resulted in $540–681 million annually, and more than half of patients utilized Medicaid. Early childhood mTBI is prevalent and results in high financial burden in the U.S. There is wide variation in diagnostic coding and computed tomography scanning amongst EDs. More focused research is needed to identify optimal diagnostic tools and management strategies.

Dyslexia and Attention deficit disorder (AD) are prevalent neurodevelopmental conditions in children and adolescents. They have high comorbidity rates and have both been associated with motor difficulties. Little is known, however, about what is shared or differentiated in dyslexia and AD in terms of motor abilities. Even when motor skill problems are identified, few studies have used the same measurement tools, resulting in inconstant findings. The present study assessed increasingly complex gross motor skills in children and adolescents with dyslexia, AD, and with both Dyslexia and AD. Our results suggest normal performance on simple motor-speed tests, whereas all three groups share a common impairment on unimanual and bimanual sequential motor tasks. Children in these groups generally improve with practice to the same level as normal subjects, though they make more errors. In addition, children with AD are the most impaired on complex bimanual out-of-phase movements and with manual dexterity. These latter findings are examined in light of the Multiple Deficit Model.

Concussion is commonly characterized by a cascade of neurometabolic changes following injury. Magnetic Resonance Spectroscopy (MRS) can be used to quantify neurometabolites non-invasively. Longitudinal changes in neurometabolites have rarely been studied in pediatric concussion, and fewer studies consider symptoms. This study examines longitudinal changes of neurometabolites in pediatric concussion and associations between neurometabolites and symptom burden. Participants who presented with concussion or orthopedic injury (OI, comparison group) were recruited. The first timepoint for MRS data collection was at a mean of 12 days post-injury (n = 545). Participants were then randomized to 3 (n = 243) or 6 (n = 215) months for MRS follow-up. Parents completed symptom questionnaires to quantify somatic and cognitive symptoms at multiple timepoints following injury. There were no significant changes in neurometabolites over time in the concussion group and neurometabolite trajectories did not differ between asymptomatic concussion, symptomatic concussion, and OI groups. Cross-sectionally, Choline was significantly lower in those with persistent somatic symptoms compared to OI controls at 3 months post-injury. Lower Choline was also significantly associated with higher somatic symptoms. Although overall neurometabolites do not change over time, choline differences that appear at 3 months and is related to somatic symptoms.