What is typical: Atypical in young children's attention regulation?: Characterizing the developmental spectrum with the Multidimensional Assessment Profiles-Attention Regulation Infant-Toddler (MAPS-AR-IT) Scale.

While attention dysregulation is a promising early indicator of neurodevelopmental risk, in particular attention-deficit/hyperactivity disorder (ADHD), it is difficult to characterize clinical concern due to its developmental expectability at the transition to toddlerhood. Thus, explicating the typical:atypical continuum of risk indicators is among the key future directions for research to promote early identification and intervention, and prevent decrements in the attainment of developmental milestones into early childhood. In this paper, we present the Multidimensional Assessment Profiles-Attention Regulation Infant-Toddler (MAPS-AR-IT) Scale, a novel parent-report survey of dimensional, developmentally specified indicators of attention (dys)regulation. Item Response Theory was employed to characterize the typical:atypical spectrum of both normative and more concerning dysregulation (including the contexts in which behavior occurs). We provide evidence of the validity of this measure in capturing the full typical:atypical spectrum via a longitudinal sample of typically developing children at 12-18 months of age (baseline) via concurrent scores on well-validated temperament and clinical measures. We also examine longitudinal stability and predictive validity if the MAPS-AR-IT via a clinical interview of ADHD symptoms at 24-30 months (follow-up). While not diagnostic, we present evidence of the utility of the MAPS-AR-IT in explicating individual neurodevelopmental risk and elucidating the broader typicality of behaviors related to attention (dys)regulation.

Aunque la desregulación de la atención es un prometedor indicador temprano del riesgo neural de desarrollo, en particular el trastorno de déficit en la atención/hiperactividad (ADHD), es difícil caracterizar las preocupaciones clínicas debido al factor de expectativa de desarrollo al momento de la transición a la temprana niñez. De manera que explicar la progresión típica:atípica de indicadores de riesgo está entre las futuras directrices claves para la investigación con el fin de promover la temprana identificación e intervención, y prevenir disminuciones en el alcance de hitos críticos hacia la temprana niñez. En este ensayo, presentamos la Escala de Perfiles de Evaluación Multidimensional - Regulación de la Atención del Infante-Niño Pequeñito (MAPS-AR-IT) una novedosa encuesta de reporte del progenitor, acerca de la (des)regulación de la atención, dimensional y específica para el desarrollo. Aportamos evidencia de la validez de esta medida para captar la completa gama típica:atípica por medio de una muestra longitudinal de niños típicamente en desarrollo, a los 12-18 meses de edad (edad base) por medio de puntajes concurrentes sobre el temperamento bien validado y las medidas clínicas, así como también la estabilidad longitudinal y la validez de predicción por medio de una entrevista clínica de síntomas de ADHD a los 24-30 meses (seguimiento). Se empleó la Teoría de Respuesta al Asunto para caracterizar la gama típica:atípica tanto de la desregulación normativa como de la más preocupante (incluyendo los contextos en los cuales ocurre el comportamiento). Aunque no se trata de diagnóstico, presentamos evidencia de la utilidad de MAPS-AR-IT para explicar el riesgo individual de desarrollo neural y elucidar el más amplio aspecto típico de comportamientos relacionados con la (des)regulación de la atención.

Bien que la dysrégulation de l'attention soit un indicateur précoce prometteur du risque neurodéveloppemental, en particulier le trouble déficitaire de l'attention/hyperactivité (TDHA) il est difficile de caractériser la préoccupation clinique du fait de sa prévisibilité développementale à la transition à la petite enfance. Par conséquent, expliquer le continuum typique:atypique des indicateurs de risque s'avère être une des directions futures de recherches clé pour promouvoir l'identification et l'intervention précoce, et prévenir les baisses dans la réalisation d'étapes développementales importantes jusque dans la petite enfance. Dans cet article nous présentons l'Echelle Multidimensional Assessment Profiles - Attention Regulation Infant-Toddler (MAPS-AR-IT) (échelle de profils d'évaluation multidimensionnelle - régulation de l'attention bébé-petit enfant, abrégée selon l'anglais MAP-AR-IT), une étude nouvelle basée sur les rapports faits par les parents de la (dys)régulation de l'attention dimensionnelle et spécifiée selon le développement. Nous démontrons la validité de cette mesure en capturant l'éventail total typique:atypique au moyen d'un échantillon longitudinal d'enfants se développement typiquement, à 12-18 mois (ligne de case) au moyen de scores concurrents de mesures cliniques et de tempérament bien validées, ainsi qu''une stabilité longitudinale et d'une validité prédictive au moyen d'un entretien Clinique des symptômes THHA à 24-30 mois (suivi). La Item Response Theory (IRT) a été employée pour caractériser l'éventail typique:atypique de la dysrégulation à la fois normative et celle plus inquiétante (y compris les contextes dans lesquels le comportement prend place). Bien que cela ne soit pas diagnostique, nous présentons la preuve de l'utilité de la MAPS-AR-IT en expliquant le risqué neurodéveloppemental individuel et en élucidant la typicalité plus large de comportements liés à la (dys)régulation de l'attention.

Modeling the normal:abnormal spectrum of early childhood internalizing behaviors: A clinical-developmental approach for the Multidimensional Assessment Profiles Internalizing Dimensions.

BACKGROUND: We expanded the Multidimensional Assessment Profiles (MAPS) Scales developmental specification model to characterize the normal:abnormal spectrum of internalizing (anxious and depressive) behaviors in early childhood via the MAPS-Internalizing (MAPS-INT) scale. METHODS: The MAPS-INT item pool was generated based on clinical expertise and prior research. Analyses were conducted on a sub-sample of families (n = 183) from the diverse When to Worry early childhood sample. RESULTS: Normal:abnormal descriptive patterns for both anxious and depressive behaviors were consistent with prior work: (1) extremes of normative variation are abnormal when very frequent; and (2) pathognomonic indicators that most children do not engage in and are abnormal, even if infrequent. Factor analysis revealed a two-factor MAPS-INT Anxious Behaviors structure (Fearful-Worried and Separation Distress) and a unidimensional MAPS-INT Depressive Behaviors factor with good fit and good-to-excellent test-retest reliability and validity. CONCLUSIONS: We characterized the normal:abnormal spectrum of internalizing behaviors in early childhood via the MAPS-INT. Future research in larger representative samples can replicate and extend findings, including clinical thresholds and predictive utility. The MAPS-INT helps lay the groundwork for dimensional characterization of the internalizing spectrum to advance neurodevelopmental approaches to emergent psychopathology and its earlier identification.

Prevalence, stability, and predictive utility of the Multidimensional Assessment of Preschoolers Scales clinically optimized irritability score: Pragmatic early assessment of mental disorder risk.

OBJECTIVES: Characterizing the scope and import of early childhood irritability is essential for real-world actualization of this reliable indicator of transdiagnostic mental health risk. Thus, we utilize pragmatic assessment to establish prevalence, stability, and predictive utility of clinically significant early childhood irritability. METHODS: Data included two independent, diverse community samples of preschool age children (N = 1857; N = 1490), with a subset enriched for risk (N = 425) assessed longitudinally from early childhood through preadolescence (∼4-9 years old). A validated, brief (2-item) scale pragmatically assessed clinically significant irritability. In the longitudinal subsample, clinical interviews assessed internalizing/externalizing disorders. RESULTS: One in five preschool-age children had clinically significant irritability, which was independently replicated. Irritability was highly stable through preadolescence. Children with versus without clinically significant early childhood irritability had greater odds of early onset, persistent internalizing/externalizing disorders. The pragmatic assessment effectively screened out low-risk children and identified 2/3 of children with early-onset, persistent psychopathology. CONCLUSIONS: Clinically significant early childhood irritability prevalence is akin to the pediatric obesity epidemic and may warrant similar universal screening/intervention. Also, irritability's stability demonstrates the common guidance "they'll grow out of it" to be false. Finally, pragmatic irritability assessment has transdiagnostic predictive power and addresses a need for feasible measures to flag risk.

Maternal perceived stress and infant behavior during the COVID-19 pandemic.

BACKGROUND: Maternal stress has negative consequences on infant behavioral development, and COVID-19 presented uniquely stressful situations to mothers of infants born during the pandemic. We hypothesized that mothers with higher levels of perceived stress during the pandemic would report higher levels of infant regulatory problems including crying and interrupted sleep patterns. METHODS: As part 6 sites of a longitudinal study, mothers of infants born during the pandemic completed the Perceived Stress Scale, the Brief Infant Sleep Questionnaire, and an Infant Crying survey at 6 (n = 433) and 12 (n = 344) months of infant age. RESULTS: Maternal perceived stress, which remained consistent at 6 and 12 months of infant age, was significantly positively correlated with time taken to settle infants. Although maternal perceived stress was not correlated with uninterrupted sleep length, time taken to put the infant to sleep was correlated. Perceived stress was also correlated with the amount of infant crying and fussiness reported at 6 months. CONCLUSIONS: Mothers who reported higher levels of perceived stress during the pandemic reported higher levels of regulatory problems, specifically at 6 months. Examining how varying levels of maternal stress and infant behaviors relate to overall infant developmental status over time is an important next step. IMPACT: Women giving birth during the COVID-19 pandemic who reported higher levels of stress on the Perceived Stress Scale also reported higher levels of infant fussiness and crying at 6 months old, and more disruptive sleep patterns in their infants at 6 months and 12 months old. Sleeping problems and excessive crying in infancy are two regulatory problems that are known risk factors for emotional and behavioral issues in later childhood. This paper is one of the first studies highlighting the associations between maternal stress and infant behaviors during the COVID-19 pandemic.

Lability of prenatal stress during the COVID-19 pandemic links to negative affect in infancy.

The association between prenatal stress and children's socioemotional development is well established. The COVID-19 pandemic has been a particularly stressful period, which may impact the gestational environment. However, most studies to-date have examined prenatal stress at a single time point, potentially masking the natural variation in stress that occurs over time, especially during a time as uncertain as the pandemic. This study leveraged dense ecological momentary assessments from a prenatal randomized control trial to examine patterns of prenatal stress over a 14-week period (up to four assessments/day) in a U.S. sample of 72 mothers and infants. We first examined whether varied features of stress exposure (lability, mean, and baseline stress) differed depending on whether mothers reported on their stress before or during the pandemic. We next examined which features of stress were associated with 3-month-old infants' negative affect. We did not find differences in stress patterns before and during the pandemic. However, greater stress lability, accounting for baseline and mean stress, was associated with higher infant negative affect. These findings suggest that pathways from prenatal stress exposure to infant socioemotional development are complex, and close attention to stress patterns over time will be important for explicating these pathways.

Calibrating temper loss severity in the transition to toddlerhood: Implications for developmental science.

The integration of neurodevelopmental perspectives into clinical science has identified irritability as an early dimensional marker of lifespan mental health risk. Elucidating the developmental patterning of irritable behavior is key to differentiating normative variation from risk markers. Accounting for dysregulation and contextual features of irritability is useful for differentiation at preschool age, laying the groundwork for even earlier characterization. We provide initial evidence for the validity of the Multidimensional Assessment Profile of Disruptive Behavior Temper Loss Scale, Infant-Toddler version in two independent samples of 12-18-month-olds from the US. We calibrated the measure using item response theory in a large representative sample, then validated within an independent sample. We characterized the developmental patterning of irritable behaviors and their dimensional spectrum, and demonstrated test-retest reliability, and convergent validity. The MAP-DB-IT is a standardized, dimensional survey assessing irritability that serves as a tool for characterizing the developmental expression of early mental health risk.

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can help to inform and enable pre-emptive interventions for a likely physiologically and perceptibly stressful day. Machine learning models are useful tools that can be developed to predict next-day physiological and perceived stress by using data collected from the previous day. Such models can improve our understanding of the specific factors that predict physiological and perceived stress and allow researchers to develop systems that collect selected features for assessment in clinical trials to minimize the burden of data collection. OBJECTIVE: The aim of this study was to build and evaluate a machine-learned model that predicts next-day physiological and perceived stress by using sensor-based, ecological momentary assessment (EMA)-based, and intervention-based features and to explain the prediction results. METHODS: We enrolled pregnant women into a prospective proof-of-concept study and collected electrocardiography, EMA, and cognitive behavioral therapy intervention data over 12 weeks. We used the data to train and evaluate 6 machine learning models to predict next-day physiological and perceived stress. After selecting the best performing model, Shapley Additive Explanations were used to identify the feature importance and explainability of each feature. RESULTS: A total of 16 pregnant women enrolled in the study. Overall, 4157.18 hours of data were collected, and participants answered 2838 EMAs. After applying feature selection, 8 and 10 features were found to positively predict next-day physiological and perceived stress, respectively. A random forest classifier performed the best in predicting next-day physiological stress (F1 score of 0.84) and next-day perceived stress (F1 score of 0.74) by using all features. Although any subset of sensor-based, EMA-based, or intervention-based features could reliably predict next-day physiological stress, EMA-based features were necessary to predict next-day perceived stress. The analysis of explainability metrics showed that the prolonged duration of physiological stress was highly predictive of next-day physiological stress and that physiological stress and perceived stress were temporally divergent. CONCLUSIONS: In this study, we were able to build interpretable machine learning models to predict next-day physiological and perceived stress, and we identified unique features that were highly predictive of next-day stress that can help to reduce the burden of data collection.

Joint Consideration of Inhibitory Control and Irritability in Young Children: Contributions to Emergent Psychopathology.

Deficits in self-regulation capacity have been linked to subsequent impairment and clinical symptomology across the lifespan. Prior work has identified difficulty regulating angry emotions (i.e., irritability) as a powerful transdiagnostic indicator of current and future clinical concerns. Less is known regarding how irritability intersects with cognitive features of self-regulation, in particular inhibitory control, despite its mental health relevance. A promising avenue for improving specificity of clinical predictions in early childhood is multi-method, joint consideration of irritability and inhibitory control capacities. To advance early identification of impairment and psychopathology risk, we contrast group- and variable-based models of neurodevelopmental vulnerability at the interface of irritability and inhibitory control in contexts of varied motivational and emotional salience. This work was conducted in a longitudinal study of children recruited at well-child visits in Midwestern pediatric clinics at preschool age (N = 223, age range = 3-7 years). Group-based models (clustering and regression of clusters on clinical outcomes) indicated significant heterogeneity of self-regulation capacity in this sample. Meanwhile, variable-based models (continuous multiple regression) evidenced associations with concurrent clinical presentation, future symptoms, and impairment across the broad spectrum of psychopathology. Irritability transdiagnostically indicated internalizing and externalizing problems, concurrently and longitudinally. In contrast, inhibitory control was uniquely associated with attention-deficit/hyperactivity symptoms. We present these findings to advance a joint consideration approach to two promising indicators of neurodevelopmental vulnerability and mental health risk. Models suggest that both emotional and cognitive self-regulation capacities can address challenges in characterizing the developmental unfolding of psychopathology from preschool to early childhood age.

Don't Get Lost in Translation: Integrating Developmental and Implementation Sciences to Accelerate Real-World Impact on Children's Development, Health, and Wellbeing.

Translation of developmental science discoveries is impeded by numerous barriers at different stages of the research-to-practice pipeline. Actualization of the vast potential of the developmental sciences to improve children's health and development in the real world is imperative but has not yet been fully realized. In this commentary, we argue that an integrated developmental-implementation sciences framework will result in a translational mindset essential for accelerating real world impact. We delineate key principles and methods of implementation science of salience to the developmental science audience, lay out a potential synthesis between implementation and developmental sciences, provide an illustration of the Mental Health, Earlier Partnership (MHE-P), and set actionable steps for realization. Blending these approaches along with wide-spread adoption of the translational mindset has transformative potential for population-level impact of developmental science discovery.

Measuring PROMIS® Emotional Distress in Early Childhood.

OBJECTIVE: Create and validate developmentally sensitive parent-report measures of emotional distress for children ages 1-5 years that conceptually align with the Patient-Reported Outcome Measurement Information System (PROMIS®) pediatric measures. METHODS: Initial items were generated based on expert and parent input regarding core components of emotional distress in early childhood and review of theoretical and empirical work in this domain. Items were psychometrically tested using data from two waves of panel surveys. Item response theory (IRT) was applied to develop item calibration parameters (Wave 1), and scores were centered on a general U.S. population sample (Wave 2). Final PROMIS early childhood (EC) instruments were compared with existing measures of related constructs to establish construct validity. RESULTS: Experts and parents confirmed the content validity of the existing PROMIS Pediatric emotional distress domains (i.e., anger, anxiety, and depressive symptoms) as developmentally salient for young children. Existing items were adapted and expanded for early childhood by employing best practices from developmental measurement science. Item banks as well as 4- and 8-item short forms, free from differential item functioning across sex and age, were constructed for the three domains based on rigorous IRT analyses. Correlations with subscales from previously validated measures provided further evidence of construct validity. CONCLUSIONS: The PROMIS EC Anger/Irritability, Anxiety, and Depressive Symptoms measures demonstrated good reliability and initial evidence of validity for use in early childhood. This is an important contribution to advancing brief, efficient measurement of emotional distress in young children, closing a developmental gap in PROMIS pediatric emotional distress assessment.

Virtual Reality in the Pediatric Intensive Care Unit: Patient Emotional and Physiologic Responses.

Context: Patients in the Pediatric Intensive Care Unit (PICU) are limited in their ability to engage in developmentally typical activity. Long-term hospitalization, especially with minimal interpersonal engagement, is associated with risk for delirium and delayed recovery. Virtual reality (VR) has growing evidence as a safe, efficacious, and acceptable intervention for pain and distress management in the context of uncomfortable healthcare procedures, and for enhancing engagement in, and improving outcomes of rehabilitation therapy. Hypothesis: Critically ill children may experience high levels of engagement and physiologic effects while engaging with VR. Methods and Models: This cross-sectional study of 3-17-year-old children admitted to a PICU used a VR headset to deliver 360-degree immersive experiences. This study had a mixed-method approach, including standardized behavioral coding, participant and parent surveys, and participant physiologic responses. Investigators noted comments the child made about VR, observed emotional responses, and documented an engagement score. To determine physiologic response to VR, integer heart rate variability (HRVi) was collected 30 min before, during, and 30 min after VR. Results: One hundred fifteen participants were enrolled from 6/18 to 10/19, and they interacted with VR for a median of 10 min (interquartile range 7-17). Most children enjoyed the experience; 83% of participants smiled and 36% laughed while using VR. Seventy-two percent made positive comments while using VR. The strongest age-related pattern regarding comments was that the youngest children were more likely to share the experience with others. Seventy-nine percent of participants were highly engaged with VR. Ninety-two percent of parents reported that VR calmed their child, and 78% of participants felt that VR was calming. HRVi Minimum scores were significantly higher during VR than pre- (p < 0.001) or post-VR (p < 0.001). There was no significant difference between pre-and post-VR (p = 0.387); therefore, children returned to their pre-intervention state following VR. Interpretations and Conclusions: Children admitted to the PICU are highly engaged with and consistently enjoyed using VR. Both participants and parents found VR to be calming, consistent with intra-intervention physiologic improvements in HRVi. VR is an immersive tool that can augment the hospital environment for children.

Social EEG: A novel neurodevelopmental approach to studying brain-behavior links and brain-to-brain synchrony during naturalistic toddler-parent interactions.

Despite increasing emphasis on emergent brain-behavior patterns supporting language, cognitive, and socioemotional development in toddlerhood, methodologic challenges impede their characterization. Toddlers are notoriously difficult to engage in brain research, leaving a developmental window in which neural processes are understudied. Further, electroencephalography (EEG) and event-related potential paradigms at this age typically employ structured, experimental tasks that rarely reflect formative naturalistic interactions with caregivers. Here, we introduce and provide proof of concept for a new "Social EEG" paradigm, in which parent-toddler dyads interact naturally during EEG recording. Parents and toddlers sit at a table together and engage in different activities, such as book sharing or watching a movie. EEG is time locked to the video recording of their interaction. Offline, behavioral data are microcoded with mutually exclusive engagement state codes. From 216 sessions to date with 2- and 3-year-old toddlers and their parents, 72% of dyads successfully completed the full Social EEG paradigm, suggesting that it is possible to collect dual EEG from parents and toddlers during naturalistic interactions. In addition to providing naturalistic information about child neural development within the caregiving context, this paradigm holds promise for examination of emerging constructs such as brain-to-brain synchrony in parents and children.

Miniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants.

Early identification of atypical infant movement behaviors consistent with underlying neuromotor pathologies can expedite timely enrollment in therapeutic interventions that exploit inherent neuroplasticity to promote recovery. Traditional neuromotor assessments rely on qualitative evaluations performed by specially trained personnel, mostly available in tertiary medical centers or specialized facilities. Such approaches are high in cost, require geographic proximity to advanced healthcare resources, and yield mostly qualitative insight. This paper introduces a simple, low-cost alternative in the form of a technology customized for quantitatively capturing continuous, full-body kinematics of infants during free living conditions at home or in clinical settings while simultaneously recording essential vital signs data. The system consists of a wireless network of small, flexible inertial sensors placed at strategic locations across the body and operated in a wide-bandwidth and time-synchronized fashion. The data serve as the basis for reconstructing three-dimensional motions in avatar form without the need for video recordings and associated privacy concerns, for remote visual assessments by experts. These quantitative measurements can also be presented in graphical format and analyzed with machine-learning techniques, with potential to automate and systematize traditional motor assessments. Clinical implementations with infants at low and at elevated risks for atypical neuromotor development illustrates application of this system in quantitative and semiquantitative assessments of patterns of gross motor skills, along with body temperature, heart rate, and respiratory rate, from long-term and follow-up measurements over a 3-mo period following birth. The engineering aspects are compatible for scaled deployment, with the potential to improve health outcomes for children worldwide via early, pragmatic detection methods.

EEG/ERP as a pragmatic method to expand the reach of infant-toddler neuroimaging in HBCD: Promises and challenges.

Though electrophysiological measures (EEG and ERP) offer complementary information to MRI and a variety of advantages for studying infants and young children, these measures have not yet been included in large cohort studies of neurodevelopment. This review summarizes the types of EEG and ERP measures that could be used in the HEALthy Brain and Cognitive Development (HBCD) study, and the promises and challenges in doing so. First, we provide brief overview of the use of EEG/ERP for studying the developing brain and discuss exemplar findings, using resting or baseline EEG measures as well as the ERP mismatch negativity (MMN) as exemplars. We then discuss the promises of EEG/ERP such as feasibility, while balancing challenges such as ensuring good signal quality in diverse children with different hair types. We then describe an ongoing multi-site EEG data harmonization from our groups. We discuss the process of alignment and provide preliminary usability data for both resting state EEG data and auditory ERP MMN in diverse samples including over 300 infants and toddlers. Finally, we provide recommendations and considerations for the HBCD study and other studies of neurodevelopment.

Caregiver-mediated interventions to support self-regulation among infants and young children (0-5 years): a protocol for a realist review.

INTRODUCTION: Self-regulation is a modifiable protective factor for lifespan mental and physical health outcomes. Early caregiver-mediated interventions to promote infant and child regulatory outcomes prevent long-term developmental, emotional and behavioural difficulties and improve outcomes such as school readiness, educational achievement and economic success. To harness the population health promise of these programmes, there is a need for more nuanced understanding of the impact of these interventions. The aim of this realist review is to understand how, why, under which circumstances and for whom, early caregiver-mediated interventions improve infant and child self-regulation. The research questions guiding this review were based on consultation with families and community organisations that provide early childhood and family services. METHODS AND ANALYSIS: Realist reviews take a theory-driven and iterative approach to evidence synthesis, structured around continuous refinement of a programme theory. Programme theories specify context-mechanism-outcome configurations to explain what works, for whom, under which circumstances and how. Our initial programme theory is based on prior work in this field and will be refined through the review process. A working group, comprising service users, community organisation representatives, representatives from specific populations, clinicians and review team members will guide the evidence synthesis and interpretation, as well as the development and dissemination of recommendations based on the findings of the review. The review will involve searching: (i) electronic databases, (ii) connected papers, articles and citations and (iii) grey literature. Decisions to include evidence will be guided by judgements about their contribution to the programme theory and will be made by the research team, with input from the working group. Evidence synthesis will be reported using the Realist and MEta-narrative Evidence Synthesis: Evolving Standards guidelines. ETHICS AND DISSEMINATION: Ethical approval is not required as this is a review. Findings will be disseminated to our working group and through peer-reviewed publications and conference presentations. REVIEW REGISTRATION NUMBER: The protocol is registered with Open Science Framework https://osf.io/5ce2z/registrations.

Disruption Leads to Methodological and Analytic Innovation in Developmental Sciences: Recommendations for Remote Administration and Dealing With Messy Data.

The COVID-19 pandemic has impacted data collection for longitudinal studies in developmental sciences to an immeasurable extent. Restrictions on conducting in-person standardized assessments have led to disruptive innovation, in which novel methods are applied to increase participant engagement. Here, we focus on remote administration of behavioral assessment. We argue that these innovations in remote assessment should become part of the new standard protocol in developmental sciences to facilitate data collection in populations that may be hard to reach or engage due to burdensome requirements (e.g., multiple in-person assessments). We present a series of adaptations to developmental assessments (e.g., Mullen) and a detailed discussion of data analytic approaches to be applied in the less-than-ideal circumstances encountered during the pandemic-related shutdown (i.e., missing or messy data). Ultimately, these remote approaches actually strengthen the ability to gain insight into developmental populations and foster pragmatic innovation that should result in enduring change.

Starting at Birth: An Integrative, State-of-the-Science Framework for Optimizing Infant Neuromotor Health.

Numerous conditions and circumstances place infants at risk for poor neuromotor health, yet many are unable to receive treatment until a definitive diagnosis is made, sometimes several years later. In this integrative perspective, we describe an extensive team science effort to develop a transdiagnostic approach to neuromotor health interventions designed to leverage the heightened neuroplasticity of the first year of life. We undertook the following processes: (1) conducted a review of the literature to extract common principles and strategies underlying effective neuromotor health interventions; (2) hosted a series of expert scientific exchange panels to discuss common principles, as well as practical considerations and/or lessons learned from application in the field; and (3) gathered feedback and input from diverse stakeholders including infant caregivers and healthcare providers. The resultant framework was a pragmatic, evidence-based, transdiagnostic approach to optimize neuromotor health for high-risk infants based on four principles: (a) active learning, (b) environmental enrichment, (c) caregiver engagement, and (d) strength-based approaches. In this perspective paper, we delineate these principles and their potential applications. Innovations include: engagement of multiple caregivers as critical drivers of the intervention; promoting neuromotor health in the vulnerability phase, rather than waiting to treat neuromotor disease; integrating best practices from adjacent fields; and employing a strengths-based approach. This framework holds promise for implementation as it is scalable, pragmatic, and holistically addresses both the needs of the infant and their family.

Translating RDoC to Real-World Impact in Developmental Psychopathology: A Neurodevelopmental Framework for Application of Mental Health Risk Calculators.

The National Institute of Mental Health Research Domain Criteria's (RDoC) has prompted a paradigm shift from categorical psychiatric disorders to considering multiple levels of vulnerability for probabilistic risk of disorder. However, the lack of neurodevelopmentally-based tools for clinical decision-making has limited RDoC's real-world impact. Integration with developmental psychopathology principles and statistical methods actualize the clinical implementation of RDoC to inform neurodevelopmental risk. In this conceptual paper, we introduce the probabilistic mental health risk calculator as an innovation for such translation and lay out a research agenda for generating an RDoC- and developmentally-informed paradigm that could be applied to predict a range of developmental psychopathologies from early childhood to young adulthood. We discuss methods that weigh the incremental utility for prediction based on intensity and burden of assessment, the addition of developmental change patterns, considerations for assessing outcomes, and integrative data approaches. Throughout, we illustrate the risk calculator approach with different neurodevelopmental pathways and phenotypes. Finally, we discuss real-world implementation of these methods for improving early identification and prevention of developmental psychopathology. We propose that mental health risk calculators can build a needed bridge between RDoC's multiple units of analysis and developmental science.

Brief Report: What Diagnostic Observation Can Teach Us About Disruptive Behavior in Young Children with Autism.

ABSTRACT: Objective: Approximately 50% of children with autism exhibit severe tantrums, defiance, and/or aggression. We propose that the Disruptive Behavior Diagnostic Observation Schedule (DB-DOS)-a standardized clinical observation modeled after, and complementary to, the Autism Diagnostic Observation Schedule (ADOS)-could enhance earlier identification of disruptive behavior (DB) in autism populations and inform treatment planning. Methods: We adapted the DB-DOS for children with autism based on expert input and preliminary feasibility testing to accommodate varying cognitive and social communication capacities and increase the likelihood of observing DB in this population. Thereafter, we concurrently administered the modified DB-DOS and the ADOS to 12 children with autism aged 36 to 50 months. Results: Overall, children exhibited greater DB, especially behavioral regulation challenges, during the DB-DOS than during the ADOS. Conclusion: The use of a developmentally sensitive standardized observation tool that presses for DB to complement standardized observations such as the ADOS shows promise for enabling more precise research on targeted DB interventions. Such a tool holds promise as a reliable and efficient method of identifying comorbid DB disorders in the autism population.

Moving the dial on prenatal stress mechanisms of neurodevelopmental vulnerability to mental health problems: A personalized prevention proof of concept.

Prenatal stress exposure increases vulnerability to virtually all forms of psychopathology. Based on this robust evidence base, we propose a "Mental Health, Earlier" paradigm shift for prenatal stress research, which moves from the documentation of stress-related outcomes to their prevention, with a focus on infant neurodevelopmental indicators of vulnerability to subsequent mental health problems. Achieving this requires an expansive team science approach. As an exemplar, we introduce the Promoting Healthy Brain Project (PHBP), a randomized trial testing the impact of the Wellness-4-2 personalized prenatal stress-reduction intervention on stress-related alterations in infant neurodevelopmental trajectories in the first year of life. Wellness-4-2 utilizes bio-integrated stress monitoring for just-in-time adaptive intervention. We highlight unique challenges and opportunities this novel team science approach presents in synergizing expertise across predictive analytics, bioengineering, health information technology, prevention science, maternal-fetal medicine, neonatology, pediatrics, and neurodevelopmental science. We discuss how innovations across many areas of study facilitate this personalized preventive approach, using developmentally sensitive brain and behavioral methods to investigate whether altering children's adverse gestational exposures, i.e., maternal stress in the womb, can improve their mental health outlooks. In so doing, we seek to propel developmental SEED research towards preventive applications with the potential to reduce the pernicious effect of prenatal stress on neurodevelopment, mental health, and wellbeing.