ABSTRACT
Developmental theories suggest that exposure to early life adversity (ELA) alters developing emotional response systems, predicting risk for psychopathology across the life span. The present study examines whether negative emotionality (NE), a trait-like measure of emotionality that develops during early childhood, mediates the association between ELA and psychopathology in a representative sample of 917 preschoolers (Mage = 3.84). Additionally, we explored whether cognitive control, which supports attentional focusing and inhibition and has been identified as a transdiagnostic protective factor, moderates the impact of heightened emotionality following adversity on psychopathology risk. We utilized parent report of adversity, psychopathology, and NE and parent report and task-based measures of cognitive control. Structural equation modeling of cross-sectional data revealed that NE partially mediated the link between ELA and psychopathology symptoms. Moreover, parent-reported cognitive control buffered this link such that the effect of ELA on psychopathology through NE was stronger in children with low versus high cognitive control. These results identify elevated NE as one mechanism linking ELA and psychopathology, specifically among children with poorer top-down control, informing our understanding of key risk and protective factors among adversity-exposed children.
ABSTRACT
BACKGROUND: The association between adversity and psychopathology in adolescents and adults is characterized by equifinality. These associations, however, have not been assessed during early childhood when psychopathology first emerges. Defining adversity using both dimensional and cumulative risk approaches, we examined whether specific types of adversity are differentially associated with psychopathology in preschool-aged children. METHODS: Measures of threat, deprivation, and total adversities (i.e., cumulative risk) were calculated based on parent-reported information for 755 2- to 5-year old children recruited from pediatric primary care clinics. Logistic regression was used to estimate cross-sectional associations between type of adversity and anxiety, depression, ADHD, and behavioral disorder diagnoses. RESULTS: Threat and cumulative risk exhibited independent associations with psychopathology. Threat was strongly related to behavioral disorders. Cumulative risk was consistently related to all psychopathologies. CONCLUSIONS: Using mutually adjusted models, we identified differential associations between threat and psychopathology outcomes in preschool-aged children. This selectivity may reflect different pathways through which adversity increases the risk for psychopathology during this developmentally important period. As has been observed at other ages, a cumulative risk approach also effectively identified the cumulative impact of all forms of adversity on most forms of psychopathology during early childhood.
Subject(s)
Child Abuse , Mental Disorders , Adolescent , Adult , Anxiety Disorders/epidemiology , Child , Child, Preschool , Cross-Sectional Studies , Humans , Mental Disorders/diagnosis , Mental Disorders/epidemiology , PsychopathologyABSTRACT
BACKGROUND: There is evidence of unmet psychiatric needs in children under 6. These young children are dependent on their parents to identify their mental health needs. This study tested child and parent associations with parent perception of young child mental health need. METHOD: Parents of 917 children (aged 2-6 years) completed a diagnostic interview about their child assessing depression, anxiety, ODD/CD, ADHD, and impairment. Parents were surveyed about their own depression, anxiety, and asked about their psychiatric impairment. Parents were also asked whether they perceived their child as having a mental health need. RESULTS: Only 38.8% of children who met criteria for a diagnosis were perceived by their parents as having a need, similar to previously studied rates in school-aged children. Perception of need was associated with higher levels of symptoms and impairment. Thresholds for at least half of parents perceiving their child as having a need were relatively high: 19 or more symptoms, or 4 or more impairments. There was evidence of specificity: children with depressive disorders were more likely to be perceived as in need compared with other disorders. In terms of parent factors, more parental depressive symptoms were associated with higher perception of child need when the child had a diagnosis. Parental psychological impairment was associated with higher perception of need when the child had no diagnosis. CONCLUSIONS: Most preschool children that meet criteria for a psychiatric disorder are not perceived as needing help by their parents, which is dependent on both child and parent factors.
Subject(s)
Mental Health , Parents , Anxiety Disorders , Child , Child, Preschool , Humans , Parents/psychology , Perception , Surveys and QuestionnairesABSTRACT
OBJECTIVES: To assess changes in quality of care for children at risk for autism spectrum disorders (ASD) due to process improvement and implementation of a digital screening form. STUDY DESIGN: The process of screening for ASD was studied in an academic primary care pediatrics clinic before and after implementation of a digital version of the Modified Checklist for Autism in Toddlers - Revised with Follow-up with automated risk assessment. Quality metrics included accuracy of documentation of screening results and appropriate action for positive screens (secondary screening or referral). Participating physicians completed pre- and postintervention surveys to measure changes in attitudes toward feasibility and value of screening for ASD. Evidence of change was evaluated with statistical process control charts and χ2 tests. RESULTS: Accurate documentation in the electronic health record of screening results increased from 54% to 92% (38% increase, 95% CI 14%-64%) and appropriate action for children screening positive increased from 25% to 85% (60% increase, 95% CI 35%-85%). A total of 90% of participating physicians agreed that the transition to a digital screening form improved their clinical assessment of autism risk. CONCLUSIONS: Implementation of a tablet-based digital version of the Modified Checklist for Autism in Toddlers - Revised with Follow-up led to improved quality of care for children at risk for ASD and increased acceptability of screening for ASD. Continued efforts towards improving the process of screening for ASD could facilitate rapid, early diagnosis of ASD and advance the accuracy of studies of the impact of screening.
Subject(s)
Autism Spectrum Disorder/diagnosis , Checklist/methods , Electronic Health Records/statistics & numerical data , Mass Screening/methods , Quality Improvement , Age Factors , Child, Preschool , Early Diagnosis , Female , Follow-Up Studies , Humans , Incidence , Infant , Male , Risk Assessment , Severity of Illness IndexABSTRACT
BACKGROUND: Bipolar disorder (BD) is highly familial, but studies have yet to examine preschoolers at risk for BD using standardized, developmentally appropriate clinical assessment tools. We used such methods to test whether preschoolers at familial risk for BD have more observed difficulty modulating emotions and behaviors than do low-risk preschoolers. Identification of emotional and behavioral difficulties in at-risk preschoolers is crucial for developing new approaches for early intervention and prevention of BD. METHODS: Using the standardized disruptive behavior diagnostic observation schedule (DB-DOS) protocol for preschoolers, we compared 23 preschoolers (M(age): 4.53 ± 0.73 years; 18 males) with a first-degree relative with BD to 21 preschoolers (M(age): 4.65 ± 0.84 years; 11 males) without a family history of BD. We characterized psychopathology in this sample using the Preschool Aged Psychiatric Assessment and behavioral and emotional problems using the Child Behavior Checklist. RESULTS: High-risk preschoolers demonstrated significantly more intense, pervasive, and clinically concerning problems in anger modulation and behavior dysregulation on the DB-DOS than the low-risk group. High-risk relative to low-risk preschoolers, were also more likely to have maternal-reported anxiety and oppositional defiant disorders and internalizing and externalizing problems. CONCLUSIONS: Clinically concerning problems in anger modulation and behavior regulation, measured during standardized laboratory observation, differentiate preschoolers at high familial risk for BD from those at low risk. Investigation in a large longitudinal sample is critical for replication and for determining whether these observed behavioral differences can be reliably used as prodromal indicators of mood disorders.
Subject(s)
Affective Symptoms/epidemiology , Bipolar Disorder/epidemiology , Child Behavior Disorders/epidemiology , Genetic Predisposition to Disease/epidemiology , Affective Symptoms/psychology , Anger , Attention Deficit and Disruptive Behavior Disorders , Bipolar Disorder/psychology , Child Behavior Disorders/psychology , Child, Preschool , Comorbidity , Female , Genetic Predisposition to Disease/psychology , Humans , MaleABSTRACT
BACKGROUND: The threshold for clinical relevance of preschool anxiety has recently come under increasing scrutiny in view of large variations in prevalence estimates. We studied the impact of presence/absence of additional depressive comorbidity (symptoms and/or diagnosis) on preschoolers with anxiety disorders in relation to clinical phenomenology, family, and peer problems compared to healthy controls. METHOD: A population of 1738 preschoolers were screened and oversampled for internalizing symptoms from community sites, yielding a sample of 236 children. RESULTS: Using a multi-informant approach (mother, father, teacher, child), we found evidence that children with anxiety disorders and depressive comorbidity display a greater internalizing symptom-load, more peer problems and live in families with more psychosocial impairment (poor family functioning, family adversity, maternal mental health problems). The pure anxiety group was merely dissociable from controls with regard to internalizing symptoms and family adversity. CONCLUSION: The presence of depressive comorbidity in anxiety disorders may mark the transition to a more detrimental and impairing disorder at preschool age.
Subject(s)
Anxiety Disorders/epidemiology , Depression/epidemiology , Anxiety Disorders/etiology , Child of Impaired Parents/psychology , Child, Preschool , Comorbidity , Depression/etiology , Family/psychology , Humans , Life Change Events , Male , Peer Group , Psychiatric Status Rating Scales , Risk FactorsABSTRACT
OBJECTIVE: To advance understanding of early childhood bed-sharing and its clinical significance, we examined reactive bed-sharing rates, sociodemographic correlates, persistence, and concurrent and longitudinal associations with sleep disturbances and psychopathology. METHODS: Data from a representative cohort of 917 children (mean age 3.8 years) recruited from primary pediatric clinics in a Southeastern city for a preschool anxiety study were used. Sociodemographics and diagnostic classifications for sleep disturbances and psychopathology were obtained using the Preschool Age Psychiatric Assessment (PAPA), a structured diagnostic interview administered to caregivers. A subsample of 187 children was re-assessed approximately 24.7 months after the initial PAPA interview. RESULTS: Reactive bed-sharing was reported by 38.4% of parents, 22.9% nightly and 15.5% weekly, and declined with age. At follow-up, 48.9% of nightly bed-sharers and 88.7% of weekly bed-sharers were no longer bed-sharing. Sociodemographics associated with nightly bed-sharing were Black and (combined) American Indian, Alaska Native and Asian race and ethnicity, low income and parent education less than high school. Concurrently, bed-sharing nightly was associated with separation anxiety and sleep terrors; bed-sharing weekly was associated with sleep terrors and difficulty staying asleep. No longitudinal associations were found between reactive bed-sharing and sleep disturbances or psychopathology after controlling for sociodemographics, baseline status of the outcome and time between interviews. CONCLUSIONS: Reactive bed-sharing is relatively common among preschoolers, varies significantly by sociodemographic factors, declines during the preschool years and is more persistent among nightly than weekly bed-sharers. Reactive bed-sharing may be an indicator of sleep disturbances and/or anxiety but there is no evidence that bed-sharing is an antecedent or consequence of sleep disturbances or psychopathology.
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OBJECTIVE: The dimensional model of adversity and psychopathology hypothesizes deprivation and threat impact distinct neurobiological pathways, such as brain structure. This hypothesis has not been examined longitudinally or in young children. This study tested longitudinal associations between threat and deprivation measured in preschool and brain structure in childhood. It was hypothesized that threat would be associated with amygdala and hippocampal subcortical volume and deprivation would be associated with cortical thickness in association cortex. METHOD: The study included T1-weighted scans from 72 children (5-10 years old, 54.2% female participants). Threat was measured by the presence of domestic violence, sexual abuse, physical abuse, or neighborhood violence. Deprivation was measured by the presence of neglect. Associations of deprivation or threat with brain structure were examined controlling for other dimension (deprivation or threat) and nuisance covariates using whole-brain vertex-wise analyses. Subcortical volume was extracted, and the same associations were examined using multiple regression. RESULTS: Threat was associated with widespread decreases in cortical surface area across the prefrontal cortex and other regions. Threat was not associated with amygdala or hippocampal volume. Deprivation was associated with increased thickness in occipital cortex, insula, and cingulate. CONCLUSION: Results suggest distinct associations of deprivation and threat on brain structure in early childhood. Threat is associated with widespread differences in surface area, and deprivation is associated with differences in cortical thickness. These observations are consistent with work in adolescence and adulthood and reflect how dimensions of adversity differentially impact neural structure.
Subject(s)
Brain , Cerebral Cortex , Child , Adolescent , Humans , Child, Preschool , Female , Male , Brain/diagnostic imaging , Brain/pathology , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/pathology , Violence , Prefrontal Cortex , Occipital Lobe , Magnetic Resonance ImagingABSTRACT
Attention-deficit/hyperactivity disorder (ADHD) symptoms affect 40-60% of autistic children and have been linked to differences in adaptive behavior. It is unclear whether adaptive behavior in autistic youth is directly impacted by co-occurring ADHD symptoms or by another associated feature of both autism and ADHD, such as increased irritability. The current study examined relationships between irritability, ADHD symptoms, and adaptive behavior in 3- to 7-year-old autistic children. Results suggest that, after adjusting for co-occurring ADHD symptoms, higher levels of irritability are associated with differences in social adaptive behavior specifically. Understanding relationships between irritability, ADHD, and adaptive behavior in autistic children is critical because measures of adaptive behavior, such as the Vineland Scales of Adaptive Functioning, are often used as a proxy for global functioning, as well as for developing intervention plans and measuring outcomes as primary endpoints in clinical trials.
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A growing literature demonstrates that early clinical intervention can reduce risks of adverse psychosocial outcomes. A first step necessary for developing early intervention services is to know the prevalence of clinical disorders, especially in systems that are rebuilding, such as Romania, where the mental health system was dismantled under Ceausescu. No epidemiologic studies have examined prevalence of psychiatric disorders in young children in Romania. The objective of this study was to determine the prevalence of psychiatric disorders in Romanian children 18-60 months in pediatric settings. Parents of 1,003 children 18-60 months in pediatric waiting rooms of two pediatric hospitals completed background information, the Child Behavior Checklist (CBCL). A subgroup over-sampled for high mental health problems were invited to participate in the Preschool Age Psychiatric Assessment. Rates of mental health problems were similar to the US norms on the CBCL. The weighted prevalence of psychiatric disorders in these children was 8.8%, with 5.4% with emotional disorders and 1.4% with behavioral disorders. Comorbidity occurred in nearly one-fourth of the children with a psychiatric disorder and children who met diagnostic criteria had more functional impairment than those without. Of children who met criteria for a psychiatric disorder, 10% of parents were concerned about their child's emotional or behavioral health. This study provides prevalence rates of psychiatric disorders in young Romanian children, clinical characteristic of the children and families that can guide developing system of care. Cultural differences in parental report of emotional and behavioral problems warrant further examination.
Subject(s)
Mental Disorders/epidemiology , Checklist , Chi-Square Distribution , Child Behavior/psychology , Child Behavior Disorders/epidemiology , Child, Preschool , Comorbidity , Educational Status , Female , Humans , Infant , Male , Prevalence , Psychiatric Status Rating Scales , Romania/epidemiology , Sex FactorsABSTRACT
Observational behavior analysis plays a key role for the discovery and evaluation of risk markers for many neurodevelopmental disorders. Research on autism spectrum disorder (ASD) suggests that behavioral risk markers can be observed at 12 months of age or earlier, with diagnosis possible at 18 months. To date, these studies and evaluations involving observational analysis tend to rely heavily on clinical practitioners and specialists who have undergone intensive training to be able to reliably administer carefully designed behavioural-eliciting tasks, code the resulting behaviors, and interpret such behaviors. These methods are therefore extremely expensive, time-intensive, and are not easily scalable for large population or longitudinal observational analysis. We developed a self-contained, closed-loop, mobile application with movie stimuli designed to engage the child's attention and elicit specific behavioral and social responses, which are recorded with a mobile device camera and then analyzed via computer vision algorithms. Here, in addition to presenting this paradigm, we validate the system to measure engagement, name-call responses, and emotional responses of toddlers with and without ASD who were presented with the application. Additionally, we show examples of how the proposed framework can further risk marker research with fine-grained quantification of behaviors. The results suggest these objective and automatic methods can be considered to aid behavioral analysis, and can be suited for objective automatic analysis for future studies.
ABSTRACT
Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time-consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors. This study assessed the utility of a tablet-based behavioral assessment for eliciting and detecting one type of risk behavior, namely, patterns of facial expression, in 104 toddlers (ASD N = 22) and evaluated whether such patterns differentiated toddlers with and without ASD. The assessment consisted of the child sitting on his/her caregiver's lap and watching brief movies shown on a smart tablet while the embedded camera recorded the child's facial expressions. Computer vision analysis (CVA) automatically detected and tracked facial landmarks, which were used to estimate head position and facial expressions (Positive, Neutral, All Other). Using CVA, specific points throughout the movies were identified that reliably differentiate between children with and without ASD based on their patterns of facial movement and expressions (area under the curves for individual movies ranging from 0.62 to 0.73). During these instances, children with ASD more frequently displayed Neutral expressions compared to children without ASD, who had more All Other expressions. The frequency of All Other expressions was driven by non-ASD children more often displaying raised eyebrows and an open mouth, characteristic of engagement/interest. Preliminary results suggest computational coding of facial movements and expressions via a tablet-based assessment can detect differences in affective expression, one of the early, core features of ASD. LAY SUMMARY: This study tested the use of a tablet in the behavioral assessment of young children with autism. Children watched a series of developmentally appropriate movies and their facial expressions were recorded using the camera embedded in the tablet. Results suggest that computational assessments of facial expressions may be useful in early detection of symptoms of autism.
Subject(s)
Autistic Disorder/diagnosis , Facial Expression , Area Under Curve , Autism Spectrum Disorder/diagnosis , Child, Preschool , Family , Female , Humans , Infant , Male , Movement , Phenotype , ROC CurveABSTRACT
BACKGROUND: The differentiation hypothesis posits that the underlying liability distribution for psychopathology is of low dimensionality in young children, inflating diagnostic comorbidity rates, but increases in dimensionality with age as latent syndromes become less correlated. This hypothesis has not been adequately tested with longitudinal psychiatric symptom data. METHODS: Confirmatory factor analyses of DSM-IV symptoms from seven common Axis I syndromes--major depression, generalized anxiety, separation anxiety, social anxiety, attention deficient hyperactivity, conduct, and oppositional defiant disorders--were conducted longitudinally, from ages 9 to 16, using the general-population Great Smoky Mountains Study sample. RESULTS: An eight-syndrome model fit well at all ages, and in both genders. It included social anxiety, separation anxiety, oppositional defiant, and conduct syndromes, along with a multidimensional attention deficit-hyperactivity syndrome (i.e., inattention, hyperactivity, and impulsivity) and a unidimensional major depression/generalized anxiety syndrome. A high degree of measurement invariance across age was found for all syndromes, except for major depression/generalized anxiety. Major depression and generalized anxiety syndromes slightly diverged at age 14-16, when they also began to explain more symptom variance. Additionally, correlations between some emotional and disruptive syndromes showed slight differentiation. CONCLUSIONS: Marked developmental differentiation of psychopathology, as implied by the orthogenetic principle, is not a prominent cause of preadolescent and adolescent psychiatric comorbidity.
Subject(s)
Mental Disorders/psychology , Adolescent , Age Factors , Child , Child, Preschool , Comorbidity , Diagnostic and Statistical Manual of Mental Disorders , Disease Progression , Disease Susceptibility , Female , Humans , Longitudinal Studies , Male , Mental Disorders/diagnosis , Mental Disorders/epidemiology , Models, Psychological , Personality Assessment/statistics & numerical data , Psychological Theory , Psychometrics , Psychopathology , Risk Factors , Sex Factors , SyndromeABSTRACT
Anxiety disorders are prevalent and significantly impact young children and their families. One hypothesized risk factor for anxiety is heightened responses to sensory input. Few studies have explored this hypothesis prospectively. This study had two goals: (1) examine whether sensory over-responsivity is predictive of the development of anxiety in a large prospective sample of children, and (2) identify whether anxiety mediates the relationship between sensory over-responsivity and behavioral challenges. Children's sensory and anxiety symptoms were assessed in a community sample of 917 at 2-5 and again in 191 of these children at 6 years old. Parents also reported on a number of additional behavioral challenges previously found to be associated with both sensory over-responsivity and anxiety separately: irritability, food selectivity, sleep problems, and gastrointestinal problems. Forty three percent of preschool children with sensory over-responsivity also had a concurrent impairing anxiety disorder. Preschool sensory over-responsivity symptoms significantly and positively predicted anxiety symptoms at age six. This relationship was both specific and unidirectional. Finally, school-age anxiety symptoms mediated the relationship between preschool sensory over-responsivity symptoms and both irritability and sleep problems at school-age. These results suggest sensory over-responsivity is a risk factor for anxiety disorders. Furthermore, children who have symptoms of sensory over-responsivity as preschoolers have higher levels of anxiety symptoms at school-age, which in turn is associated with increased levels of school-age behavioral challenges.
Subject(s)
Anxiety Disorders/epidemiology , Child Development , Irritable Mood , Sensation Disorders/epidemiology , Sleep Wake Disorders/epidemiology , Child , Child, Preschool , Female , Follow-Up Studies , Humans , Male , Risk FactorsABSTRACT
This study examines interactions of heritable influences, prenatal substance use, and postnatal parental warmth and hostility on the development of conduct problems in middle childhood for boys and girls. Participants are 561 linked families, collected in 2 cohorts, including birth parents, adoptive parents, and adopted children. Heritable influences on internalizing and externalizing (including substance use) problems were derived from birth mothers' and fathers' symptoms, diagnoses, and age of onset from diagnostic interviews, and the proportion of first-degree relatives with the same type of problems. Smoking during pregnancy (SDP) and alcohol use during pregnancy were assessed retrospectively from birth mothers at 5 months postpartum. Earlier externalizing problems and parental warmth and hostility and were assessed at 1 assessment prior to the outcome (Cohort II: 4.5 years; Cohort I: 7 years). Conduct problems were symptoms from a diagnostic interview assessed at age 6 (Cohort II) or 8 (Cohort I). Findings from regression analyses suggest that (a) SDP plays an important role for the development of conduct problems, (b) some relatively well-accepted effects (e.g., parental hostility) were less important when simultaneously considering multiple factors influencing the development of conduct problems, and (c) main effects of genetic risk and SDP, and interactions among genetic risk and postnatal warmth, SDP and postnatal warmth, and genetic risk, SDP, and postnatal hostility for conduct problems were important for boys' but not girls' conduct problems. Replication is needed, but the current results provide preliminary but empirically grounded hypotheses for future research testing complex developmental models of conduct problems. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Subject(s)
Conduct Disorder/genetics , Parent-Child Relations , Parenting/psychology , Prenatal Exposure Delayed Effects/genetics , Alcoholism , Child , Child, Preschool , Cohort Studies , Female , Hostility , Humans , Male , Pregnancy , Prenatal Exposure Delayed Effects/psychology , Risk FactorsABSTRACT
To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundered and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. Computer vision analysis measured participants' attention and orienting in response to name calls. Reliability of the computer vision analysis algorithm was tested against a human rater. Differences in behavior were analyzed between the autism spectrum disorder group and the comparison group. Reliability between computer vision analysis and human coding for orienting to name was excellent (intra-class coefficient 0.84, 95% confidence interval 0.67-0.91). Only 8% of toddlers with autism spectrum disorder oriented to name calling on >1 trial, compared to 63% of toddlers in the comparison group (p = 0.002). Mean latency to orient was significantly longer for toddlers with autism spectrum disorder (2.02 vs 1.06 s, p = 0.04). Sensitivity for autism spectrum disorder of atypical orienting was 96% and specificity was 38%. Older toddlers with autism spectrum disorder showed less attention to the videos overall (p = 0.03). Automated coding offers a reliable, quantitative method for detecting atypical social orienting and reduced sustained attention in toddlers with autism spectrum disorder.
Subject(s)
Attention/physiology , Autism Spectrum Disorder/physiopathology , Photic Stimulation/methods , Child, Preschool , Computers , Female , Humans , Infant , Male , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Current tools for objectively measuring young children's observed behaviors are expensive, time-consuming, and require extensive training and professional administration. The lack of scalable, reliable, and validated tools impacts access to evidence-based knowledge and limits our capacity to collect population-level data in non-clinical settings. To address this gap, we developed mobile technology to collect videos of young children while they watched movies designed to elicit autism-related behaviors and then used automatic behavioral coding of these videos to quantify children's emotions and behaviors. We present results from our iPhone study Autism & Beyond, built on ResearchKit's open-source platform. The entire study-from an e-Consent process to stimuli presentation and data collection-was conducted within an iPhone-based app available in the Apple Store. Over 1 year, 1756 families with children aged 12-72 months old participated in the study, completing 5618 caregiver-reported surveys and uploading 4441 videos recorded in the child's natural settings. Usable data were collected on 87.6% of the uploaded videos. Automatic coding identified significant differences in emotion and attention by age, sex, and autism risk status. This study demonstrates the acceptability of an app-based tool to caregivers, their willingness to upload videos of their children, the feasibility of caregiver-collected data in the home, and the application of automatic behavioral encoding to quantify emotions and attention variables that are clinically meaningful and may be refined to screen children for autism and developmental disorders outside of clinical settings. This technology has the potential to transform how we screen and monitor children's development.
ABSTRACT
BACKGROUND: Controversy concerning the diagnosis of pediatric bipolar disorder (BD) has focused attention on children with chronic irritability and hyperarousal. This syndrome has been called the "broad BD phenotype" or severe mood dysregulation (SMD). This study examines prevalence, concurrent Axis I diagnoses, and longitudinal outcome of SMD in an epidemiologic sample. METHODS: Data were drawn from the Great Smoky Mountains Study, a longitudinal epidemiological study. Items from the Child and Adolescent Psychiatric Assessment were used to generate SMD criteria. RESULTS: Among 1420 children, the lifetime prevalence of SMD in children ages 9-19 was 3.3%. Most (67.7%) SMD youth had an Axis I diagnosis, most commonly attention-deficit/hyperactivity disorder (26.9%), conduct disorder (25.9%), and/or oppositional defiant disorder (24.5%). In young adulthood (mean age 18.3 +/- 2.1 years), youth who met criteria for SMD in the first wave (mean age 10.6 +/- 1.4 years) were significantly more likely to be diagnosed with a depressive disorder (odds ratio 7.2, confidence interval 1.3-38.8, p = .02) than youth who never met criteria for SMD. CONCLUSIONS: Severe mood dysregulation is relatively common in childhood and predicts risk for early adulthood depressive disorders. Research should continue to explore the course of illness in children with SMD.
Subject(s)
Attention Deficit Disorder with Hyperactivity/epidemiology , Conduct Disorder/epidemiology , Depression/epidemiology , Mood Disorders/diagnosis , Mood Disorders/epidemiology , Adolescent , Adult , Age Factors , Child , Conduct Disorder/diagnosis , Cross-Sectional Studies , Female , Humans , Longitudinal Studies , Male , Mood Disorders/complications , Prevalence , Psychiatric Status Rating Scales/statistics & numerical dataABSTRACT
Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over the last decade find that the prevalence of impairing anxiety disorders in preschool children ranges from 0.3% to 6.5%. Yet, less than 15% of young children with an impairing anxiety disorder receive a mental health evaluation or treatment. One possible reason for the low rate of care for anxious preschoolers is the lack of affordable, timely, reliable and valid tools for identifying young children with clinically significant anxiety. Diagnostic interviews assessing psychopathology in young children require intensive training, take hours to administer and code, and are not available for use outside of research settings. The Preschool Age Psychiatric Assessment (PAPA) is a reliable and valid structured diagnostic parent-report interview for assessing psychopathology, including anxiety disorders, in 2 to 5 year old children. In this paper, we apply machine-learning tools to already collected PAPA data from two large community studies to identify sub-sets of PAPA items that could be developed into an efficient, reliable, and valid screening tool to assess a young child's risk for an anxiety disorder. Using machine learning, we were able to decrease by an order of magnitude the number of items needed to identify a child who is at risk for an anxiety disorder with an accuracy of over 96% for both generalized anxiety disorder (GAD) and separation anxiety disorder (SAD). Additionally, rather than considering GAD or SAD as discrete/binary entities, we present a continuous risk score representing the child's risk of meeting criteria for GAD or SAD. Identification of a short question-set that assesses risk for an anxiety disorder could be a first step toward development and validation of a relatively short screening tool feasible for use in pediatric clinics and daycare/preschool settings.
Subject(s)
Anxiety Disorders/diagnosis , Machine Learning , Anxiety Disorders/epidemiology , Child, Preschool , Female , Humans , Male , Parents/psychology , Prevalence , Risk , Sensitivity and SpecificityABSTRACT
This paper presents the clinical/developmental framework underlying a new diagnostic observational tool, the Disruptive Behavior Diagnostic Observation Schedule (DB-DOS). The special importance of observation for clinical assessment during the preschool period is delineated. The developmental rationale for a multi-dimensional assessment of disruptive behavior in young children, including problems in modulation of negative affect and low competence is discussed. The ways in which the DB-DOS will elucidate distinctions between normative and atypical behavior during this developmental period via (a) the integration of qualitative and quantitative dimensions of behavior within a clinically-sensitive coding system, (b) the observation of child behavior both within, and outside of, the parent-child context and (c) the use of specially designed tasks to "press" for clinically salient behaviors are addressed. The promise of this new method for yielding a more precise, developmentally based description of the phenotype of early onset disruptive behavior problems and for providing a standardized clinical tool for observational assessment of disruptive behavior in young children is presented. Large-scale validation of the measure is currently underway.