Pathways to Service Receipt: Modeling Parent Help-Seeking for Childhood Mental Health Problems

Understanding parent appraisals of child behavior problems and parental help-seeking can reduce unmet mental health needs. Research has examined individual contributors to help-seeking and service receipt, but use of structural equation modeling (SEM) is rare. SEM was used to examine parents’ appraisal of child behavior, thoughts about seeking help, and receipt of professional services in a diverse, urban sample (N = 189) recruited from women infant and children offices. Parents of children 11–60 months completed questionnaires about child behavior and development, parent well-being, help-seeking experiences, and service receipt. Child internalizing, externalizing, and dysregulation problems, language delay, and parent worry about child behavior loaded onto parent appraisal of child behavior. Parent stress and depression were positively associated with parent appraisal (and help-seeking). Parent appraisal and help-seeking were similar across child sex and age. In a final model, parent appraisals were significantly associated with parent thoughts about seeking help, which was significantly associated with service receipt

Patterns of anxiety symptoms in toddlers and preschool-age children: Evidence of early differentiation

The degree to which young children’s anxiety symptoms differentiate according to diagnostic groupings is under-studied, especially in children below the age of 4 years. Theoretical (confirmatory factor analysis, CFA) and statistical (exploratory factor analysis, EFA) analytical methods were employed to test the hypothesis that anxiety symptoms among 2–3-year-old children from a non-clinical, representative sample would differentiate in a manner consistent with current diagnostic nosology. Anxiety symptom items were selected from two norm-referenced parent-report scales of child behavior. CFA and EFA results suggested that anxiety symptoms aggregate in a manner consistent with generalized anxiety, obsessive–compulsive symptoms, separation anxiety, and social phobia. Multi-dimensional models achieved good model fit and fit the data significantly better than undifferentiated models. Results from EFA and CFA methods were predominantly consistent and supported the grouping of early childhood anxiety symptoms into differentiated, diagnostic-specific categories

An Ecological Risk Model for Early Childhood Anxiety: The Importance of Early Child Symptoms and Temperament

Childhood anxiety is impairing and associated with later emotional disorders. Studying risk factors for child anxiety may allow earlier identification of at-risk children for prevention efforts. This study applied an ecological risk model to address how early childhood anxiety symptoms, child temperament, maternal anxiety and depression symptoms, violence exposure, and sociodemographic risk factors predict school-aged anxiety symptoms. This longitudinal, prospective study was conducted in a representative birth cohort (n=1109). Structural equation modeling was used to examine hypothesized associations between risk factors measured in toddlerhood/preschool (age=3.0 years) and anxiety symptoms measured in kindergarten (age=6.0 years) and second grade (age= 8.0 years). Early child risk factors (anxiety symptoms and temperament) emerged as the most robust predictor for both parent-and child-reported anxiety outcomes and mediated the effects of maternal and family risk factors. Implications for early intervention and prevention studies are discussed

Lost Toy? Monsters Under the Bed? Contributions of Temperament and Family Factors to Early Internalizing Problems in Boys and Girls

This study was designed to examine the contribution of multiple risk factors to early internalizing problems and to investigate whether family and ecological context moderated the association between child temperament and internalizing outcomes. A sample of 1,202 mothers of 2- and 3-year-old children completed a survey of child social-emotional functioning, family environment, and violence exposure. Child temperament, maternal affective symptoms, and family expressiveness were associated with child anxiety and depression problems. Violence exposure was related only to child anxiety. When maternal affective symptoms were elevated, inhibited girls but not boys were rated as more anxious and youngsters with heightened negative emotionality were rated as more depressed. Family expressiveness moderated the association between inhibited temperament and anxiety symptoms

Attention bias and anxiety in young children exposed to family violence

Background—Attention bias towards threat is associated with anxiety in older youth and adults and has been linked with violence exposure. Attention bias may moderate the relationship between violence exposure and anxiety in young children. Capitalizing on measurement advances, the current study examines these relationships at a younger age than previously possible. Methods—Young children (mean age 4.7, ±0.8) from a cross-sectional sample oversampled for violence exposure (N = 218) completed the dot-probe task to assess their attention biases. Observed fear/anxiety was characterized with a novel observational paradigm, the Anxiety Diagnostic Observation Schedule. Mother-reported symptoms were assessed with the Preschool-Age Psychiatric Assessment and Trauma Symptom Checklist for Young Children. Violence exposure was characterized with dimensional scores reflecting probability of membership in two classes derived via latent class analysis from the Conflict Tactics Scales: Abuse and Harsh Parenting. Results—Family violence predicted greater child anxiety and trauma symptoms. Attention bias moderated the relationship between violence and anxiety

Identifying and making recommendations for pediatric anxiety disorders in primary care settings: a video-based training

INTRODUCTION: Pediatric anxiety disorders have high rates of prevalence and confer risk for later disorders if they go undetected. In primary care, they are underdiagnosed, partly because pediatricians often lack relevant training. We developed a brief, video-based training program for pediatric residents aimed at improving early identification of anxiety disorders in primary care. METHODS: Video content was consistent with the American Academy of Pediatrics Behavioral Health Competencies, as applied to the evaluation of anxiety disorders and guidance for discussing treatment options. This training can be delivered in two formats: videos (43 minutes) can be shown in a live, group-based format, or accessed via an online, asynchronous training. We tested this training program using both formats and developed surveys to evaluate knowledge about child anxiety, perceived evaluation skills, and satisfaction with the training. We also developed a video-based vignette to measure sensitivity to detecting disorders (how much the condition is interfering, diagnostic severity, and referral urgency). RESULTS: Pediatric residents from two residency programs completed the training and pre- and posttraining assessments to evaluate program efficacy. Residents' knowledge and perceived evaluation skills increased posttraining, with large effect sizes. Residents also demonstrated increased sensitivity to detecting anxiety disorders on the vignette-based assessment and reported high levels of satisfaction. DISCUSSION: Our results suggested that residents participating in this training improved their evaluation skills and that residents found the training beneficial. Video-based trainings can significantly supplement existing education. This cost-effective and minimally burdensome training program can be used to enhance resident education in a much-needed area.Published versio

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity