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BackgroundResearch and clinical practice rely heavily on caregiver-report measures, such as the Child Behavior Checklist 1.5-5 (CBCL/1.5-5), to gather information about early childhood behavior problems and to screen for clinically significant behavior problems. While studies have shown that demographic variables influence ratings of behavior problems, the extent to which the CBCL/1.5-5 functions equivalently at the item level across diverse samples is unknown.MethodsItem-level data of CBCL/1.5-5 on a large sample of young children (N=7827) were drawn from 26 cohorts in the Environmental influences on Child Health Outcomes (ECHO) program. Factor analyses and the alignment method were applied to examine measurement invariance and differential item functioning (DIF) across child- (child age, sex, bilingual status, and neurodevelopmental disorders), and caregiver-level characteristics (caregiver sex, education level, household income level, and depression). Child race was examined in sensitivity analyses.ResultsItem sets with the most impactful DIF across child and caregiver groupings were identified for Internalizing, Externalizing, and Total Problems. The robust item sets, which excluded the high DIF items, showed good reliabilities and high correlations with the original scales for all three constructs. Language version of CBCL administration, caregiver education, and respondent sex showed the most significant impact on the measurement invariance, followed by child age. Sensitivity analyses revealed that child race has a unique impact on DIF over and above socioeconomic status.ConclusionsThe CBCL/1.5-5, a parent-report measure of early childhood behavior problems, showed bias across demographic groups. Robust item sets with less DIF can measure Internalizing, Externalizing, and Total Problems equally as well as the full item sets.

Background: The financial hardships and social isolation experienced during the COVID-19 pandemic have been found to adversely affect children’s developmental outcomes. While many studies thus far have focused on school-aged children and the pandemic-related impacts on their academic skills and behavior problems, relatively less is known about pandemic hardships and associations with children’s development during their early years. Using a racially and economically diverse sample, we examined whether hardships experienced during the pandemic were associated with children’s development with a particular focus on communication and socioemotional development. Methods: Participants from eight cohorts of the Environmental influences on Child Health Outcomes program provided data on pandemic-related financial and social hardships as well as child developmental outcomes. Financial hardship was defined as at least one parent experiencing job loss or change, and social hardship was defined as families’ quarantining from household members or extended family and friends. The development of children under 4 was assessed longitudinally, before and during the pandemic (N = 684), using the Ages and Stages Questionnaire (ASQ). The Generalized Estimating Equations, which accounted for within-child correlation, were used for analysis. Results: Families from minority backgrounds and low socioeconomic status disproportionately experienced pandemic-related hardships. Male children had higher odds of experiencing negative changes in communication and personal social skills from pre- to during-pandemic visits (ORs ranged between 2.24 and 3.03 in analysis with binary ASQ outcomes and ranged from −0.34–0.36 in analyses with ASQ z-scores, ps = 0.000). Pandemic-related hardships in the social and financial areas did not explain within-individual changes in children’s developmental outcomes. Conclusion: Negative developmental changes from pre- to during-pandemic were found in boys, yet we did not find any associations between increased experience of pandemic-related hardships and children’s development. E how pandemic hardships affect development using a larger sample size and with longer follow-up is warranted.

Humans show an attention bias toward emotional versus neutral information, which is considered an adaptive pattern of information processing. Deviations from this pattern have been observed in children with socially withdrawn behaviors, with most research being conducted in controlled settings among children from urban areas. The goal of the current study was to examine the cross-cultural applicability of two eye-tracking-based measures in assessing attention biases and their relations to children's symptoms of socially withdrawn behaviors in two independent and diverse samples of preschool children. The cross-cultural comparison was conducted between the Navajo Birth Cohort study (NBCS), an indigenous cohort with relatively low socioeconomic status (SES), and the Illinois Kids Development study (IKIDS), a primarily Non-Hispanic White and high SES cohort. Children in both cohorts completed eye-tracking tasks with pictures of emotional faces, and mothers reported on children's symptoms of socially withdrawn behaviors. Results showed that general patterns of attention biases were mostly the same across samples, reflecting heightened attention toward emotional versus neutral faces. The differences across two samples mostly involved the magnitude of attention biases. NBCS children were slower to disengage from happy faces when these emotional faces were paired with neutral faces. Additionally, socially withdrawn children in the NBCS sample showed a pattern of attentional avoidance for emotional faces. The comparability of overall patterns of attention biases provides initial support for the cross-cultural applicability of the eye-tracking measures and demonstrates the robustness of these methods across clinical and community settings. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Background: The financial hardships and social isolation experienced during the COVID-19 pandemic have been found to adversely affect children’s developmental outcomes. While many studies thus far have focused on school-aged children and the pandemic-related impacts on their academic skills and behavior problems, relatively less is known about pandemic hardships and associations with children’s development during their early years. Using a racially and economically diverse sample, we examined whether hardships experienced during the pandemic were associated with children’s development with a particular focus on communication and socioemotional development. Methods: Participants from eight cohorts of the Environmental influences on Child Health Outcomes program provided data on pandemic-related financial and social hardships as well as child developmental outcomes. Financial hardship was defined as at least one parent experiencing job loss or change, and social hardship was defined as families’ quarantining from household members or extended family and friends. The development of children under 4 was assessed longitudinally, before and during the pandemic (N = 684), using the Ages and Stages Questionnaire (ASQ). The Generalized Estimating Equations, which accounted for within-child correlation, were used for analysis. Results: Families from minority backgrounds and low socioeconomic status disproportionately experienced pandemic-related hardships. Male children had higher odds of experiencing negative changes in communication and personal social skills from pre- to during-pandemic visits (ORs ranged between 2.24 and 3.03 in analysis with binary ASQ outcomes and ranged from −0.34–0.36 in analyses with ASQ z-scores, ps = 0.000). Pandemic-related hardships in the social and financial areas did not explain within-individual changes in children’s developmental outcomes. Conclusion: Negative developmental changes from pre- to during-pandemic were found in boys, yet we did not find any associations between increased experience of pandemic-related hardships and children’s development. E how pandemic hardships affect development using a larger sample size and with longer follow-up is warranted.

For many practitioners in schools and clinics, collecting data to show the effectiveness of an intervention is probably one of the most important yet challenging components of intervention implementation. This article provides practitioners with an example case study of how data can be organized and collected to determine the effectiveness of a social skills group intervention. Techniques to establish individual and group goals, determine a method to collect data, collect baseline data, and monitor progress are described. Challenges and practical strategies are discussed, and useful and specific suggestions are provided.

Objective: The Internet and other electronic media may provide one part of a solution for reducing disparities in the availability of medical services. From a patient-centred perspective, an individual with a chronic, degenerative condition may ask what information is available that I can use to manage changes in my functional capacity over time, and how effective is this? The purpose of this study was to assess the availability and quality of a sample of online self-help videos which address common functional problems ubiquitous among individuals living with one such condition: Parkinson’s disease. Design: Cross-sectional survey. Setting: Internet. Method: An Internet search was conducted to identify self-help videos offering instruction on how to manage changes in function, and each video was assessed using 17 factors relevant to instructional quality. Results: Of 295 videos, 14 (4.7%) provided self-help instruction for three chosen skills. The quality of instructional presentation averaged 2.75 on a 5-point scale, where 1 was poor and 5 was excellent. Conclusion: The identified self-help videos that addressed maintaining functional outcomes for individuals living with Parkinson’s disease varied significantly in quality, and few met accepted standards of instructional design. Future research into effective presentation modes and patient functional capacity needs might usefully develop a patient-centred curriculum that can be delivered utilising multiple platforms. This area of research is critical in rehabilitation and other health settings to enhance assistance for individuals living with chronic health conditions and their families and caregivers.

Purpose Recent developments in image recognition and “Big Data” offer a method for monitoring the physical accessibility of community environments over time. The stimulus characteristics of images showing access features in context are extremely complex, however, and defining access features that are recognizable by humans or machines is a challenging task. Carefully defining access features provides a basis for teaching both humans and machines to recognize those features and to rate the degree of accessibility. Design/methodology/approach We employed a stage-process to identify access features detectable in images presented by GSV. We created definitions of features, developed a protocol for conducting community observations, and used it to conduct assessments of access images of 14 towns and cities in 9 states and the District of Columbia. Findings Interobserver agreement averaged 84% on features and 93% on people observed. A combined access score across communities averaged 60%; ranging from 32% to 100%. A scaled “minimum access” score averaged .92; ranging from .59 to 1.0. We observed 158 people, 3 of whom used a mobility device and 13 of whom used other wheeled devices. Practical Implications Equating these ratings to academic grades suggests that several communities fail to achieve standards of accessibility but do achieve minimal levels of access in their civic cores. Google Street View offers a data source for human observers to assess the accessibility of communities. Researchers should explore the feasibility of using supervised and unsupervised learning to establish machine recognition of access features.

Attention-deficit/hyperactivity disorder (ADHD) in childhood is associated with poor academic functioning. Deficits in academic functioning have proven to be less responsive to intervention than behavioral deficits in this population, yet the causes of this academic underperformance are not well understood. The purpose of this study is to examine the relationship between ADHD and academic performance in elementary-aged children in a developmental context. To do this, we study important cognitive variables and academic achievement over a three-year timeframe.Based on teacher ratings of ADHD, children were divided into a high symptom group (n = 17) and a low symptom group (n = 34). A thorough battery of cognitive and academic tests was administered at Time 1 and again 2 years later. Cognitive measures focused specifically on working memory and response inhibition.RESULTS indicate that children who have high levels of ADHD signs differ from their low-sign peers in academic achievement and in several cognitive domains. Differences in cognitive functioning show a developmental trend consistent with earlier developmental delays in response inhibition and later delays in working memory. Working memory appears to be particularly important in several academic domains. Importantly, in a longitudinal model, working memory was more predictive of math achievement for students demonstrating signs of ADHD than for those who did not.The relationship between these cognitive variables and academic functioning are explicated in the domains of reading, math, and problem solving.