Quantitative analysis of heterogeneity in academic achievement of children with autism.
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ABSTRACT:
SUBMITTER: Chen L
PROVIDER: S-EPMC6483392 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
Publications
Quantitative analysis of heterogeneity in academic achievement of children with autism.
Chen Lang L Abrams Daniel A DA Rosenberg-Lee Miriam M Iuculano Teresa T Wakeman Holly N HN Prathap Sandhya S Chen Tianwen T Menon Vinod V
Clinical psychological science : a journal of the Association for Psychological Science 20181114 2
Autism spectrum disorders (ASD) represent a quintessential example of a clinical population with diverse symptom presentations and marked variation in cognitive abilities. However, the extent literature lacks rigorous quantitative procedures for characterizing heterogeneity of cognitive abilities in these individuals. Here we employ novel clustering and cross-validation procedures to investigate the stability of heterogeneous patterns of cognitive abilities in reading and math in a relatively la ...[more]
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Project description:OBJECTIVE:This study examined early predictors of and changes in school-age academic achievement and class placement in children referred for autism spectrum disorder (ASD) at age 2. METHOD:Of 111 ASD referrals, 74 were diagnosed with ASD at age 18. Regression analyses were performed to identify age 3 predictors of achievement in arithmetic, passage comprehension, word reading, and spelling at ages 9 and 18. Linear Mixed Models were used to examine predictors of academic growth between ages 9 and 18. RESULTS:Academic skills varied widely at 9 and 18, but were mostly commensurate with or higher than expected given cognitive levels. However, 22% (age 9) and 32% (age 18) of children with average/above average IQ showed below/low average achievement in at least one academic domain. Children who remained in general education/inclusion classrooms had higher achievement than those who moved to special education classrooms. Stronger cognitive skills at age 3 and 9 predicted better academic achievement and faster academic growth from age 9 to 18. Parent participation in intervention by age 3 predicted better achievement at age 9 and 18. CONCLUSIONS:Many children with ASD achieve basic academic skills commensurate with or higher than their cognitive ability. However, more rigorous screening for learning difficulties may be important for those with average cognitive skills because a significant minority show relative academic delays. Interventions targeting cognitive skills and parent participation in early treatment may have cascading effects on long-term academic development.
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Project description:Background and objectivePrevious studies of academic achievement of children with oral clefts have mostly relied on small, clinic-based samples prone to ascertainment bias. In the first study in the United States to use a population-based sample with direct assessment, we evaluated the academic achievement of children with oral clefts relative to their classmates.MethodsChildren born with isolated oral clefts in Iowa from 1983 to 2003 were identified from the Iowa Registry for Congenital and Inherited Disorders and matched to unaffected classmates by gender, school/school district, and month and year of birth. Academic achievement was assessed by using standardized tests of academic progress developed by the Iowa Testing Programs. Iowa Testing Programs data were linked to birth certificates for all children. Regression models controlled for household demographic and socioeconomic factors. The analytical sample included 588 children with clefts contributing 3735 child-grade observations and 1874 classmates contributing 13?159 child-grade observations.ResultsChildren with oral clefts had lower scores than their classmates across all domains and school levels, with a 5-percentile difference in the overall composite score. Children with clefts were approximately one-half grade level behind their classmates and had higher rates of academic underachievement and use of special education services by 8 percentage points. Group differences were slightly lower but remained large and significant after adjusting for many background characteristics.ConclusionsChildren with oral clefts underperformed across all academic areas and grade levels compared with their classmates. The results support a model of early testing and intervention among affected children to identify and reduce academic deficits.
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Project description:Aerobic fitness has been shown to have several beneficial effects on child health. However, research on its relationship with academic performance has been limited, particularly in developing countries and among undernourished populations. This study examined the association between aerobic fitness and academic achievement in clinically healthy but nutritionally compromised Indian school-aged children and assessed whether micronutrient status affects this association. 273 participants, aged 7 to 10.5 years, were enrolled from three primary schools in Bangalore, India. Data on participants' aerobic fitness (20-m shuttle test), demographics, anthropometry, diet, physical activity, and micronutrient status were abstracted. School-wide exam scores in mathematics and Kannada language served as indicators of academic performance and were standardized by grade level. The strength of the fitness/achievement association was analyzed using Spearman's rank correlation, multiple variable logistic regression, and multi-level models. Significant positive correlations between aerobic capacity (VO2 peak) and academic scores in math and Kannada were observed (P < 0.05). After standardizing scores across grade levels and adjusting for school, gender, socioeconomic status, and weight status (BMI Z-score), children with greater aerobic capacities (mL * kg(-1) * min(-1)) had greater odds of scoring above average on math and Kannada exams (OR=1.08, 95% CI: 1.02 to 1.15 and OR=1.11, 95% CI: 1.04 to 1.18, respectively). This association remained significant after adjusting for micronutrient deficiencies. These findings provide preliminary evidence of a fitness/achievement association in Indian children. While the mechanisms by which aerobic fitness may be linked to academic achievement require further investigation, the results suggest that educators and policymakers should consider the adequacy of opportunities for physical activity and fitness in schools for both their physical and potential academic benefits.
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Project description:BackgroundCare for children with autism spectrum disorder (ASD) can be challenging for families and medical care systems. This is especially true in low- and- middle-income countries such as Bangladesh. To improve family-practitioner communication and developmental monitoring of children with ASD, mCARE (Mobile-Based Care for Children with Autism Spectrum Disorder Using Remote Experience Sampling Method) was developed. Within this study, mCARE was used to track child milestone achievement and family sociodemographic assets to inform mCARE feasibility/scalability and family asset-informed practitioner recommendations.ObjectiveThe objectives of this paper are threefold. First, it documents how mCARE can be used to monitor child milestone achievement. Second, it demonstrates how advanced machine learning models can inform our understanding of milestone achievement in children with ASD. Third, it describes family/child sociodemographic factors that are associated with earlier milestone achievement in children with ASD (across 5 machine learning models).MethodsUsing mCARE-collected data, this study assessed milestone achievement in 300 children with ASD from Bangladesh. In this study, we used 4 supervised machine learning algorithms (decision tree, logistic regression, K-nearest neighbor [KNN], and artificial neural network [ANN]) and 1 unsupervised machine learning algorithm (K-means clustering) to build models of milestone achievement based on family/child sociodemographic details. For analyses, the sample was randomly divided in half to train the machine learning models and then their accuracy was estimated based on the other half of the sample. Each model was specified for the following milestones: Brushes teeth, Asks to use the toilet, Urinates in the toilet or potty, and Buttons large buttons.ResultsThis study aimed to find a suitable machine learning algorithm for milestone prediction/achievement for children with ASD using family/child sociodemographic characteristics. For Brushes teeth, the 3 supervised machine learning models met or exceeded an accuracy of 95% with logistic regression, KNN, and ANN as the most robust sociodemographic predictors. For Asks to use toilet, 84.00% accuracy was achieved with the KNN and ANN models. For these models, the family sociodemographic predictors of "family expenditure" and "parents' age" accounted for most of the model variability. The last 2 parameters, Urinates in toilet or potty and Buttons large buttons, had an accuracy of 91.00% and 76.00%, respectively, in ANN. Overall, the ANN had a higher accuracy (above ~80% on average) among the other algorithms for all the parameters. Across the models and milestones, "family expenditure," "family size/type," "living places," and "parent's age and occupation" were the most influential family/child sociodemographic factors.ConclusionsmCARE was successfully deployed in a low- and middle-income country (ie, Bangladesh), providing parents and care practitioners a mechanism to share detailed information on child milestones achievement. Using advanced modeling techniques this study demonstrates how family/child sociodemographic elements can inform child milestone achievement. Specifically, families with fewer sociodemographic resources reported later milestone attainment. Developmental science theories highlight how family/systems can directly influence child development and this study provides a clear link between family resources and child developmental progress. Clinical implications for this work could include supporting the larger family system to improve child milestone achievement.
| S-EPMC8262602 | biostudies-literature
Project description: Not available
| S-EPMC4874515 | biostudies-literature
Project description:ObjectivesWelfare policy focuses on vulnerable populations, such as children with difficult family backgrounds. Education is a crucial way to reduce poverty. This study explored the relationship between children's diet structure and academic achievement and compared these across different family backgrounds.DesignA cross-sectional study was conducted to survey the health status of children from difficult families based on a random sampling method in 2018. Survey data were collected from children and their guardians with a questionnaire. A multi-sample latent class model and an ordinal logistic model were applied for data analysis.SettingThis study was conducted in 31 provinces nationwide. Two provinces in the Central (Shandong and Jiangxi), Eastern (Hebei and Henan) and Western (Chongqing and Shanxi) regions and one province in the Northeast (Liaoning) were selected considering different stratum of economic development.ParticipantsA total of 2099 children with difficult family backgrounds and 666 children from ordinary families were surveyed.ResultsThe dietary structure of children from ordinary families was significantly better than that of children with difficult or unstable family backgrounds ([Formula: see text] =9.178, p<0.01). Children from difficult families had an intake of dairy products and fruits below dietary standards. The difference in academic achievement between children in the balanced and deprived groups was statistically significant (OR=0.640, 95% CI 0.429 to 0.955). Other determinants of the academic achievement of children in difficult families were parents' education level (OR=1.331, 95% CI 1.162 to 1.525), family economic status (OR=0.835, 95% CI 0.748 to 0.932) and parents' academic concern (OR=0.373, 95% CI 0.252 to 0.553).ConclusionsTo address the differences between children from difficult families and ordinary families, policymakers should develop support policies for difficult children, guide the formation of a reasonable dietary structure. Besides, enhancing family closeness and fostering family nurturing behaviours are the keys to promote the good academic development of children from difficult families.
| S-EPMC8932259 | biostudies-literature