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Prevention Science : the Official... Jan 2023The Early Intervention Parenting Partnerships (EIPP) program is a home visiting program that provides home visits, group services, assessments and screenings, and...
The Early Intervention Parenting Partnerships (EIPP) program is a home visiting program that provides home visits, group services, assessments and screenings, and referrals delivered by a multidisciplinary team to expectant parents and families with infants who experience socioeconomic barriers, emotional and behavioral health challenges, or other stressors. The present study examines whether EIPP successfully meets its aims of screening families for social and environmental factors that may increase the risk of children's developmental delays and connect them to the larger statewide early intervention (EI) system relative to families with similar background characteristics who do not receive EIPP. Coarsened exact matching was used to match EIPP participants who enrolled between 2013 and 2017 to a comparison group of families identified from birth certificates. Primary study outcomes including EI referrals, evaluations, and service receipt for children from 3 months to 3 years were measured using EI program data. Secondary outcomes included EI referral source, EI eligibility criteria (e.g., presence of biological, social, or environmental factors that may increase later risk for developmental delay), and information on service use. Impacts were assessed by fitting weighted regression models adjusted for preterm birth and maternal depression and substance use. EIPP participants were more likely than the comparison group to be referred to, evaluated for, and receive EI services. EIPP facilitated the identification of EI-eligible children who are at risk for developmental delays due to social or environmental factors, such as violence and substance use in the home, child protective services involvement, high levels of parenting stress, and parent chronic illness or disability. EIPP serves as an entry point into the EI system, helping families attain the comprehensive supports they may need to optimize their well-being and enhance children's development.
Topics: Child; Female; Humans; Infant; Infant, Newborn; Developmental Disabilities; Premature Birth; Risk Assessment; Parenting; Referral and Consultation
PubMed: 36272016
DOI: 10.1007/s11121-022-01453-6 -
Journal of Psychiatric Research Aug 2017To describe the frequency and characteristics of developmental regression in a sample of 50 patients with Phelan McDermid Syndrome (PMS) and investigate the possibility...
PURPOSE
To describe the frequency and characteristics of developmental regression in a sample of 50 patients with Phelan McDermid Syndrome (PMS) and investigate the possibility of association between regression, epilepsy, and electroencephalogram (EEG) abnormalities and deletion size.
METHODS
The Autism Diagnostic Interview-Revised (ADI-R) was used to evaluate regression in patients with a confirmed diagnosis of PMS. Information on seizure history and EEGs was obtained from medical record review. Deletion size was determined by DNA microarray.
RESULTS
A history of regression at any age was present in 43% of all patients. Among those exhibiting regression, 67% had onset after the age of 30 months, affecting primarily motor and self-help skills. In 63% of all patients there was a history of seizures and a history of abnormal EEG was also present in 71%. No significant associations were found between regression and seizures or EEG abnormalities. Deletion size was significantly associated with EEG abnormalities, but not with regression or seizures.
CONCLUSION
This study found a high rate of regression in PMS. In contrast to regression in autism, that often occurs earlier in development and affects language and social skills, we found regression in PMS most frequently has an onset in mid-childhood, affecting motor and self-help skills. We also found high rates of seizures and abnormal EEGs in patients with PMS. However, a history of abnormal EEG and seizures was not associated with an increased risk of regression. Larger deletion sizes were found to be significantly associated with a history of abnormal EEG.
Topics: Adolescent; Age of Onset; Child; Child, Preschool; Chromosome Deletion; Chromosome Disorders; Chromosomes, Human, Pair 22; Electroencephalography; Female; Genetic Association Studies; Humans; Infant; Infant, Newborn; Language; Male; Motor Skills; Regression, Psychology; Seizures; Young Adult
PubMed: 28346892
DOI: 10.1016/j.jpsychires.2017.03.010 -
NeuroImage Oct 2019Machine learning is increasingly being applied to neuroimaging data. However, most machine learning algorithms have not been designed to accommodate neuroimaging data,...
Machine learning is increasingly being applied to neuroimaging data. However, most machine learning algorithms have not been designed to accommodate neuroimaging data, which typically has many more data points than subjects, in addition to multicollinearity and low signal-to-noise. Consequently, the relative efficacy of different machine learning regression algorithms for different types of neuroimaging data are not known. Here, we sought to quantify the performance of a variety of machine learning algorithms for use with neuroimaging data with various sample sizes, feature set sizes, and predictor effect sizes. The contribution of additional machine learning techniques - embedded feature selection and bootstrap aggregation (bagging) - to model performance was also quantified. Five machine learning regression methods - Gaussian Process Regression, Multiple Kernel Learning, Kernel Ridge Regression, the Elastic Net and Random Forest, were examined with both real and simulated MRI data, and in comparison to standard multiple regression. The different machine learning regression algorithms produced varying results, which depended on sample size, feature set size, and predictor effect size. When the effect size was large, the Elastic Net, Kernel Ridge Regression and Gaussian Process Regression performed well at most sample sizes and feature set sizes. However, when the effect size was small, only the Elastic Net made accurate predictions, but this was limited to analyses with sample sizes greater than 400. Random Forest also produced a moderate performance for small effect sizes, but could do so across all sample sizes. Machine learning techniques also improved prediction accuracy for multiple regression. These data provide empirical evidence for the differential performance of various machines on neuroimaging data, which are dependent on number of sample size, features and effect size.
Topics: Brain; Humans; Machine Learning; Models, Theoretical; Neuroimaging; Reproducibility of Results
PubMed: 31173905
DOI: 10.1016/j.neuroimage.2019.05.082 -
BMJ Open May 2019We investigated the associations between Apgar scores at 1 and 5 min, across the entire range of score values, and child developmental health at 5 years of age.
OBJECTIVES
We investigated the associations between Apgar scores at 1 and 5 min, across the entire range of score values, and child developmental health at 5 years of age.
SETTING
British Columbia, Canada PARTICIPANTS: All singleton term infants without major congenital anomalies born between 1993 and 2009, who had a developmental assessment in kindergarten between 1999 and 2014.
MAIN OUTCOMES AND MEASURES
Developmental vulnerability on one or more domains of the Early Development Instrument and special needs requirements. Adjusted rate ratios (aRRs) and 95% CIs were estimated using log-linear regression.
RESULTS
Of the 150 081 children in the study, 45 334 (30.2%) were developmentally vulnerable and 3644 (2.5%) had special needs. There was an increasing trend in developmental vulnerability and special needs with decreasing 1 min and 5 min Apgar scores. Compared with children with an Apgar score of 10 at 5 min, the aRR for developmental vulnerability increased steadily with decreasing Apgar score from 1.02 (95% CI 1.00 to 1.04) for an Apgar score of 9 to 1.57 (95% CI 1.03 to 2.39) for an Apgar score of 2. Among children with 1 min Apgar scores in the 7-10 range, changes in Apgar scores between 1 and 5 min were associated with significant differences in developmental vulnerability. Compared with children who had an Apgar score of 9 at 1 min and 10 at 5 min, children with an Apgar score of 9 at both 1 and 5 min had higher rates of developmental vulnerability (aRR 1.03, 95% CI 1.01 to 1.05). Compared with infants with an Apgar of 10 at both 1 and 5 min, infants with a 1 min score of 10 and a 5 min score of <10 had higher rates of developmental vulnerability (aRR 1.53, 95% CI 1.08 to 2.17).
CONCLUSION
Risks of adverse developmental health and having special needs at 5 years of age are inversely associated with 1 min and 5 min Apgar scores across their entire range.
Topics: Apgar Score; British Columbia; Child Development; Child Health; Child, Preschool; Cohort Studies; Developmental Disabilities; Female; Humans; Infant, Newborn; Linear Models; Male; Risk Assessment; Risk Factors
PubMed: 31072859
DOI: 10.1136/bmjopen-2018-027655 -
The Clinical Neuropsychologist Jul 2022: Autism spectrum disorder (ASD) in very young children with significant cognitive impairment is difficult to diagnose, depriving them of the earliest opportunities for...
: Autism spectrum disorder (ASD) in very young children with significant cognitive impairment is difficult to diagnose, depriving them of the earliest opportunities for autism-specific intervention. This study delineated specific symptoms in this group, compared to symptoms in children with Global Developmental Delay (GDD) and in ASD with milder developmental delays.: Autism Diagnostic Observation Schedule, 2nd Edition, Toddler Module revealed symptoms in three groups of toddlers, with mean ages of 17-20 months: (1) ASD and cognitive/language functioning below the 12-month level (ASD-MA < 12 mos; = 28), (2) GDD ( = 27), and (3) ASD and cognitive/language functioning at or above the 12-month level (ASD-MA ≥ 12 mos; = 29). Logistic regression models were fit to control for developmental level. : Items in all domains (social interaction, communication, repetitive movements) discriminated ASD-MA < 12 mos from GDD. The two ASD groups, matched for age but differing on developmental level, showed strikingly similar ASD symptomatology. Conclusion: ADOS-2 symptoms differentiated ASD-MA < 12 mos from GDD, after controlling for cognitive impairment. Symptoms in the two ASD groups were minimally related to developmental level. The ADOS-2 Toddler Module successfully captured ASD symptomatology even in children whose developmental level was below the recommended ADOS-2 cutoff of 12 months, which may increase their access to early ASD-specific intervention.
Topics: Autism Spectrum Disorder; Child, Preschool; Cognition; Humans; Infant; Intelligence; Logistic Models; Neuropsychological Tests
PubMed: 34762009
DOI: 10.1080/13854046.2021.1998634 -
Epilepsia Aug 2009The significant morbidity linked to epileptic encephalopathies of childhood has prompted the need to identify and dissect the factors and mechanisms that contribute to... (Comparative Study)
Comparative Study Review
The significant morbidity linked to epileptic encephalopathies of childhood has prompted the need to identify and dissect the factors and mechanisms that contribute to the resultant functional regression. Although experiments specifically assessing language in rodents are difficult to design, a number of studies have shed light on the conditions that contribute to the functional deterioration. In particular, interictal spikes and seizures, especially if prolonged or frequent, may cause acute or long-lasting effects on brain functioning and development, which may impair performance in a variety of behavioral tests. These effects are further modified by a number of genetic, biological, and epigenetic factors, including age, sex, and underlying pathology, which further diversify outcome. Of special importance is the developmental age when the epileptic disorder manifests, because it may dictate outcome but also may be a deciding factor in selecting appropriate therapies.
Topics: Age Factors; Animals; Brain; Child, Preschool; Cognition Disorders; Developmental Disabilities; Disease Models, Animal; Electroencephalography; Epigenesis, Genetic; Epilepsy; Humans; Infant; Infant, Newborn; Seizures; Spasms, Infantile; Status Epilepticus; Substantia Nigra; gamma-Aminobutyric Acid
PubMed: 19682049
DOI: 10.1111/j.1528-1167.2009.02217.x -
Health and Quality of Life Outcomes Jul 2023The level of child development may be associated with the risk of poor maternal health-related quality of life (HRQoL). The objective of this study was to describe the...
Health-related quality of life of mothers and developmental characteristics of very low birth weight children at 2.5 years of age: results from the Japan Environment and Children's Study (JECS).
BACKGROUND
The level of child development may be associated with the risk of poor maternal health-related quality of life (HRQoL). The objective of this study was to describe the developmental characteristics of very low birth weight (VLBW) children at 2.5 years of age and to examine associations between maternal HRQoL and the degree of child development based on the Japanese version of Ages and Stages Questionnaire (J-ASQ-3).
METHODS
A cross-sectional study was performed using the data from a nationwide prospective birth cohort study in Japan. Among a total of 104,062 fetal records, the VLBW infants (birth weight ≤ 1500 g) were analyzed using linear regression models, adjusted for potential covariates. Subgroup analysis was also conducted to assess the association between social connection or cooperation of the partner and maternal HRQoL by the level of child development.
RESULTS
The final study subjects included 357 VLBW children and mothers. The suspected developmental delays (SDDs) in at least two domains was significantly associated with lower maternal mental HRQoL regression coefficient -2.314 (95%CI: -4.065 to -0.564). There was no association between the status of child development and maternal physical HRQoL. After adjusting for child and maternal covariates, the maternal HRQoL was not significantly associated with child development. Amongst women who indicated having some social support, having a child with a SDD in two or more domains was negatively associated with mental HRQoL compared with women whose child was less developmental delay, regression coefficient -2.337 (95%CI: -3.961 to -0.714). Amongst women who indicated having partner's cooperation to child-rearing, having a child with a SDD in two or more domains was negatively associated with mental HRQoL compared with women whose child was less developmental delay, regression coefficient -3.785 (95%CI: -6.647 to -0.924).
CONCLUSIONS
Our findings indicate that the lower maternal mental HRQoL was independently associated with the SDDs evaluated by the J-ASQ-3, whereas there was no association after adjusting for covariates. Further research is warranted to elucidate the impact of social connection and partner's cooperation on maternal HRQoL and child development. This study urges that particular attention should be paid to mothers of VLBW children with SDDs and also to provide early intervention and continued support.
Topics: Infant; Infant, Newborn; Humans; Female; Mothers; Cohort Studies; Cross-Sectional Studies; Japan; Prospective Studies; Quality of Life; Infant, Very Low Birth Weight
PubMed: 37430264
DOI: 10.1186/s12955-023-02156-4 -
Journal of Pediatric Psychology Jun 2019The aim is to investigate if young children with developmental and behavioral difficulties (DBDs) have greater risk of peer-victimization compared with typically...
OBJECTIVE
The aim is to investigate if young children with developmental and behavioral difficulties (DBDs) have greater risk of peer-victimization compared with typically developing (TD) children.
METHOD
The sample was drawn from the Norwegian Mother and Child Cohort Study (MoBa). MoBa has collected population-based data on children's health and development for 114,500 children. We included children that were 5 years of age (n = 41,609). Multivariate logistic regression was used to estimate the effect of different DBDs and of co-occurring DBDs on peer-victimization compared with TD children. Categories of DBDs included autistic traits, emotional difficulties, behavioral difficulties, general learning difficulties, attention difficulties/impulsive behavior, motor development difficulties, language difficulties, and hearing and vision difficulties. Results were adjusted for socioeconomic status and the child's sex.
RESULTS
Peer-victimization was 2.8% (933) among TD children, and 8.0% (615) among children with DBD. The highest risk of peer-victimization was found among children with autistic traits and children with five or more co-occurring DBDs (adjusted odds ratios [ORs] = 12.76; 95% confidence interval [CI] 8.64-18.84; p ≤ .001) and 17.37 (95% CI 12.15-24.82; p ≤ .001)], respectively. The lowest risk was found among children with hearing and vision difficulties and children with only one DBD [adjusted ORs = 1.98 (95% CI 1.71-2.29; p ≤ .001) and 1.95 (95% CI 1.70-2.22; p ≤ .001)].
CONCLUSION
Children with DBD have a substantially higher risk of peer-victimization compared with TD children. Peer-victimization varies with type of DBD and increases cumulatively by number of DBDs.
Topics: Bullying; Child Behavior Disorders; Child, Preschool; Cohort Studies; Crime Victims; Developmental Disabilities; Female; Humans; Male; Norway; Peer Group; Prospective Studies; Risk Factors
PubMed: 30816959
DOI: 10.1093/jpepsy/jsy112 -
Sleep Oct 2021Structural brain maturation and sleep are complex processes that exhibit significant changes over adolescence and are linked to many physical and mental health outcomes....
STUDY OBJECTIVES
Structural brain maturation and sleep are complex processes that exhibit significant changes over adolescence and are linked to many physical and mental health outcomes. We investigated whether sleep-gray matter relationships are developmentally invariant (i.e. stable across age) or developmentally specific (i.e. only present during discrete time windows) from late childhood through young adulthood.
METHODS
We constructed the Neuroimaging and Pediatric Sleep Databank from eight research studies conducted at the University of Pittsburgh (2009-2020). Participants completed a T1-weighted structural MRI scan (sMRI) and 5-7 days of wrist actigraphy to assess naturalistic sleep. The final analytic sample consisted of 225 participants without current psychiatric diagnoses (9-25 years). We extracted cortical thickness and subcortical volumes from sMRI. Sleep patterns (duration, timing, continuity, regularity) were estimated from wrist actigraphy. Using regularized regression, we examined cross-sectional associations between sMRI measures and sleep patterns, as well as the effects of age, sex, and their interaction with sMRI measures on sleep.
RESULTS
Shorter sleep duration, later sleep timing, and poorer sleep continuity were associated with thinner cortex and altered subcortical volumes in diverse brain regions across adolescence. In a discrete subset of regions (e.g. posterior cingulate), thinner cortex was associated with these sleep patterns from late childhood through early-to-mid adolescence but not in late adolescence and young adulthood.
CONCLUSIONS
In childhood and adolescence, developmentally invariant and developmentally specific associations exist between sleep patterns and gray matter structure, across brain regions linked to sensory, cognitive, and emotional processes. Sleep intervention during specific developmental periods could potentially promote healthier neurodevelopmental outcomes.
Topics: Adolescent; Adolescent Development; Adult; Brain; Child; Cross-Sectional Studies; Gray Matter; Humans; Magnetic Resonance Imaging; Sleep; Young Adult
PubMed: 33971013
DOI: 10.1093/sleep/zsab120 -
Frontiers in Pediatrics 2021Given the profound inequities in maternal and child health along racial, ethnic, and socioeconomic lines, strength-based, community-partnered research is required to...
THRIVE Conceptual Framework and Study Protocol: A Community-Partnered Longitudinal Multi-Cohort Study to Promote Child and Youth Thriving, Health Equity, and Community Strength.
BACKGROUND
Given the profound inequities in maternal and child health along racial, ethnic, and socioeconomic lines, strength-based, community-partnered research is required to foster thriving children, families, and communities, where thriving is defined as optimal development across physical, mental, cognitive, and social domains. The Pittsburgh Study (TPS) is a community-partnered, multi-cohort study designed to understand and promote child and youth thriving, build health equity, and strengthen communities by integrating community partners in study design, implementation, and dissemination. TPS launched the Tracking Health, Relationships, Identity, EnVironment, and Equity (THRIVE) Study to evaluate children's developmental stages and contexts from birth through completion of high school and to inform a child health data hub accessible to advocates, community members, educators, health professionals, and policymakers.
METHODS AND ANALYSIS
TPS is rooted in community-partnered participatory research (CPPR), health equity, antiracism, and developmental science. Using our community-informed conceptual framework of child thriving, the THRIVE Study will assess cross-cutting measures of place, environment, health service use, and other social determinants of health to provide longitudinal associations with developmentally appropriate child and youth thriving outcomes across participants in six cohorts spanning from pregnancy through adolescence (child ages 0-18 years). Data from electronic health records, school records, and health and human services use are integrated to assess biological and social influences of thriving. We will examine changes over time using paired -tests and adjusted linear regression models for continuous thriving scores and McNemar tests and adjusted logistic regression models for categorical outcomes (thriving/not thriving). Data analyses will include mixed models with a random intercept (in combination with the previously-specified types of regression models) to account for within-subject correlation.
DISCUSSION
By enhancing assessment of child and youth well-being, TPS will fill critical gaps in our understanding of the development of child and youth thriving over time and test strategies to support thriving in diverse communities and populations. Through CPPR and co-design, the study aims to improve child health inequities across multiple socioecological levels and developmental domains.
PubMed: 35186824
DOI: 10.3389/fped.2021.797526