The relationship between expressive language level and psychological                 development in children with autism 5 years of age

Pry, René; Petersen, Arne Friemuth; Baghdadli, Amaria

doi:10.1177/1362361305047222

Cited by 16 publications

(11 citation statements)

References 15 publications

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“…Delays in expressive language development, poor social use of language, and unusual speech patterns such as echolalia and dysfluences have been well established in children with autism [67][68][69][70][71] and in children with FXS [72][73][74][75][76]. However, comparatively few studies have compared language performance across both groups in the same study.…”

Section: Fragile X Syndrome and Autism: Converging And Diverging Cognmentioning

confidence: 99%

Fragile X Syndrome and Autism: Common Developmental Pathways?

Cornish¹,

Turk²,

Levitas

2007

CPR

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Identifying atypical trajectories that distinguish children with differing developmental disorders from each other and from typically developing children is a potentially powerful tool for early ascertainment and treatment of syndrome specific proficiencies and deficiencies. The past decade has seen unparalleled advances in the fields of molecular genetics, pediatrics, developmental cognitive neuroscience and brain imaging. Collaboratively, these advances have facilitated our understanding of how genes can impact upon early development, through the identification of specific patterns of cognitive and behavior processing and the deficits in these domains that are typical to a specific developmental disorder. These advances have also made early diagnoses possible for many developmental disorders, including those for which genetic etiology has yet to be determined, such as is the case for most individuals with autism, or disorders such as fragile X syndrome that result from the silencing of a single gene. This early identification necessitates thorough investigation of the impact of a condition across the lifespan beginning in early childhood when interventions are most likely to have significant benefit. This is especially relevant for disorders that at first glance appear to share overlapping behavioral and clinical symptomology. In the case of autism and fragile X syndrome, commonalties in social and communication profiles are now well documented in early childhood. However, to what degree symptom overlap implies common developmental pathways or etiologies remains unclear. The focus of this review will be to critically evaluate whether so called 'commonalities' in phenotypic outcomes actually reflect very different developmental pathways that diverge over developmental time and across syndromes. More detailed knowledge of these profiles will facilitate early timing of tailored interventions that will promote optimal development resulting in significant educational, clinical, and adaptive benefits across a child's lifespan.

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Section: Fragile X Syndrome and Autism: Converging And Diverging Cognmentioning

confidence: 99%

Fragile X Syndrome and Autism: Common Developmental Pathways?

Cornish¹,

Turk²,

Levitas

2007

CPR

View full text Add to dashboard Cite

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“…These measures generate two variables AgeEquCom and AgeEquAuton with values between 3 and 65. More information concerning materials and methods can be found in Pry et al [26]. This is a two-level data set with 3 observations per child.…”

Section: Application To Children With Autism Data Setmentioning

confidence: 99%

A mixture model-based approach to the clustering of exponential repeated data

Martinez¹,

Lavergne²,

Trottier³

2009

Journal of Multivariate Analysis

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International audienceThe analysis of finite mixture models for exponential repeated data is considered. The mixture components correspond to different unknown groups of the statistical units. Dependency and variability of repeated data are taken into account through random effects. For each component, an exponential mixed model is thus defined. When considering parameter estimation in this mixture of exponential mixed models, the EM-algorithm cannot be directly used since the marginal distribution of each mixture component cannot be analytically derived. In this paper, we propose two parameter estimation methods. The first one uses a linearisation specific to the exponential distribution hypothesis within each component. The second approach uses a Metropolis-Hastings algorithm as a building block of a general MCEM-algorith

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“…Furthermore, estimates of intellectual level based on global indicators, such as DQ or IQ, are rooted in normative concepts that are not very useful in pathological development. This lowers the diagnostic and prognostic power of these variables in the case of autism (25). In fact, there are no developmental studies of autistic children that focus on the impact of the specifics of each individual cognitive profile, or that address the extensive heterogeneity of autistics as reflected by their wide range of scores on psychometric tests.…”

Section: Introductionmentioning

confidence: 99%