Do reciprocal associations exist between social and language pathways in preschoolers with autism spectrum disorders? / Teresa BENNETT in Journal of Child Psychology and Psychiatry, 56-8 (August 2015)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 56-8 (August 2015) . - p.874-883 Titre : Do reciprocal associations exist between social and language pathways in preschoolers with autism spectrum disorders? Type de document : Texte imprimé et/ou numérique Auteurs : Teresa BENNETT, Auteur ; Peter SZATMARI, Auteur ; Katholiki GEORGIADES, Auteur ; Steven HANNA, Auteur ; Magdelena JANUS, Auteur ; Stelios GEORGIADES, Auteur ; Eric DUKU, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Isabel M. SMITH, Auteur ; Pat MIRENDA, Auteur ; Joanne VOLDEN, Auteur ; Charlotte WADDELL, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Mayada ELSABBAGH, Auteur ; Ann THOMPSON, Auteur ; THE PATHWAYS IN A. S. D. STUDY TEAM,, Auteur Article en page(s) : p.874-883 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder  social development  language  epidemiology  reciprocal effects model Index. décimale : PER Périodiques Résumé : Background Differences in how developmental pathways interact dynamically in children with autism spectrum disorder (ASD) likely contribute in important ways to phenotypic heterogeneity. This study aimed to model longitudinal reciprocal associations between social competence (SOC) and language (LANG) pathways in young children with ASD. Methods Data were obtained from 365 participants aged 2–4 years who had recently been diagnosed with an ASD and who were followed over three time points: baseline (time of diagnosis), 6- and 12 months later. Using structural equation modeling, a cross-lagged reciprocal effects model was developed that incorporated auto-regressive (stability) paths for SOC (using the Socialization subscale of the Vineland Adaptive Behavior Scales-2) and LANG (using the Preschool Language Scale-4 Auditory Comprehension subscale). Cross-domain associations included within-time correlations and lagged associations. Results SOC and LANG were highly stable over 12 months. Small reciprocal cross-lagged associations were found across most time points and within-time correlations decreased over time. There were no differences in strength of cross-lagged associations between SOC-LANG and LANG-SOC across time points. Few differences were found between subgroups of children with ASD with and without cognitive impairment. Conclusions Longitudinal reciprocal cross-domain associations between social competence and language were small in this sample of young children with ASD. Instead, a pattern emerged to suggest that the two domains were strongly associated around time of diagnosis in preschoolers with ASD, and then appeared to become more independent over the ensuing 12 months. En ligne : http://dx.doi.org/10.1111/jcpp.12356 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=263 [article] Do reciprocal associations exist between social and language pathways in preschoolers with autism spectrum disorders? [Texte imprimé et/ou numérique] / Teresa BENNETT, Auteur ; Peter SZATMARI, Auteur ; Katholiki GEORGIADES, Auteur ; Steven HANNA, Auteur ; Magdelena JANUS, Auteur ; Stelios GEORGIADES, Auteur ; Eric DUKU, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Isabel M. SMITH, Auteur ; Pat MIRENDA, Auteur ; Joanne VOLDEN, Auteur ; Charlotte WADDELL, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Mayada ELSABBAGH, Auteur ; Ann THOMPSON, Auteur ; THE PATHWAYS IN A. S. D. STUDY TEAM,, Auteur . - p.874-883. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 56-8 (August 2015) . - p.874-883 Mots-clés : Autism spectrum disorder  social development  language  epidemiology  reciprocal effects model Index. décimale : PER Périodiques Résumé : Background Differences in how developmental pathways interact dynamically in children with autism spectrum disorder (ASD) likely contribute in important ways to phenotypic heterogeneity. This study aimed to model longitudinal reciprocal associations between social competence (SOC) and language (LANG) pathways in young children with ASD. Methods Data were obtained from 365 participants aged 2–4 years who had recently been diagnosed with an ASD and who were followed over three time points: baseline (time of diagnosis), 6- and 12 months later. Using structural equation modeling, a cross-lagged reciprocal effects model was developed that incorporated auto-regressive (stability) paths for SOC (using the Socialization subscale of the Vineland Adaptive Behavior Scales-2) and LANG (using the Preschool Language Scale-4 Auditory Comprehension subscale). Cross-domain associations included within-time correlations and lagged associations. Results SOC and LANG were highly stable over 12 months. Small reciprocal cross-lagged associations were found across most time points and within-time correlations decreased over time. There were no differences in strength of cross-lagged associations between SOC-LANG and LANG-SOC across time points. Few differences were found between subgroups of children with ASD with and without cognitive impairment. Conclusions Longitudinal reciprocal cross-domain associations between social competence and language were small in this sample of young children with ASD. Instead, a pattern emerged to suggest that the two domains were strongly associated around time of diagnosis in preschoolers with ASD, and then appeared to become more independent over the ensuing 12 months. En ligne : http://dx.doi.org/10.1111/jcpp.12356 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=263

Investigating phenotypic heterogeneity in children with autism spectrum disorder: a factor mixture modeling approach / Stelios GEORGIADES in Journal of Child Psychology and Psychiatry, 54-2 (February 2013)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 54-2 (February 2013) . - p.206-215 Titre : Investigating phenotypic heterogeneity in children with autism spectrum disorder: a factor mixture modeling approach Type de document : Texte imprimé et/ou numérique Auteurs : Stelios GEORGIADES, Auteur ; Peter SZATMARI, Auteur ; Michael H. BOYLE, Auteur ; Steven HANNA, Auteur ; Eric DUKU, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Joanne VOLDEN, Auteur ; Pat MIRENDA, Auteur ; Isabel M. SMITH, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Charlotte WADDELL, Auteur ; Teresa BENNETT, Auteur ; Ann THOMPSON, Auteur ; PATHWAYS IN A. S. D. STUDY TEAM, Auteur Année de publication : 2013 Article en page(s) : p.206-215 Langues : Anglais (eng) Mots-clés : Symptomatology  Autistic disorder  Classification  Diagnosis  DSM Index. décimale : PER Périodiques Résumé : Background: Autism spectrum disorder (ASD) is characterized by notable phenotypic heterogeneity, which is often viewed as an obstacle to the study of its etiology, diagnosis, treatment, and prognosis. On the basis of empirical evidence, instead of three binary categories, the upcoming edition of the DSM 5 will use two dimensions – social communication deficits (SCD) and fixated interests and repetitive behaviors (FIRB) – for the ASD diagnostic criteria. Building on this proposed DSM 5 model, it would be useful to consider whether empirical data on the SCD and FIRB dimensions can be used within the novel methodological framework of Factor Mixture Modeling (FMM) to stratify children with ASD into more homogeneous subgroups. Methods: The study sample consisted of 391 newly diagnosed children (mean age 38.3 months; 330 males) with ASD. To derive subgroups, data from the Autism Diagnostic Interview-Revised indexing SCD and FIRB were used in FMM; FMM allows the examination of continuous dimensions and latent classes (i.e., categories) using both factor analysis (FA) and latent class analysis (LCA) as part of a single analytic framework. Results: Competing LCA, FA, and FMM models were fit to the data. On the basis of a set of goodness-of-fit criteria, a ‘two-factor/three-class' factor mixture model provided the overall best fit to the data. This model describes ASD using three subgroups/classes (Class 1: 34%, Class 2: 10%, Class 3: 56% of the sample) based on differential severity gradients on the SCD and FIRB symptom dimensions. In addition to having different symptom severity levels, children from these subgroups were diagnosed at different ages and were functioning at different adaptive, language, and cognitive levels. Conclusions: Study findings suggest that the two symptom dimensions of SCD and FIRB proposed for the DSM 5 can be used in FMM to stratify children with ASD empirically into three relatively homogeneous subgroups. En ligne : http://dx.doi.org/10.1111/j.1469-7610.2012.02588.x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=188 [article] Investigating phenotypic heterogeneity in children with autism spectrum disorder: a factor mixture modeling approach [Texte imprimé et/ou numérique] / Stelios GEORGIADES, Auteur ; Peter SZATMARI, Auteur ; Michael H. BOYLE, Auteur ; Steven HANNA, Auteur ; Eric DUKU, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Joanne VOLDEN, Auteur ; Pat MIRENDA, Auteur ; Isabel M. SMITH, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Charlotte WADDELL, Auteur ; Teresa BENNETT, Auteur ; Ann THOMPSON, Auteur ; PATHWAYS IN A. S. D. STUDY TEAM, Auteur . - 2013 . - p.206-215. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 54-2 (February 2013) . - p.206-215 Mots-clés : Symptomatology  Autistic disorder  Classification  Diagnosis  DSM Index. décimale : PER Périodiques Résumé : Background: Autism spectrum disorder (ASD) is characterized by notable phenotypic heterogeneity, which is often viewed as an obstacle to the study of its etiology, diagnosis, treatment, and prognosis. On the basis of empirical evidence, instead of three binary categories, the upcoming edition of the DSM 5 will use two dimensions – social communication deficits (SCD) and fixated interests and repetitive behaviors (FIRB) – for the ASD diagnostic criteria. Building on this proposed DSM 5 model, it would be useful to consider whether empirical data on the SCD and FIRB dimensions can be used within the novel methodological framework of Factor Mixture Modeling (FMM) to stratify children with ASD into more homogeneous subgroups. Methods: The study sample consisted of 391 newly diagnosed children (mean age 38.3 months; 330 males) with ASD. To derive subgroups, data from the Autism Diagnostic Interview-Revised indexing SCD and FIRB were used in FMM; FMM allows the examination of continuous dimensions and latent classes (i.e., categories) using both factor analysis (FA) and latent class analysis (LCA) as part of a single analytic framework. Results: Competing LCA, FA, and FMM models were fit to the data. On the basis of a set of goodness-of-fit criteria, a ‘two-factor/three-class' factor mixture model provided the overall best fit to the data. This model describes ASD using three subgroups/classes (Class 1: 34%, Class 2: 10%, Class 3: 56% of the sample) based on differential severity gradients on the SCD and FIRB symptom dimensions. In addition to having different symptom severity levels, children from these subgroups were diagnosed at different ages and were functioning at different adaptive, language, and cognitive levels. Conclusions: Study findings suggest that the two symptom dimensions of SCD and FIRB proposed for the DSM 5 can be used in FMM to stratify children with ASD empirically into three relatively homogeneous subgroups. En ligne : http://dx.doi.org/10.1111/j.1469-7610.2012.02588.x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=188

Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6 / Stelios GEORGIADES in Journal of Autism and Developmental Disorders, 44-12 (December 2014)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 44-12 (December 2014) . - p.3045-3055 Titre : Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6 Type de document : Texte imprimé et/ou numérique Auteurs : Stelios GEORGIADES, Auteur ; Michael H. BOYLE, Auteur ; Peter SZATMARI, Auteur ; Steven HANNA, Auteur ; Eric DUKU, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Joanne VOLDEN, Auteur ; Pat MIRENDA, Auteur ; Isabel SMITH, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Charlotte WADDELL, Auteur ; Teresa BENNETT, Auteur ; Mayada ELSABBAGH, Auteur ; Ann THOMPSON, Auteur Article en page(s) : p.3045-3055 Langues : Anglais (eng) Mots-clés : Autism symptoms  Classification  Phenotypic heterogeneity Index. décimale : PER Périodiques Résumé : The latent class structure of autism symptoms from the time of diagnosis to age 6 years was examined in a sample of 280 children with autism spectrum disorder. Factor mixture modeling was performed on 26 algorithm items from the Autism Diagnostic Interview - Revised at diagnosis (Time 1) and again at age 6 (Time 2). At Time 1, a “2-factor/3-class” model provided the best fit to the data. At Time 2, a “2-factor/2-class” model provided the best fit to the data. Longitudinal (repeated measures) analysis of variance showed that the “2-factor/3-class” model derived at the time of diagnosis allows for the identification of a subgroup of children (9 % of sample) who exhibit notable reduction in symptom severity. En ligne : http://dx.doi.org/10.1007/s10803-014-2167-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=243 [article] Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6 [Texte imprimé et/ou numérique] / Stelios GEORGIADES, Auteur ; Michael H. BOYLE, Auteur ; Peter SZATMARI, Auteur ; Steven HANNA, Auteur ; Eric DUKU, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Susan E. BRYSON, Auteur ; Eric FOMBONNE, Auteur ; Joanne VOLDEN, Auteur ; Pat MIRENDA, Auteur ; Isabel SMITH, Auteur ; Wendy ROBERTS, Auteur ; Tracy VAILLANCOURT, Auteur ; Charlotte WADDELL, Auteur ; Teresa BENNETT, Auteur ; Mayada ELSABBAGH, Auteur ; Ann THOMPSON, Auteur . - p.3045-3055. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 44-12 (December 2014) . - p.3045-3055 Mots-clés : Autism symptoms  Classification  Phenotypic heterogeneity Index. décimale : PER Périodiques Résumé : The latent class structure of autism symptoms from the time of diagnosis to age 6 years was examined in a sample of 280 children with autism spectrum disorder. Factor mixture modeling was performed on 26 algorithm items from the Autism Diagnostic Interview - Revised at diagnosis (Time 1) and again at age 6 (Time 2). At Time 1, a “2-factor/3-class” model provided the best fit to the data. At Time 2, a “2-factor/2-class” model provided the best fit to the data. Longitudinal (repeated measures) analysis of variance showed that the “2-factor/3-class” model derived at the time of diagnosis allows for the identification of a subgroup of children (9 % of sample) who exhibit notable reduction in symptom severity. En ligne : http://dx.doi.org/10.1007/s10803-014-2167-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=243

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