ABSTRACT
Comprehensive data on the developmental history and current behaviours of a large sample of high-functioning individuals with diagnoses of autism, Asperger's syndrome, or other related disorder were collected via parent interviews. This provided the basis for a taxonomic analysis to search for subgroups. Most participants also completed theory of mind tasks. Three clusters or subgroups were obtained; these differed on theory of mind performance and on verbal abilities. Although subgroups were identified which bore some relationship to clinical differentiation of autistic, Asperger syndrome, and Pervasive Developmental Disorder Not Otherwise Specified (PDD-NOS) cases, the nature of the differences between them appeared strongly related to ability variables. Examination of the kinds of behaviours that differentiated the groups suggested that a spectrum of autistic disorders on which children differ primarily in term of degrees of social and cognitive impairments could explain the findings.
Subject(s)
Autistic Disorder/diagnosis , Adolescent , Adult , Child , Child, Preschool , Cluster Analysis , Diagnosis, Differential , Female , Humans , MaleABSTRACT
DSM-IV states that Asperger Disorder may be distinguished from Autistic Disorder by a lack of a delay in early language development. The aim of this study was to establish whether the presence or absence of early language delay would predict autistic symptomatology in children diagnosed with a PDD/autism spectrum disorder. Forty-six language-delayed and 62 normal language onset individuals (M age 11 years) were compared on ICD-10 research criteria and DSM-IV criteria, receptive language, and developmental history variables. Retrospective data were also obtained to determine whether language onset predicted autism symptomatology when young (< 6 years). We found that early language delay predicts more autistic symptomatology when young, but not at an older age. Early language delay is also associated with developmental motor milestone delays and lower receptive language abilities. The results question the use of early language delay as a valid discriminating variable between PDD subgroups.
Subject(s)
Autistic Disorder/diagnosis , Child Development Disorders, Pervasive/diagnosis , Language Development Disorders/diagnosis , Adolescent , Autistic Disorder/psychology , Child , Child Development Disorders, Pervasive/psychology , Child, Preschool , Diagnosis, Differential , Female , Humans , Language Development Disorders/psychology , Male , Prognosis , Psychiatric Status Rating Scales , Psychomotor Disorders/diagnosis , Psychomotor Disorders/psychology , SyndromeABSTRACT
Within the context of a longitudinal study investigating outcome for children following traumatic brain injury, this paper reports on the utility of neuropsychological testing in predicting academic outcome in children 2 years following traumatic brain injury (TBI). Twenty-nine school-age children who were admitted to hospital after TBI were assessed with a battery of neuropsychological and academic measures at 3 and 24 months postinjury. The neuropsychological battery included measures of memory, learning, and speed of information processing. Academic outcome was assessed in terms of post-TBI change in school placement. According to logistic regression analysis, change in placement from regular to special education at 2 years post-TBI was predicted by injury severity and by neuropsychological performance at 3 months post-TBI. Findings suggest that neuropsychological testing is useful in identifying children with special educational needs subsequent to TBI.
Subject(s)
Brain Injuries/complications , Cognition Disorders/diagnosis , Education, Special , Neuropsychological Tests/standards , Adolescent , Chi-Square Distribution , Child , Cognition Disorders/etiology , Female , Follow-Up Studies , Forecasting , Glasgow Coma Scale , Humans , Logistic Models , Male , PrognosisABSTRACT
OBJECTIVE: To determine what clinical symptoms clinicians have been using to distinguish between Asperger's disorder (AsD) and autistic disorder (AD). METHOD: Parents of children and adolescents with high-functioning AD (n = 48) and AsD (n = 69) were given a structured interview based on DSM-III-R and ICD-10 diagnostic criteria. Information regarding early and current symptom presentation and family, developmental, and verbal mental age information were collected. Logistic regression analyses were conducted to determine which variables best predicted clinician's diagnosis. RESULTS: A number of clinical variables predicted diagnosis. Delayed language onset was the only variable of the family and developmental variables that predicted diagnosis. The AsD group was also significantly higher than the AD group in verbal mental age. CONCLUSION: Clinicians appear to be diagnosing AsD and AD on the basis of published research and case study accounts. The findings question whether DSM-IV and ICD-10 criteria adequately describe the AsD individual, particularly in the communication domain.
Subject(s)
Autistic Disorder/diagnosis , Adolescent , Adult , Autistic Disorder/classification , Autistic Disorder/genetics , Autistic Disorder/psychology , Child , Diagnosis, Differential , Female , Humans , Male , Personality Assessment , Psychiatric Status Rating Scales , Risk Factors , SyndromeABSTRACT
Evaluated the utility of neuropsychological testing in predicting academic outcome in children 1 year following traumatic brain injury (TBI). Fifty-one school age children who were admitted to hospital after TBI were assessed with a battery of neuropsychological measures at 3 months postinjury. Academic achievement was assessed at 3 and 12 months postinjury. The neuropsychological battery included intelligence testing and measures of memory, learning, and speed of information processing. Academic outcome was assessed in terms of post-TBI changes in reading, spelling, and arithmetic; changes in teacher ratings of school performance; and change in school placement. According to logistic regression analysis, change in placement from regular to special education at 1-year post-TBI was predicted by injury severity and by neuropsychological performance at 3 months post-TBI. Findings suggest that neuropsychological testing is useful in identifying children with special educational needs subsequent to TBI.
