Autism Spectrum Disorder
Conditions
Brief summary
The goals of this diagnostic study are to determine how accurate general pediatricians are in autism spectrum disorder (ASD) diagnostic assessment and which children might be best suited for this type of assessment. The investigators will also evaluate the use of a new virtual diagnostic tool, the Autism Assessment for Preschoolers with Language Element Sequence (AAPLES). The investigators will recruit twenty general pediatricians from across Ontario, Canada, as well as 200 of their patients (maximum 10 per pediatrician) who have been referred with possible ASD. The general pediatrician will complete their assessment and decide on a diagnosis, but will not tell the family. The ASD expert team, consisting of a developmental paediatrician and a psychologist, will also perform a diagnostic assessment without knowing the general pediatrician's opinion. The team will inform the family of their diagnostic opinion. Investigators will determine the diagnostic agreement between the two assessments. They will then determine which of the child's characteristics (age, sex, racial/ethnic background, ASD features, developmental delays, having a sibling with ASD) predict agreement in diagnosis. Some children in the study will have the option of undergoing an additional virtual autism diagnostic assessment using the AAPLES. The clinician administering the AAPLES will not know the results of the other assessments. The investigators will measure diagnostic agreement between the clinician administering the AAPLES and the expert team.
Detailed description
Increasing rates of autism spectrum disorder (ASD) diagnosis have contributed to lengthy waits for expert diagnostic assessment that negatively impact ASD outcomes. Many ASD diagnostic guidelines state that an expert team is needed to make the diagnosis; although some children currently receive their diagnosis from a community-based clinician, e.g. a general paediatrician. There are very few studies of the accuracy of general pediatricians in diagnosing ASD. The aims of this project are to: 1. determine accuracy of general pediatrician ASD diagnosis compared to an expert team assessment; 2. to determine child features associated with accurate diagnosis by general pediatricians (possible features include: child's age; gender; cultural background; ASD features; developmental delays; and having a sibling with ASD; pediatrician certainty; virtual versus in person assessment); 3. to identify general pediatrician factors associated with accurate diagnosis (possible features include pediatrician years in practice, gender, rurality, extra training in child development, use of tools in the assessment, time spent on the assessment); 4. to determine the concordance between an assessment with the AAPLES virtual tool and the expert team assessment. Investigators will recruit twenty general pediatricians from across Ontario, as well as 200 of their patients (10 per general pediatrician) who have been referred with possible ASD. The general pediatrician will complete their assessment and decide on a diagnosis, but will not tell the family. The ASD expert team, consisting of a developmental paediatrician and a psychologist, will also perform a diagnostic assessment without knowing the general pediatrician's opinion. The team will inform the family of their diagnostic opinion. Investigators will determine the diagnostic agreement between the two assessments. They will then determine which of the child's characteristics (age, sex, cultural background, ASD severity, developmental delays, having a sibling with ASD) predict agreement in diagnosis. Exploratory analyses will be done on pediatrician factors associated with diagnostic accuracy, analyzing pediatrician years in practice, gender, rurality, extra training in child development, use of tools in the assessment, and time spent on the assessment. Children meeting the criteria for the AAPLES will be offered an additional virtual assessment where a trained clinician, blinded to the previous assessment results, will administer the AAPLES and record their diagnostic opinion. Investigators will measure agreement between this opinion and the expert team.
Interventions
General pediatricians will assess children for possible autism spectrum disorder diagnosis as they usually would (i.e. no specific tests will be required).
The multidisciplinary team will assess children for possible autism spectrum disorder diagnosis. The team consists of a developmental pediatrician, a psychologist, and a psychometrist. Administered tests include the Autism Diagnostic Interview - Revised (ADI-R; a developmental history will be substituted for children with a developmental age of \<18 months), the Autism Diagnostic Observation Schedule (ADOS), and the Mullen Scales of Early Learning. When needed and available, the team will call a preschool or school teacher to gather more information about the child.
The AAPLES was developed at the Glenrose/Holland Bloorview and is designed for children who have flexible phrase speech. The assessment will be conducted virtually over Zoom Health by a trained clinician. This tool involves coaching the caregiver to interact with the child in specific ways to allow a trained professional to observe for features of ASD while watching remotely. It should take about 30-45 minutes. The individual who conducts the assessment will be blinded to the results of the other assessments. This virtual assessment will occur after the other assessments have been completed so as to not delay the child receiving a potential diagnosis.
Sponsors
Study design
Eligibility
Inclusion criteria
Child Inclusion Criteria: * Must be referred to a general pediatrician participating in the study with any of the following issues: 1) Failed 18-month developmental screen (other than isolated motor delay); 2) Speech/language delay; 3) Social/emotional delay/concern; 4) Behavioral concerns, inattention, hyperactivity, or impulsivity; 5) Global developmental delay/concern; 6) A referral with a query of ASD. * Age \<5 years 6 months * Resident of Ontario, Canada (support for travel is available for participants who live \>100 km from Toronto)
Exclusion criteria
* Child has already received a diagnosis of ASD For the AAPLES exploratory objective: Inclusion Criteria: * Child has a developmental age of 36 months or more (determined on Mullen Scales of Early Learning) * Child has flexible phrase speech
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy measures | Within 6 weeks | Sensitivity, specificity, positive predictive value, negative predictive value, kappa |
Other
| Measure | Time frame | Description |
|---|---|---|
| Child-level predictors of accurate assessment | Within 6 weeks | Investigators will conduct a logistic regression to determine the odds ratio of accurate assessment (agreement between general pediatrician and multi-disciplinary team) for each of the following factors: child age, gender, racial/ethnic background, ASD features (ADOS composite score), developmental level (Mullen Scales of Early Learning Visual Reception T-score), having an autistic sibling, pediatrician certainty (5-point Likert scale), and virtual versus in-person assessment. Regression models will be run for each of: 1) children diagnosed with ASD by the multi-disciplinary team; and 2) children not diagnosed with ASD by the multi-disciplinary team. |
| General pediatrician predictors of accurate assessment (exploratory) | Within 6 weeks | Investigators will conduct a regression measuring the association between general pediatrician correct classification rate (number of children correctly diagnosed out of total number assessed) and general pediatrician gender, years in practice, practice location, extra training in child development, use of tools in the assessment, and time spent on the assessment. |
| AAPLES accuracy measures (exploratory) | Within 6 weeks | Comparing the diagnostic opinion of the assessor completing the AAPLES with the multi-disciplinary team, measuring sensitivity, specificity, positive predictive value, negative predictive value, kappa |
Countries
Canada