Recruiting NCT05874466
SenseToKnow Autism Screening Device Validation Study
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Autism, Autism Spectrum Disorder. Basic parameters: 16 months — 36 months · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
SenseToKnow STAR Study: A Study of Technologies for Assessing Children's Development
Overview
This is a pivotal, prospective, double-blind, study to evaluate the sensitivity and specificity of the SenseToKnow device for the detection of autism spectrum disorder in children 16-36 months of age.
Detailed description
This is a pivotal, prospective, double-blind, study to evaluate the sensitivity and specificity of the SenseToKnow device for the classification of autism spectrum disorder when administered by parents in a sample of patients 16-36 months of age. The trial design is a non-interventional cross-sectional study comparing the SenseToKnow device classification of autism spectrum disorder ("autism") versus non-autism with the patient's diagnostic status based on expert clinical diagnosis in a population of pediatric patients.
Primary outcome measures
- Sensitivity of the SenseToKnow screening device based on a machine learning algorithm that combines SenseToKnow digital data with data from the SenseToKnow Caregiver survey for autism detection [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Specificity of the SenseToKnow screening device based on machine earning algorithm that combines SenseToKnow digital data with data from the SenseToKnow Caregiver survey for autism detection [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
Secondary outcome measures (8)
- Positive Predictive Value of SenseToKnow screening device (based on a machine learning algorithm using the SenseToKnow digital data, combined with the SenseToKnow Caregiver Survey data) for autism detection in comparison to expert clinical diagnosis [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Negative Predictive Value of SenseToKnow screening device (based on a machine learning algorithm using the SenseToKnow digital data, combined with the SenseToKnow Caregiver Survey data) for autism detection in comparison to expert clinical diagnosis [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Receiver Operating Characteristic Curve and Area Under the Curve with respect to the accuracy of the SenseToKnow screening device (using the SenseToKnow digital data and SenseToKnow Caregiver survey data) for autism versus non-autism classification [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Sensitivity of SenseToKnow screening device based on a machine learning algorithm using only the SenseToKnow digital data for autism detection [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Specificity of SenseToKnow screening device based on a machine learning algorithm using only the SenseToKnow digital data for autism detection [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Positive Predictive Value of SenseToKnow screening device based on a machine learning algorithm using only the SenseToKnow digital data for autism detection in comparison to expert clinical diagnosis [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Negative Predictive Value of SenseToKnow screening device based on a machine learning algorithm using only the SenseToKnow digital data for autism detection in comparison to expert clinical diagnosis [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
- Receiver Operating Characteristic Curve and Area Under the Curve with respect to the accuracy of the SenseToKnow device using only the SenseToKnow digital data for autism versus non-autism classification [Time frame: Will be calculated based on data from Baseline/Timepoint 1]
Eligibility criteria
Inclusion criteria
- Duke Health pediatric patient at enrollment
- 16-<37 months of age at enrollment
- Parent/legal guardian speaks English or Spanish
- Parent/legal guardian understands and voluntarily provides informed consent
Exclusion criteria
- Severe motor impairment that precludes study measure completion
- Known genetic disorders
- Severe hearing or visual impairment as determined on physical examination according to parent report
- Acute illnesses likely to prevent successful or valid data collection
- Uncontrolled epilepsy or seizure disorder
- History or presence of a clinically significant medical disease, or a mental state that could confound the study or be detrimental to the subject as determined by the investigator
- Acute exacerbations of chronic illnesses likely to prevent successful or valid data collection
- Receiving therapies that affect vision
- Parent/legal guardian and/or investigator believes that the child will be unable/unwilling to sit in the parent's lap to watch the app videos
- Parent/legal guardian indicates that they or their child is unwilling or unable to complete the app administration, surveys, or diagnostic assessment
- Participants who are otherwise judged as unable to comply with the protocol by the investigator
- Any other factor that the investigator feels would make the study measures invalid
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Cohort
Study locations
United States · 1 center
- Duke University — Durham
Identifiers
NCT: NCT05874466 · Pro00111371 · 2P50HD093074