SenseToKnow Autism Screening Device Validation Study

NCT05874466 | Recruiting

• 2 other identifiers: Pro001113712P50HD093074
• Study Type: observational
• Target: 350
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Autism; Autism Spectrum Disorder

Keywords

Diagnosis; Digital device

Outcome Measures

Primary Outcomes (2)

• 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

  Sensitivity = #participants positive for autism on both (1) the SenseToKnow screening device based on a machine learning algorithm that combines SenseToKnow digital data with the SenseToKnow Caregiver Survey data and (2) expert clinical diagnosis / #participants positive for autism on both SenseToKnow and expert clinical diagnosis

  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

  Specificity = #participants negative for autism on both (1) the SenseToKnow screening device based on a machine learning algorithm that combines SenseToKnow digital data with the SenseToKnow Caregiver Survey data, and (2) expert clinical diagnosis / #participants negative for autism on autism by expert clinical diagnosis

  Will be calculated based on data from Baseline/Timepoint 1

Secondary Outcomes (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

  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

  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

  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

  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

  Will be calculated based on data from Baseline/Timepoint 1

Study Arms (1)

Pediatric patients, 16-36 months of age, recruited through pediatric medical clinics

Consecutive pediatric participants will be recruited and enrolled via \>= 6 participating sites comprised of pediatric medical clinics (e.g., primary care and family medicine clinics) that are part of the broader Duke University Health System (DUHS) located in North Carolina. Enrollment will proceed until the targets of N = 150 participants diagnosed with autism spectrum disorder and N = 200 without autism are reached.

Eligibility Criteria

• Age: 16 Months - 36 Months
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)
• Sampling Method: Non-Probability Sample

Study Population

Participants will be patients 16-36 months of age recruited from \> 6 sites comprised of pediatric medical clinics that are part of the broader Duke University Health System in North Carolina.

You may qualify if:

• Duke Health pediatric patient at enrollment
• \<37 months of age at enrollment
• Parent/legal guardian speaks English or Spanish
• Parent/legal guardian understands and voluntarily provides informed consent

You may not qualify if:

• 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

Sponsors & Collaborators

• Duke University: lead
• Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): collaborator

Study Sites (1)

Duke University

Durham, North Carolina, 27705, United States

RECRUITING

MeSH Terms

Conditions

Autistic Disorder; Autism Spectrum Disorder; Disease

Condition Hierarchy (Ancestors)

Child Development Disorders, Pervasive; Neurodevelopmental Disorders; Mental Disorders; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Geraldine Dawson, PhD

  Duke University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Geraldine Dawson, PhD

CONTACT

9196680070; geraldine.dawson@duke.edu

Charlotte Stoute, BA

CONTACT

919-681-9730; charlotte.stoute@duke.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 12, 2023
• First Posted: May 25, 2023
• Study Start: July 7, 2023
• Primary Completion (Estimated): December 1, 2027
• Study Completion (Estimated): December 1, 2027
• Last Updated: March 6, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: ANALYTIC CODE
• Time Frame: We will submit an electronic version of the final, peer-reviewed work, including the statistical analysis code, to the National Library of Medicine PubMed Central, to be made publicly available no later than 12 months after the official date of publication.
• Access Criteria: Publically available via PubMed Central

Locations

US (1)