Duke University and the NIH have collaborated to create SenseToKnow, a groundbreaking tablet-based application for screening autism spectrum disorder (ASD) in toddlers aged 17 months to three years. This innovative tool boasts an 87.8% accuracy rate for detecting ASD and an 80.8% specificity for children without ASD. By addressing the limitations of traditional parent questionnaires, SenseToKnow aims to reduce healthcare disparities and ensure early diagnosis and intervention. This development is significant for improving access to care, particularly for children of color, who often face delays in ASD diagnoses.
Duke University and the National Institutes of Health (NIH) have collaborated to create a groundbreaking tool for screening autism spectrum disorder (ASD), with the aim of enhancing access to care and reducing healthcare disparities. This significant development represents a significant step forward in ASD screening programs, particularly for early diagnosis and intervention.
The Autism Center of Excellence at Duke University has developed a tablet-based application, known as SenseToKnow, which healthcare providers utilize during well-child visits for toddlers aged 17 months to three years. This application helps identify toddlers who may require further examination for ASD, ensuring they are promptly connected with the necessary resources and support.
The importance of this tool lies in its potential to bridge the gap in healthcare access for children and families. Recent research funded by the NIH has highlighted the limitations of traditional parent questionnaires used in primary care settings, especially for girls and children of color. These questionnaires have proven to be less accurate than desired, resulting in disparities in early autism diagnoses and interventions.
SenseToKnow, on the other hand, records and analyzes children’s responses to short movies designed to elicit various behavioral patterns. It can detect early signs of ASD, including differences in social attention, facial expressions, head movements, response to name, blink rates, and motor skills. In a study involving 475 toddlers, the digital screening tool demonstrated an impressive 87.8% accuracy rate for detecting ASD and an 80.8% specificity for children without ASD who tested negative.
Comparatively, traditional parent questionnaires only correctly identify 15% of children who are later diagnosed with ASD, whereas the digital app increased this probability to 40.6%. Combining the app with the standard questionnaire further raised the probability of a positive screen leading to a later diagnosis to 63.4%. Following the study, 49 of the enrolled toddlers were subsequently diagnosed with ASD, and 98 were diagnosed with developmental delays without ASD. These children were promptly referred to and connected with the appropriate services.
This development is particularly significant because children with autism often experience poorer health outcomes compared to their peers, both with and without disabilities. Addressing healthcare disparities is crucial, especially for communities of color. Dr. Daniel Turner-Lloveras, the president of SaludConTech, an organization supporting the Latino community through digital health empowerment, emphasizes the importance of leveraging accessible technology and innovation to bridge these gaps.
In a separate study involving app-based screening for conditions like atrial fibrillation, digital exams were found to be superior in detection. This underscores the potential of digital tools in improving healthcare access and outcomes.
NIH officials have noted that SenseToKnow’s ability to reliably detect children diagnosed with ASD remains consistent across toddlers of different sex, race, and ethnicity, offering hope for more equitable access to care for all children.
