SenseToKnow STAR Study: A Study of Technologies for Assessing Children's Development
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 350
- 试验地点
- 1
- 主要终点
- 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
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 16 Months 至 36 Months（Child）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •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
研究组 & 干预措施
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.
结局指标
主要结局
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
时间窗: Will be calculated based on data from Baseline/Timepoint 1
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
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
时间窗: Will be calculated based on data from Baseline/Timepoint 1
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
次要结局
- 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)
- 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(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(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(Will be calculated based on data from Baseline/Timepoint 1)