This study aims to demonstrate the accuracy of the MT1 algorithm using the MindTension biometric sensor device as a diagnostic aid for healthcare providers in diagnosing ADHD in youth ages ≥ 6 to ≤17 years.
The study aims to demonstrate the accuracy of the MT1 algorithm. The output of the MT1 algorithm will be compared to a Gold Standard clinical diagnosis made by specialist clinician diagnosis supported by the Kiddie SADS Present and Lifetime semi-structured interview (K-SADS-PL) and norm-referenced measures of current ADHD symptom frequency and severity using the ADHD-RS-5 rating scale. Diagnosis will be scaled according to the Diagnostic and Statistical Manual of Mental Disorders- 5 (DSM-5) criteria, and made with agreement between two licensed specialists in ADHD (a Clinical Psychologist and a Psychiatrist). Further to the above, demonstrate that the agreement between the MT1 output and the specialist clinician diagnosis will be non-inferior to the level of agreement between the clinician diagnosis with the Test of Visual Attention (TOVA) FDA cleared device.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
120
Objective measurements of attention and inhibition.
Objective measurements of attention and inhibitory control.
Icahn School of Medicine at Mount Sinai
New York, New York, United States
RECRUITINGOverall Agreement Rate (OAR) - probability that the test will be normal and the condition is normal or positive and the condition is positive, out of all subjects.
The outcome measure will be calculated by using the following formula: Over All Agreement = (True Positive + True Negative) / (True Positive + True Negative + False Positive + False Negative) X 100.
Time frame: From the beginning of clinical assessment until the end of testing (approximately 1-2 days).
Positive Predicted Value (PPV) - conditional probability that the condition will be positive if the test is positive.
The outcome measure will be calculated using the following formula: Positive Predicted Value = (True Positive) / (True Positive + False Positive) X 100
Time frame: From the beginning of clinical assessment until the end of testing (approximately 1-2 days).
Negative Predicted Value (NPV) - conditional probability that the condition will be normal if the test is normal.
The outcome measure will be calculated using the following formula: Negative Predicted Value = (True Negative) / (True Negative + False Negative) X 100
Time frame: From the beginning of clinical assessment until the end of testing (approximately 1-2 days).
Sensitivity - conditional probability that the test will be positive if the condition is positive.
The outcome measure will be calculated using the following formula: Sensitivity = (True Positive) / (True Positive + False Negative) X 100
Time frame: From the beginning of clinical assessment until the end of testing (approximately 1-2 days).
Specificity - conditional probability that the test will be normal if the condition is normal.
The outcome measure will be calculated using the following formula: Specificity = (True Negative) / (True Negative + False Positive) X 100
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Time frame: From the beginning of clinical assessment until the end of testing (approximately 1-2 days).