title: Combined psychophysiological assessment of ADHD: a pilot study of Bayesian probability approach illustrated by appraisal of ADHD in female college students.
abstract: Manifestations of ADHD are observed at both psychological and physiological levels and assessed via various psychometric, EEG, and imaging tests. However, no test is 100% accurate in its assessment of ADHD. This study introduces a stochastic assessment combining psychometric tests with previously reported (Consistency Index) and newly developed (Alpha Blockade Index) EEG-based physiological markers of ADHD. The assessment utilizes classical Bayesian inference to refine after each step the probability of ADHD of each individual. In a pilot study involving six college females with ADHD and six matched controls, the assessment achieved correct classification for all ADHD and non-ADHD participants. In comparison, the classification of ADHD versus non-ADHD participants was < 85% for any one of the tests separately. The procedure significantly improved the score separation between ADHD versus non-ADHD groups. The final average probabilities for ADHD were 76% for the ADHD group and 8% for the control group. These probabilities correlated (r = .87) with the Brown ADD scale and (r = .84) with the ADHD-Symptom Inventory used for the screening of the participants. We conclude that, although each separate test was not completely accurate, a combination of several tests classified correctly all ADHD and all non-ADHD participants. The application of the proposed assessment is not limited to the specific tests used in this study--the assessment represents a general paradigm capable of accommodating a variety of ADHD tests into a single diagnostic assessment.
authors.affiliation: Department of Mathematical Sciences, Sweet Briar College, Sweet Briar, Virginia 24595, USA. robeva@sbc.edu
authors.forename: Raina
authors.initials: R
authors.lastname: Robeva
authors.forename: Jennifer Kim
authors.initials: JK
authors.lastname: Penberthy
authors.forename: Tim
authors.initials: T
authors.lastname: Loboschefski
authors.forename: Daniel
authors.initials: D
authors.lastname: Cox
authors.forename: Boris
authors.initials: B
authors.lastname: Kovatchev
mesh_terms: D000328:Adult; D001289:Attention Deficit Disorder with Hyperactivity / Q000175:diagnosis* / Q000503:physiopathology; D001499:Bayes Theorem; D003937:Diagnosis, Differential; D004569:Electroencephalography; D005260:Female; D006801:Humans; D010865:Pilot Projects; D011569:Psychiatric Status Rating Scales; D011594:Psychometrics; D012680:Sensitivity and Specificity