ADHD Diagnosis In University Settings: The Utility Of Quantitative EEG Coherence
2018
- 455Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage455
- Downloads269
- Abstract Views186
Artifact Description
The current study investigated the utility of EEG coherence parameters in the diagnosis of ADHD. Quantitative EEG (qEEG) analyses were performed in 35 college students with an ADHD diagnosis and 35 control students. Differences between groups were examined and the diagnostic significance of EEG coherence parameters was assessed by means of stepwise logistic regression analyses. The relation between inattentive and hyperactive/impulsive symptoms, as measured by the current symptom scale (CSS) and EEG coherence parameters was also assessed. Analyses assessing group differences using individual electrode pairings detected increased interhemispheric frontal beta-wave coherence in individuals with ADHD. Together, alpha, beta, delta, and theta-wave principle components allowed for identification of individuals diagnosed with ADHD with a sensitivity of 80% and a specificity of 71.4%. Moreover, symptoms of inattention were significantly correlated with EEG coherence values within beta and delta bands, while symptoms of hyperactivity/impulsivity were significantly correlated with coherence values within beta and theta bands. Findings warrant continued research, yet suggest qEEG coherence analyses may enhance current diagnostic procedures used for identifying ADHD in college populations
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