Blinded, multi-center validation of EEG and rating scales in identifying ADHD within a clinical sample

Snyder, Steven M.; Quintana, Humberto; Sexson, Sandra B.; Knott, P. J.; Haque, A. F M; Reynolds, D.

doi:10.1016/j.psychres.2007.05.006

Cited by 115 publications

(108 citation statements)

References 60 publications

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“…Still, our findings regarding comparable theta and TBR between groups are in contrast with other studies Clarke et al, 2007Clarke et al, , 2011Dupuy et al, 2011;González-Castro et al, 2013;Lansbergen et al, 2011;Loo et al, 2010;Shi et al, 2012;Snyder et al, 2008), but correspond with some recent studies that also failed to replicate increased theta or TBR in ADHD (Coolidge et al, 2007;Liechti et al, 2013;Loo et al, 2013;Nazari et al, 2011;Ogrim et al, 2012;Swartwood et al, 2003). As for alpha and beta power, our results are not unexpected since deviances in those frequency ranges in ADHD have not been consistently observed across studies (see Section 1).…”

Section: Discussionsupporting

confidence: 84%

“…Furthermore, the findings indicate that it is unlikely that stable, univariate EEG abnormalities are implicated in all children with ADHD and that it is important to take into account state-dependent characteristics when evaluating EEG in ADHD. From a clinical perspective, this implies that cautiousness is warranted in using simple EEG measures as a supplementary diagnostic tool, as has been proposed by some researchers (Monastra, Lubar, & Linden, 2001;Snyder et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…Resting EEG studies with either eyes closed or open typically have reported increased theta power or an elevated proportion of slow to fast frequency power, theta/beta ratio (TBR), in children with ADHD compared to typically developing children (e.g., Barry, Clarke, & Johnstone, 2003;González-Castro, Rodríguez, López, Cueli, & Álvarez, 2013;Lansbergen, Arns, van Dongen-Boomsma, Spronk, & Buitelaar, 2011;Loo et al, 2010;Shi et al, 2012;Snyder et al, 2008). However, lately the robustness of these EEG deviances characterizing the whole ADHD population has become the focus of a debate, as a number of studies, mainly addressing eyes open resting EEG, could not invariably distinguish children with ADHD from a typically developing group based on theta power or TBR (Coolidge, Starkey, & Cahill, 2007;Liechti et al, 2013;Loo et al, 2013;Nazari, Wallois, Aarabi, & Berquin, 2011;Ogrim, Kropotov, & Hestad, 2012;Swartwood, Swartwood, Lubar, & Timmermann, 2003).…”

Section: Introductionmentioning

confidence: 99%

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State-related electroencephalographic deviances in attention deficit hyperactivity disorder

Buyck

Wiersema

2014

Research in Developmental Disabilities

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This study investigated the stability and state-related characteristics of electroencephalographic (EEG) deviances in attention-deficit/hyperactivity disorder (ADHD). Three minutes resting EEG with eyes closed and eyes open were compared between 21 children with ADHD and 29 typically developing children. Across resting conditions, children with ADHD exhibited divergent topographic distribution for theta, alpha and beta power compared to typically developing children. In addition, less alpha and theta suppression to eye opening was found in children with ADHD, but only in those without comorbid ODD/CD. Findings of the present study refer to a consistent divergence in topographic distribution in ADHD across resting state conditions, yet demonstrate that state-related factors and comorbidity may also contribute to resting EEG deviances in ADHD. The state-related findings are in accord with several theoretical accounts emphasizing the role of contextual and state factors defining deficits in ADHD.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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State-related electroencephalographic deviances in attention deficit hyperactivity disorder

Buyck

Wiersema

2014

Research in Developmental Disabilities

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“…OR met accepted criteria for clinical levels of symptoms on validated ADHD rating scales‖ [emphasis added]. The authors fail to acknowledge that such allegedly validated ADHD rating scales have only class-IV evidence for diagnosing ADHD according to the American Academy of Neurology, and in a recent large blinded multisite trial had exceptionally poor diagnostic sensitivity (range: 38-79%) and specificity (range: 13-61%) with an overall diagnostic accuracy similar to flipping a coin (range: 47-58%; see Snyder et al, 2008). Rigorous methods would have informed readers which of their included studies relied on such -flip-a-coin‖ rating scales to diagnosis ADHD-versus the goldstandard of clinician diagnosis-and then analyzed these low-quality studies separately to assess if they differentially affected their findings.…”

Section: Garbage In Garbage Outmentioning

confidence: 99%

“…Second, to analyze outcomes, the authors relied on parent and teacher-completed ADHD rating scales that are subject to significant rater bias with poor inter-rater agreement and exceedingly high levels of false-positive and false-negative findings when used to assess ADHD (Snyder et al, 2008). Due to not having both parent-and teacher-completed rating scales, the group excluded from its -probably blinded‖ meta-analysis randomized NFB studies using more objective measures of ADHD including:…”

Section: Ignoring Neurofeedback's Use Of Objective Outcomesmentioning

confidence: 99%

Neurofeedback Requires Better Evidence of Efficacy Before It Should Be Considered a Legitimate Treatment for ADHD: What is the Evidence for this Claim?

Pigott¹,

Cannon²

2014

NeuroRegulation

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Integration of an EEG biomarker with a clinician's ADHD evaluation

et al. 2015

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BackgroundThis study is the first to evaluate an assessment aid for attention-deficit/hyperactivity disorder (ADHD) according to both Class-I evidence standards of American Academy of Neurology and De Novo requirements of US Food and Drug Administration. The assessment aid involves a method to integrate an electroencephalographic (EEG) biomarker, theta/beta ratio (TBR), with a clinician's ADHD evaluation. The integration method is intended as a step to help improve certainty with criterion E (i.e., whether symptoms are better explained by another condition).MethodsTo evaluate the assessment aid, investigators conducted a prospective, triple-blinded, 13-site, clinical cohort study. Comprehensive clinical evaluation data were obtained from 275 children and adolescents presenting with attentional and behavioral concerns. A qualified clinician at each site performed differential diagnosis. EEG was collected by separate teams. The reference standard was consensus diagnosis by an independent, multidisciplinary team (psychiatrist, psychologist, and neurodevelopmental pediatrician), which is well-suited to evaluate criterion E in a complex clinical population.ResultsOf 209 patients meeting ADHD criteria per a site clinician's judgment, 93 were separately found by the multidisciplinary team to be less likely to meet criterion E, implying possible overdiagnosis by clinicians in 34% of the total clinical sample (93/275). Of those 93, 91% were also identified by EEG, showing a relatively lower TBR (85/93). Further, the integration method was in 97% agreement with the multidisciplinary team in the resolution of a clinician's uncertain cases (35/36). TBR showed statistical power specific to supporting certainty of criterion E per the multidisciplinary team (Cohen's d, 1.53). Patients with relatively lower TBR were more likely to have other conditions that could affect criterion E certainty (10 significant results; P ≤ 0.05). Integration of this information with a clinician's ADHD evaluation could help improve diagnostic accuracy from 61% to 88%.ConclusionsThe EEG-based assessment aid may help improve accuracy of ADHD diagnosis by supporting greater criterion E certainty.

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Blinded, multi-center validation of EEG and rating scales in identifying ADHD within a clinical sample

Cited by 115 publications

References 60 publications

State-related electroencephalographic deviances in attention deficit hyperactivity disorder

State-related electroencephalographic deviances in attention deficit hyperactivity disorder

Neurofeedback Requires Better Evidence of Efficacy Before It Should Be Considered a Legitimate Treatment for ADHD: What is the Evidence for this Claim?

Integration of an EEG biomarker with a clinician's ADHD evaluation

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