Dataset Information

The link between ADHD-like inattention and obsessions and compulsions during treatment of youth with OCD.

ABSTRACT: Attention-deficit/hyperactivity disorder (ADHD) has been found to be highly comorbid in children and adolescents with obsessive-compulsive disorder (OCD). Some have proposed, however, that obsessive anxiety may cause inattention and executive dysfunction, leading to inappropriate ADHD diagnoses in those with OCD. If this were the case, these symptoms would be expected to decrease following successful OCD treatment. The present study tested this hypothesis and evaluated whether ADHD symptoms at baseline predicted OCD treatment response. Obsessive-compulsive and ADHD symptoms were assessed in 50 youth enrolled in a randomized controlled trial investigating selective serotonin reuptake inhibitor and cognitive behavioral treatment. Repeated-measures analysis of variance (RMANOVA) revealed that ADHD symptoms at baseline do not significantly predict treatment outcome. A multivariate RMANOVA found that OCD treatment response moderated change in inattention; participants who showed greater reduction in OCD severity experienced greater reduction in ADHD-inattentive symptoms, while those with less substantial reduction in obsessions and compulsions showed less change. These findings suggest that children and adolescents with OCD and inattention may experience meaningful improvements in attention problems following OCD treatment. Thus, in many youth with OCD, inattention may be inherently tied to obsessions and compulsions. Clinicians may consider addressing OCD in treatment before targeting inattentive-type ADHD.

SUBMITTER: Guzick AG

PROVIDER: S-EPMC5619255 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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The link between ADHD-like inattention and obsessions and compulsions during treatment of youth with OCD.

Guzick Andrew G AG McNamara Joseph P H JPH Reid Adam M AM Balkhi Amanda M AM Storch Eric A EA Murphy Tanya K TK Goodman Wayne K WK Bussing Regina R Geffken Gary R GR

Journal of obsessive-compulsive and related disorders 20161123

Attention-deficit/hyperactivity disorder (ADHD) has been found to be highly comorbid in children and adolescents with obsessive-compulsive disorder (OCD). Some have proposed, however, that obsessive anxiety may cause inattention and executive dysfunction, leading to inappropriate ADHD diagnoses in those with OCD. If this were the case, these symptoms would be expected to decrease following successful OCD treatment. The present study tested this hypothesis and evaluated whether ADHD symptoms at b ...[more]

PMID: 28966908

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Project description:Background: Topographic memory is the ability to reach various places by recognizing spatial layouts and getting oriented in familiar environments. It involves several different cognitive abilities, in particular executive functions (EF), such as attention, working memory, and planning. Children with attention deficit hyperactivity disorder (ADHD) show impairments in inhibitory control, regulation of attention, planning, and working memory. Aim: The aim of this study was to evaluate the topographic memory in children with ADHD-combined subtype (ADHD-C). Method: Fifteen children (8-10 years) with a diagnosis of ADHD-C (DSM-5) (ADHD-C group) were compared to 15 children with typical development (TD group) of the same age. All children performed Raven's colored progressive matrices (CPM) test to obtain a measure related with cognitive functioning. The walking Corsi test (WalCT), a large-scale version of the Corsi block-tapping test, was used to assess topographic memory in experimental environment. Results: A higher impairment was observed in ADHD-C than TD with significant differences in the WalCT, in particular on the topographic short-term memory (TSTM) task, on the topographic learning (TL) task, and on the repetition number (RN) task during the TL task. Perseverative errors were reported in performing the square-sequence in the WalCT. Zero-order correlations showed a positive correlation between TSTM and auditory attention, and memory of design of NEPSY-II and digit span of WISC-IV. No statistically significant differences were found between the ADHD-C group and TD group in the TL task in the WalCT condition. Conclusion: In ADHD-C, initial topographic learning was compromised whereas the long-term retention of learned topographical material seemed to not be impaired. In particular, these impairments seem to be linked with difficulties in sustained attention, in spatial memory for novel visual materials, in a poor working memory, and in perseverative behaviors.

Project description:ObjectiveSleep problems is the most common side effect of methylphenidate (MPH) treatment in ADHD youth and carry potential to negatively impact long-term self-regulatory functioning. This study aimed to examine whether applying machine learning approaches to pre-treatment demographic, clinical questionnaire, environmental, neuropsychological, genetic, and neuroimaging features can predict sleep side effects following MPH administration.MethodThe present study included 83 ADHD subjects as a training dataset. The participants were enrolled in an 8-week, open-label trial of MPH. The Barkley Stimulant Side Effects Rating Scale was used to determine the presence/absence of sleep problems at the 2nd week of treatment. Prediction of sleep side effects were performed with step-wise addition of variables measured at baseline: demographics (age, gender, IQ, height/weight) and clinical variables (ADHD Rating Scale-IV (ADHD-RS) and Disruptive Behavior Disorder rating scale) at stage 1, neuropsychological test (continuous performance test (CPT), Stroop color word test) and genetic/environmental variables (dopamine and norepinephrine receptor gene (DAT1, DRD4, ADRA2A, and SLC6A2) polymorphisms, blood lead, and urine cotinine level) at stage 2, and structural connectivities of frontostriatal circuits at stage 3. Three different machine learning algorithms ((Logistic Ridge Regression (LR), support vector machine (SVM), J48) were used for data analysis. Robustness of classifier model was validated in the independent dataset of 36 ADHD subjects.ResultsClassification accuracy of LR was 95.5% (area under receiver operating characteristic curve (AUC) 0.99), followed by SVM (91.0%, AUC 0.85) and J48 (90.0%, AUC 0.87) at stage 3 for predicting sleep problems. The inattention symptoms of ADHD-RS, CPT response time variability, the DAT1, ADRA2A DraI, and SLC6A2 A-3081T polymorphisms, and the structural connectivities between frontal and striatal brain regions were identified as the most differentiating subset of features. Validation analysis achieved accuracy of 86.1% (AUC 0.92) at stage 3 with J48.ConclusionsOur results provide preliminary support to the combination of multimodal classifier, in particular, neuroimaging features, as an informative method that can assist in predicting MPH side effects in ADHD.

Dataset Information

The link between ADHD-like inattention and obsessions and compulsions during treatment of youth with OCD.

Publications

The link between ADHD-like inattention and obsessions and compulsions during treatment of youth with OCD.

Similar Datasets

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