(1) Background: Attention deficit hyperactivity disorder (ADHD) is characterized by a persistent pattern of age-inappropriate levels of inattention and/or hyperactivity/impulsivity that results in functional impairment at work, education, or hobbies and affects family life, social contacts, and self-confidence. ADHD is a comorbid condition associated with a prognosis of severe substance use disorder (SUD) and the early onset of such. The aim of this meta-analysis was to obtain the best estimate of the prevalence of ADHD in SUD populations. (2) Methods: A literature research was conducted using PUBMED^® and Web of Science^®. The following search terms were used: [ADHD], [prevalence], and [substance use disorder]. RStudio^® was used for meta-analysis methods. (3) Results: In total, 31 studies were included. We estimate the prevalence of ADHD among SUD patients at 21%.

Adult attention-deficit/hyperactivity disorder (ADHD) is a serious and frequent psychiatric disorder of multifactorial pathogenesis. Several lines of evidence support the idea that ADHD is, in its core, a disorder of dysfunctional brain connectivity within and between several neurofunctional networks. The primary aim of this study was to investigate associations between the functional connectivity within resting state brain networks and the individual severity of core ADHD symptoms (inattention, hyperactivity, and impulsivity). Resting state functional magnetic resonance imaging (rs-fMRI) data of 38 methylphenidate-naïve adults with childhood-onset ADHD (20 women, mean age 40.5 years) were analyzed using independent component analysis (FSL’s MELODIC) and FSL’s dual regression technique. For motion correction, standard volume-realignment followed by independent component analysis-based automatic removal of motion artifacts (FSL’s ICA-AROMA) were employed. To identify well-established brain networks, the independent components found in the ADHD group were correlated with brain networks previously found in healthy participants (Smith et al. PNAS 2009;106:13040–5). To investigate associations between functional connectivity and individual symptom severity, sex, and age, linear regressions were performed. Decomposition of resting state brain activity of adults with ADHD resulted in similar resting state networks as previously described for healthy adults. No significant differences in functional connectivity were seen between women and men. Advanced age was associated with decreased functional connectivity in parts of the bilateral cingulate and paracingulate cortex within the executive control network. More severe hyperactivity was associated with increased functional connectivity in the left putamen, right caudate nucleus, right central operculum and a portion of the right postcentral gyrus within the auditory/sensorimotor network. The present study supports and extends our knowledge on the involvement of the striatum in the pathophysiology of ADHD, in particular, in the pathogenesis of hyperactivity. Our results emphasize the usefulness of dimensional analyses in the study of ADHD, a highly heterogeneous disorder. ISRCTN12722296 ( https://doi.org/10.1186/ISRCTN12722296 ).

Delay aversion (DAv) is thought to be a crucial factor in the manifestation of impulsive behaviors in patients with attention-deficit/hyperactivity disorder (ADHD). The imposition of delay is predicted to elicit negative emotional reactions in ADHD. The present study offers a multimodal approach to the investigation of DAv. Twelve adult patients with ADHD and 12 matched healthy controls were tested on a new task with several levels of anticipated delays during functional magnet resonance imaging (fMRI). Behavioral measures of delay discounting, DAv, and delay frustration were collected. Skin conductance and finger pulse rate were assessed. Results indicated a group difference in response to changes in delay in the right amygdala: For control participants activity decreased with longer delays, whereas activity tended to increase for ADHD patients. The degree of amygdala increase was correlated with the degree of behavioral DAv within the ADHD group. Patients also exhibited increased emotional arousal on physiological measures. These results support the notion of an exacerbated negative emotional state during the anticipation and processing of delay in ADHD.

Speech is a promising biomarker for schizophrenia spectrum disorder (SSD) and major depressive disorder (MDD). This proof of principle study investigates previously studied speech acoustics in combination with a novel application of voice pathology features as objective and reproducible classifiers for depression, schizophrenia, and healthy controls (HC). Speech and voice features for classification were calculated from recordings of picture descriptions from 240 speech samples (20 participants with SSD, 20 with MDD, and 20 HC each with 4 samples). Binary classification support vector machine (SVM) models classified the disorder groups and HC. For each feature, the permutation feature importance was calculated, and the top 25% most important features were used to compare differences between the disorder groups and HC including correlations between the important features and symptom severity scores. Multiple kernels for SVM were tested and the pairwise models with the best performing kernel (3-degree polynomial) were highly accurate for each classification: 0.947 for HC vs. SSD, 0.920 for HC vs. MDD, and 0.932 for SSD vs. MDD. The relatively most important features were measures of articulation coordination, number of pauses per minute, and speech variability. There were moderate correlations between important features and positive symptoms for SSD. The important features suggest that speech characteristics relating to psychomotor slowing, alogia, and flat affect differ between HC, SSD, and MDD.

Although guidelines recommend multimodal treatments in attention-deficit/hyperactivity disorder (ADHD), evidence of long-lasting effects in adults is scarce.^1-5 In particular, studies investigating long-term effectiveness of interventions combining psychotherapy and stimulant medication compared with interventions not including medication are hardly available.⁴ Owing to the paucity of long-term follow-up data, generalizability of results for cognitive behavioral group psychotherapy (GPT) combined with pharmacotherapy is very limited. Moreover, quality of evidence was evaluated as poor by a 2018 Cochrane review.⁶