1. Erratum: What Predicts Attention-Deficit/Hyperactivity Disorder Literacy in Primary Schoolteachers?. Niger Postgrad Med J. 2026; 33(5): 689.

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2. Bergey M. « If it’s going to be, it’s up to me. . . »: Health-related coaching, personal responsibility, empowerment, digital health, and the expanding practice of ADHD care. Health (London). 2026: 13634593261473498.

Despite the emergence of various « health coaches » in recent decades, little is known about the nature of their work in addressing medicalized conditions. Utilizing in-depth interviews with 51 ADHD coaches, participant observation data from 7 ADHD national symposia, and qualitative content from ADHD coach publications, I examine access to and characteristics of the practice of coaching for a classic case of medicalization: attention deficit hyperactivity disorder (ADHD). Findings indicate certain elements of a neoliberal and consumerist response to what is perceived to be limited, prescriptive, hierarchical medical care. Often drawing upon personal experiences and working with « clients » as opposed to « patients, » ADHD coaches characterize their practice as highly-tailored support grounded in partnership, accountability, accessibility, and choice – factors often facilitated by the use of digital technologies. Client empowerment is partially constrained and coach/provider empowerment is partially enhanced, however, by determinations of « coachability, » an emphasis on individual responsibility, and limited reimbursement options. Additionally, findings point to the role that intersecting stakeholder identities (e.g., clinician/coaches, coach/clients) may play in such dynamics. I discuss the relevance of such findings for theorizing about the engaged health client within an era of increased health consumerism, corporatization, growing and intersecting forms of « expertise, » and increased personal responsibility over health.

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3. Groenman AP, Welling LE, Pieters S. The monthly spectrum: Premenstrual symptoms across ADHD and autism. Womens Health (Lond). 2026; 22: 17455057261476912.

BackgroundWomen with ADHD and autism experience elevated rates of premenstrual problems, yet no direct comparisons between these conditions exist in adults.ObjectivesThis study examined premenstrual dysphoric disorder (PMDD) prevalence, symptoms, and impairment across ADHD, autism, and neurotypical women.DesignCross-sectional data from 199 women aged 20-40 without hormonal contraceptive use were analyzed across two samples.MethodsParticipants included 89 with ADHD, 39 with autism, and 71 controls. Premenstrual symptoms were assessed using the Premenstrual Symptoms Screening Tool (PSST), alongside measures of ADHD characteristics, autism traits, and sensory hypersensitivity.ResultsBoth ADHD and autistic women showed significantly elevated provisional PMDD rates according to the PSST screening instrument compared to controls, with no significant difference between neurodivergent groups. Dimensional analyses revealed positive associations between premenstrual symptoms and neurodiverse traits, particularly inattention, hyperactivity-impulsivity, and social skills difficulties. The impact of premenstrual problems was similarly associated with these traits across diagnostic groups. Contrary to hypotheses, sensory hypersensitivity was not independently associated with premenstrual symptoms after controlling for ADHD and autism characteristics.ConclusionsPremenstrual problems constitute a significant burden for both ADHD and autistic women, with dimensional associations suggesting that individuals with more severe neurodivergent traits face heightened risk. Yet our findings also demonstrate that prevalence estimates are only as reliable as the recruitment strategies behind them. Advancing this field requires both greater clinical attention to menstrual cycle-related difficulties in neurodivergent populations and recruitment strategies that yield dependable estimates. Many individuals with ADHD or autistic individuals report premenstrual problems such as low mood, irritability, or headaches in the days before their period. Until now, no study had directly compared these individuals with ADHD or autism to each other, so it was unclear whether one group was more affected than the other. We studied 199 individuals with a menstrual cycle aged 20 to 40 who were not using hormonal contraception: 89 with ADHD, 39 with autism, and 71 individuals without either diagnosis. Everyone completed a short questionnaire about premenstrual symptoms, along with measures of ADHD characteristics and autism traits. A subsample also completed a measure on sensory sensitivity. Individuals with ADHD and autistic individuals were both more likely than those without these classifications to screen positive for premenstrual dysphoric disorder (PMDD), a severe form of premenstrual difficulty. The two neurodivergent groups did not differ from each other. We also found that the more neurodivergent traits a person reported, especially inattention, hyperactivity and impulsivity, and social difficulties, the more premenstrual symptoms she tended to report, and the more those symptoms affected her daily life. This pattern held regardless of classification. Sensory sensitivity was not related to premenstrual problems. Overall, premenstrual problems appear to be a real and meaningful burden for both ADHD and autistic women, and individuals who reported more traits seem to be at greater risk. However, our results carry a note of caution: Our results show a strong indication of selection bias, where those individuals recruited for a study on premenstrual problems showed a much higher prevalence than those recruited for a study on sleep. Progress in this field will require both more clinical attention to menstrual cycle difficulties in neurodivergent women and recruitment methods that produce trustworthy estimates. eng.

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4. Hao Z, Xu H, Wang C, Wang B, Qiu Z. Multimodal Digital Therapeutics Enhanced by Task Design and AI for Attention-Deficit/Hyperactivity Disorder Core Symptoms and Executive Functions in Children and Adolescents: Systematic Review and Network Meta-Analysis of Randomized Controlled Trials. J Med Internet Res. 2026; 28: e95043.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Digital therapeutics (DTx) show promise as nonpharmacological interventions, but the comparative efficacy of different DTx modalities remains unclear. OBJECTIVE: This network meta-analysis (NMA) compared 4 DTx modalities (single-task, cognitive-motor dual-task, AI-integrated single-task, and AI-integrated cognitive-motor dual-task DTx) on core ADHD symptoms and executive functions, identified the optimal modality, and explored treatment moderators. METHODS: We included randomized controlled trials (RCTs) in children and adolescents aged 4 to 17 years with ADHD diagnosed per the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]) or ICD-10 (International Classification of Diseases, Tenth Revision). We searched PubMed/MEDLINE, PsycINFO, Web of Science, EMBASE, Scopus, ProQuest Dissertations and Theses, Cochrane Library, and ClinicalTrials.gov (gray literature) to identify trials published between January 2000 to May 2026 (last search May 22, 2026) without language restrictions, supplemented by snowballing. Risk of bias was assessed with the Cochrane Risk of Bias (RoB) 2 tool. Data were synthesized using Bayesian NMA with random-effects models. The surface under the cumulative ranking curve (SUCRA) was used to rank interventions. Heterogeneity was evaluated via 95% prediction intervals (95% PI) and explored through subgroup analyses and meta-regression. Small-study effects were assessed using Egger test, and sensitivity analyses were also performed. RESULTS: Thirty-two RCTs (2819 patients) were included. The risk of bias assessment identified a low risk in 37.5% of the studies, some concerns in 21.9% of the studies, and a high risk in 40.6% of the studies, mainly due to inadequate reporting of randomization or blinding. AI-integrated cognitive-motor dual-task DTx ranked first for all outcomes in Bayesian network meta-analysis. For the Attention-Deficit/Hyperactivity Disorder-Rating Scale (ADHD-RS; 7 studies, n=1642), SUCRA was 57.5% (mean difference [MD] -3.03, 95% credible intervals [95% CrI] -5.59 to -0.47). For the Swanson, Nolan, and Pelham Rating Scale (Version IV; SNAP-IV) inattention subscale (SNAP-IV-PI; 8 studies, n=468), SUCRA was 82.5% (MD -5.58, 95% CrI -8.76 to -2.39); for the SNAP-IV hyperactivity-impulsivity subscale (SNAP-IV-PHI; 8 studies, n=468), SUCRA was 92.6% (MD -6.84, 95% CrI -10.37 to -3.31). For the Behavior Rating Inventory of Executive Function (BRIEF; 23 studies, n=1927), SUCRA was 84.4% (MD -7.75, 95% CrI -10.06 to -5.43). In pairwise meta-analyses, the 95% PI for ADHD-RS did not cross zero (-7.19 to -0.11), whereas those for the SNAP-IV (PI subscale: -5.62 to 1.87; PHI subscale: -6.66 to 2.82) and BRIEF (-6.91 to 1.94) did, indicating limited generalizability and substantial between-study heterogeneity. Subgroup analyses suggested intervention duration as a heterogeneity source for the SNAP-IV (both subscales) and BRIEF and mean age as a heterogeneity source for the SNAP-IV-PI and BRIEF. CONCLUSIONS: This NMA provides the first dual-dimension classification framework for ADHD DTx, combining SUCRA ranking, PI, and GRADE (Grading of Recommendations Assessment, Development and Evaluation). AI-integrated cognitive-motor dual-task DTx had the highest probability of improving core symptoms and executive functions, with duration and age as potential heterogeneity sources. These findings inform clinical decision-making and DTx development, although interpretation should account for evidence limitations.

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5. Kazazi F, Howell P. Network Models for Assessing the Co-occurrence Between Stuttering and ADHD. Int J Lang Commun Disord. 2026; 61(5): e70320.

BACKGROUND AND AIMS: Previous studies have indicated that people who stutter (PWS) and people with ADHD (PWADHD) show similar cognitive profiles, implying a link between the two neurodevelopmental profiles. This study examined the relationship between stuttering and ADHD and investigated the extent of this similarity using Network Models (NMs). METHODS AND PROCEDURES: Neurotypical participants (people who did not stutter and did not have ADHD; N = 67), PWADHD (N = 79) and PWS (N = 33) were assessed for stuttering, ADHD traits, and phonological working memory (PWM). Lower PWM is associated with many conditions including stuttering and ADHD. OUTCOMES AND RESULTS: NM analysis revealed differences in cognitive networks (fluency, attention and PWM) between participant groups. The findings suggest partially different cognitive architectures across participant groups indicating that stuttering and ADHD do not share a common underlying mechanism. There were marked differences between participant groups in the way that traits of attention, stuttering, and PWM linked with each other which emphasises partially unique cognitive architecture of these participant groups. Higher PWM scores were associated with better attention in the neurotypical group and PWADHD but not PWS. Higher stuttering characteristics affected PWM in PWADHD and PWS, but the link was stronger in PWS. Whilst higher stuttering characteristics correlated positively with lower attention in PWADHD, the opposite was the case for PWS. PWM was the most important factor in all groups but the way it affected other cognitive processes differed between neurotypical participants, PWS and PWADHD. CONCLUSIONS AND IMPLICATIONS: Overall NM structures were similar between the neurotypical group and PWADHD but they both differed from those of PWS. Findings argue against a shared underlying mechanism of attention, fluency and PWM in stuttering and ADHD and highlight the importance of including PWM assessments within a network-based framework. WHAT THIS PAPER ADDS: What is already known on this subject Existing research indicates that people who stutter (PWS) and people with ADHD (PWADHD) exhibit overlapping traits in attention, speech fluency, and phonological working memory (PWM). Past studies have reported lower performance in attention, speech fluency and PWM in PWADHD and PWS as compared to neurotypical participants. This trait overlap has often been interpreted as co-occurrence between the two profiles (stuttering and ADHD). However, existing literature has primarily relied on trait co-occurrence and group-level performance differences, without examining whether attention, fluency, and PWM interact in similar ways across the two profiles. As a result, it remains unclear whether these shared traits reflect common underlying mechanisms or distinct cognitive profiles that show similar behavioural outcomes. What this study adds to existing knowledge The present study showed that although attention, fluency, and PWM differ between neurotypical participants versus PWS, and PWADHD, the way these abilities are interconnected differs between groups. Network analyses revealed partially distinct patterns of association, with the PWADHD network more closely resembling that of the neurotypical participants than that of PWS. Whilst PWM was a central component across all groups, its role within the network varied. In neurotypical participants and PWADHD, PWM was closely linked to attention, but this link was lost in PWS. These findings indicate that similar trait profiles do not necessarily imply the same cognitive architecture, and that overlapping traits in stuttering and ADHD can arise from different patterns of interaction among attention, fluency and PWM rather than from a shared underlying mechanism. What are the actual clinical implications of this study? Our findings suggest that overlapping traits in attention, speech and PWM should not automatically be interpreted as evidence of a shared underlying profile in stuttering and ADHD. Instead, clinical evaluation should consider how cognitive processes interact within each profile. The results also highlight the value of including PWM assessment when examining attentional and fluency traits in both PWS and PWADHD, particularly using tools such as the UNWR. More broadly, network-based approaches offer a promising framework for distinguishing between surface-level trait overlap and fundamental differences in cognitive organisation, thereby supporting more precise, profile-specific intervention strategies.

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6. Kim HJ, Kim KJ, Han DH, Kim SM, Hwang H, Hong JS. Age-Related Cognitive Patterns in Children With Attention-Deficit/Hyperactivity Disorder and Typically Developing Children: A Comparative Study. J Korean Med Sci. 2026; 41(32): e221.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD), characterized by inattention and hyperactivity-impulsivity, profoundly influences cognitive and behavioral development. Compared with their typically developing (TD) counterparts, children diagnosed with ADHD consistently exhibit impaired performance, which manifests as delays in response inhibition, interference selection, and working memory. We hypothesized that with increasing age, the attentional differences observed in younger children would progressively diminish, and that these developmental changes would be associated with behavioral and emotional problems. METHODS: We analyzed data from 131 children diagnosed with ADHD, sourced from the psychiatric outpatient departments of two hospitals, alongside data from 167 TD children aged 4-12 years. Using analysis of variance, we investigated differences in Comprehensive Attention Test (CAT) scores, intelligence quotients, and the Korean version of the Child Behavior Checklist (K-CBCL) scores between children with ADHD and their TD peers. RESULTS: Compared with their TD counterparts, children diagnosed with ADHD exhibited lower intelligence quotient scores across multiple subscales and elevated levels of diverse behavioral problems. Age-related patterns unveiled shifts in CAT scores. K-CBCL externalizing and internalizing problem scale and CAT scores were correlated. CONCLUSION: This study revealed age-related patterns of cognition among pediatric patients with ADHD when compared with a non-ADHD control group. With maturation, developmental delays may lessen, and attention improvement follows a discernible sequence, commencing with basic attention, followed by inhibition and ultimately, interference selection. Furthermore, age-dependent correlations between CAT and K-CBCL scale scores were identified. These findings highlight the clinical importance of considering age-specific patterns of cognitive and behavioral characteristics in the assessment of ADHD.

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7. Yonezawa N, Momo K. Real-World Medication Regimen Change in Adults with ADHD: A Large Claims Database Study. Biol Pharm Bull. 2026; 49(8): 1263-70.

Pharmacotherapy persistence in adults with attention-deficit/hyperactivity disorder (ADHD) remains concerning; however, evidence describing early treatment changes and discontinuation is limited. This study aimed to describe initial ADHD pharmacotherapy patterns and quantify claims-based initial regimen instability in Japanese adults. Using a Japanese claims database, we assembled a cohort of adults who initiated ADHD medication with methylphenidate, atomoxetine, guanfacine, or polytherapy (combination therapy) at initiation. Initial regimen instability was defined as the first observed regimen modification, including switching, add-on/polytherapy, de-escalation or combination-pattern change among initial polytherapy users, or a temporary drug-free interruption followed by restart after 31-179 d. A sustained medication-free period of ≥180 d without restart was treated as a competing event. We estimated cumulative incidence functions for initial regimen instability, treating the sustained medication-free period as a competing event. Fine-Gray models adjusted for age, sex, and major psychiatric comorbidities were used to compare initial regimens with methylphenidate as a reference. Landmark analysis was used to assess robustness. Among 14814 initiators, 3085, 8517, 3076, and 136 started methylphenidate, atomoxetine, guanfacine, and initial polytherapy, respectively. In the adjusted Fine-Gray model, the subdistribution hazard ratio for initial regimen instability was 0.74 for atomoxetine and 0.72 for guanfacine, whereas it was higher (2.65) for initial polytherapy in the main analysis. However, this estimate was sensitive to the operational definition of regimen instability. Landmark analysis yielded consistent differences between regimens. Initial ADHD pharmacotherapy showed heterogeneity in Japanese adults and included initial polytherapy, with initial regimen instability differing substantially depending on the starting regimen.

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