Psychometric properties of the Chinese version of the Quick Delay Questionnaire (C-QDQ) and ecological characteristics of reward-delay impulsivity of adults with ADHD.

BACKGROUND: The Quick Delay Questionnaire (QDQ) is a short questionnaire designed to assess delay-related difficulties in adults. This study aimed to examine the reliability and validity of the Chinese version of the QDQ (C-QDQ) in Chinese adults, and explore the ecological characteristics of delay-related impulsivity in Chinese adults with attention-deficit/hyperactivity disorder (ADHD). METHODS: Data was collected from 302 adults, including ADHD (n = 209) and healthy controls (HCs) (n = 93). All participants completed the C-QDQ. The convergent validity, internal consistency, retest reliability and confirmatory factor analysis (CFA) of the C-QDQ were analyzed. The correlations between C-QDQ and two laboratory measures of delay-related difficulties and Barratt Impulsiveness Scale-11 (BIS-11), the comparison of C-QDQ scores between ADHD subgroups and HCs were also analyzed. RESULTS: The Cronbach's α of C-QDQ was between 0.83 and 0.89. The intraclass correlation coefficient of C-QDQ was between 0.80 and 0.83. The results of CFA of C-QDQ favoured the original two-factor model (delay aversion and delay discounting). Significant positive associations were found between C-QDQ scores and BIS-11 total score and performance on the laboratory measure of delay-related difficulties. Participants with ADHD had higher C-QDQ scores than HCs, and female ADHD reported higher scores on delay discounting subscale than male. ADHD-combined type (ADHD-C) reported higher scores on delay aversion subscale than ADHD-inattention type (ADHD-I). CONCLUSION: The C-QDQ is a valid and reliable tool to measure delay-related responses that appears to have clinical utility. It can present the delay-related impulsivity of patients with ADHD. Compared to HCs, the level of reward-delay impulsivity was higher in ADHD.

Attention-deficit hyperactivity disorder symptoms and brain morphology: Addressing potential selection bias with inverse probability weighting.

The goal of this study was to examine what happens to established associations between attention deficit hyperactivity disorder (ADHD) symptoms and cortical surface and thickness regions once we apply inverse probability of censoring weighting (IPCW) to address potential selection bias. Moreover, we illustrate how different factors that predict participation contribute to potential selection bias. Participants were 9- to 11-year-old children from the Generation R study (N = 2707). Cortical area and thickness were measured with magnetic resonance imaging (MRI) and ADHD symptoms with the Child Behavior Checklist. We examined how associations between ADHD symptoms and brain morphology change when we weight our sample back to either follow-up (ages 9-11), baseline (cohort at birth), or eligible (population of Rotterdam at time of recruitment). Weights were derived using IPCW or raking and missing predictors of participation used to estimate weights were imputed. Weighting analyses to baseline and eligible increased beta coefficients for the middle temporal gyrus surface area, as well as fusiform gyrus cortical thickness. Alternatively, the beta coefficient for the rostral anterior cingulate decreased. Removing one group of variables used for estimating weights resulted in the weighted regression coefficient moving closer to the unweighted regression coefficient. In addition, we found considerably different beta coefficients for most surface area regions and all thickness measures when we did not impute missing covariate data. Our findings highlight the importance of using inverse probability weighting (IPW) in the neuroimaging field, especially in the context of mental health-related research. We found that including all variables related to exposure-outcome in the IPW model and combining IPW with multiple imputations can help reduce bias. We encourage future psychiatric neuroimaging studies to define their target population, collect information on eligible but not included participants and use inverse probability of censoring weighting (IPCW) to reduce selection bias.

Acetaminophen Use During Pregnancy and Children's Risk of Autism, ADHD, and Intellectual Disability.

Importance: Several studies suggest that acetaminophen (paracetamol) use during pregnancy may increase risk of neurodevelopmental disorders in children. If true, this would have substantial implications for management of pain and fever during pregnancy. Objective: To examine the associations of acetaminophen use during pregnancy with children's risk of autism, attention-deficit/hyperactivity disorder (ADHD), and intellectual disability. Design, Setting, and Participants: This nationwide cohort study with sibling control analysis included a population-based sample of 2 480 797 children born in 1995 to 2019 in Sweden, with follow-up through December 31, 2021. Exposure: Use of acetaminophen during pregnancy prospectively recorded from antenatal and prescription records. Main Outcomes and Measures: Autism, ADHD, and intellectual disability based on International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes in health registers. Results: In total, 185 909 children (7.49%) were exposed to acetaminophen during pregnancy. Crude absolute risks at 10 years of age for those not exposed vs those exposed to acetaminophen were 1.33% vs 1.53% for autism, 2.46% vs 2.87% for ADHD, and 0.70% vs 0.82% for intellectual disability. In models without sibling control, ever-use vs no use of acetaminophen during pregnancy was associated with marginally increased risk of autism (hazard ratio [HR], 1.05 [95% CI, 1.02-1.08]; risk difference [RD] at 10 years of age, 0.09% [95% CI, -0.01% to 0.20%]), ADHD (HR, 1.07 [95% CI, 1.05-1.10]; RD, 0.21% [95% CI, 0.08%-0.34%]), and intellectual disability (HR, 1.05 [95% CI, 1.00-1.10]; RD, 0.04% [95% CI, -0.04% to 0.12%]). To address unobserved confounding, matched full sibling pairs were also analyzed. Sibling control analyses found no evidence that acetaminophen use during pregnancy was associated with autism (HR, 0.98 [95% CI, 0.93-1.04]; RD, 0.02% [95% CI, -0.14% to 0.18%]), ADHD (HR, 0.98 [95% CI, 0.94-1.02]; RD, -0.02% [95% CI, -0.21% to 0.15%]), or intellectual disability (HR, 1.01 [95% CI, 0.92-1.10]; RD, 0% [95% CI, -0.10% to 0.13%]). Similarly, there was no evidence of a dose-response pattern in sibling control analyses. For example, for autism, compared with no use of acetaminophen, persons with low (<25th percentile), medium (25th-75th percentile), and high (>75th percentile) mean daily acetaminophen use had HRs of 0.85, 0.96, and 0.88, respectively. Conclusions and Relevance: Acetaminophen use during pregnancy was not associated with children's risk of autism, ADHD, or intellectual disability in sibling control analysis. This suggests that associations observed in other models may have been attributable to familial confounding.

Effects of yoga on impulsivity in patients with and without mental disorders: a systematic review.

BACKGROUND: Yoga can be used as a complementary intervention to conventional treatments, whether pharmacological or non-pharmacological. Sustained practice of yoga can generate a series of benefits for individuals' quality of life and improve their physical fitness. OBJECTIVE: To investigate the potential effects of yoga as an adjunct intervention in conditions involving impulse control issues, such as attention deficit hyperactivity disorder (ADHD), borderline personality disorder, bipolar affective disorder, and substance use disorders. METHODS: We performed a systematic review of placebo-controlled, randomized trials of yoga in patients with impulsivity. PubMed, Web of Science, and Science Direct databases were searched for trials published up to January, 2023. Data were extracted from published reports and quality assessment was performed per Cochrane recommendations. RESULTS: Out of 277 database results, 6 RCT were included in this systematic review. To assess the level of attention and impulsiveness, the following scales were analyzed: Barratt Impulsiveness, UPPS-P Impulsive Behavior scale, Conners' Continuous Performance Test IIª and Conners' Parent Rating Scale-Revised: Long. CONCLUSIONS: Yoga didn't have a significant improvement in impulsivity when compared to placebo. There are many tools to assess impulsivity, but they mean different concepts and domains consisting in a weakness on comparison of yoga effects. PROSPERO REGISTRATION: CRD42023389088.

Comparison of self-esteem and quality of life in 8-12-year-old children with ADHD with and without learning disorders.

BACKGROUND: Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common disorders in school-aged children. Learning disorder (LD) is also one of the most important psychiatric disorders in children, which can often be associated with ADHD. In this study, we sought to compare self-esteem and quality of life in 8 to 12-year-old children with attention deficit/hyperactivity disorder with and without co-occurring learning disorders in order to emphasize the importance of attention and diagnosis in children with ADHD. METHOD: Among the 8- to 12-year-old outpatients referred to the child and adolescent psychiatry clinic of Omid Babol Clinic, 120 children aged 8 to 12 years with attention deficit/hyperactivity disorder whose disease was diagnosed by a child and adolescent psychiatry subspecialist. Among the tools used to collect information was the Colorado Learning Difficulties Questionnaire by Wilcott et al. (CLDQ), five-scale self-esteem test of Pepe et al. (1989) for children and quality-of-life questionnaire for 8-12-year-old children (PedsQL). RESULTS: This study investigated self-esteem and quality of life in children with ADHD (n = 120, 51.7% boys). Children with ADHD and learning disabilities reported significantly lower self-esteem and quality of life compared to those with ADHD alone. CONCLUSION: Considering the relatively high probability of co-occurrence of ADHD and learning disorders, if one of them is diagnosed in a child, it is possible to look for other disorders in the child in order to avoid the more severe negative effects that this co-occurrence can have on the child by diagnosing it as soon as possible.

[The role of personal strengths in the relationship between adult attention-deficit/hyperactivity symptoms and perceived stress]. / A személyes erosségek szerepe a felnottkori figyelemhiányos/hiperaktivitás tünetek és az észlelt stressz kapcsolatában.

BACKGROUND/OBJECTIVES: David P. Bernstein's model of personal strengths was born out of the interaction of schema theory and positive psychology. According to Bernstein, the strengths of a healthy adult self can be described along four dimensions: self-directedness, self-regulation, connectedness, and transcendence. Previous research has shown that attention- deficit/hyperactivity disorder (ADHD) in adults is associated with higher levels of perceived stress, but the role of personal strengths in this context has not yet been investigated. The aim of our study was to explore the role of Bernstein's strength dimensions in the relationship between adult ADHD symptoms and perceived stress, using a dimensional approach in a non-clinical sample. METHOD: Our online questionnaire, which included the Bernstein Strengths Scale (BSS), the Adult ADHD Self-Report Scale (ASRS), and a shortened version of the Perceived Stress Scale (PSS4), was completed by 100 adults (mean age 38.25 years, standard deviation 5.73 years) after informed consent. RESULTS: In the bivariate analysis, the ASRS showed a significant negative association with the BSS dimensions, with a large effect size for self-regulation and a medium effect size for the other dimensions. On the other hand, the PSS4 scale showed significant negative correlations with all four strength dimensions, with effect sizes large for self-direction and self-regulation and medium for the connection and transcendence dimensions. Personal strengths mediated the relationship between ADHD symptoms and perceived stress. DISCUSSION: Our results suggest that ADHD symptoms may be associated with a deficit in personal strengths, which may contribute to negative outcomes. Psychotherapeutic interventions that support the recognition, cultivation and mobilization of strengths may be useful in the treatment of adults diagnosed with ADHD.

The relationship between game genre, monetization strategy and symptoms of gaming disorder in a clinical sample of adolescents.

Background: Gaming disorder (GD) has been introduced as a new diagnosis in the International Classification of Disease 11 (ICD-11). Currently, there's limited understanding of how various video games may differentially contribute to the risk of developing GD. The main aim of this study was to examine the relationship between individuals' game genre preferences, their preferred games' monetization strategies, and GD Symptoms. Methods: A total of 85 patients undergoing treatment for GD at a child and youth psychiatric clinic were included in the study. Their preferred games were classified into five novel genres based on gameplay similarities and objectives, and further categorized based on their monetization strategy. Results: Symptom burden of GD, measured with Game Addiction Scale for Adolescents (GASA), was highest for those playing Free-to-Play (F2P) games and lowest for Pay-to-Play (P2P) players. Players of Competitive Games endorsed higher GD symptom burden, whereas players of Story-driven games reported lower GD symptom burden. Symptoms of GD were associated with attention-deficit hyperactivity disorder (ADHD) diagnosis in males. Conclusions: This study reveals that game genre preference is influenced by sex, age, and certain psychiatric diagnoses. The categorizing of games into genres is increasingly complex and our research introduces a novel categorization in a developing research field. The result of this study suggests that the monetization model is important to consider while trying to understand the relationship between game characteristics and GD symptoms.

Correlations between developmental trajectories of brain functional connectivity, neurocognitive functions, and clinical symptoms in patients with attention-deficit hyperactivity disorder.

Several studies on attention-deficit hyperactivity disorder (ADHD) have suggested a developmental sequence of brain changes: subcortico-subcortical connectivity in children, evolving to subcortico-cortical in adolescence, and culminating in cortico-cortical connectivity in young adulthood. This study hypothesized that children with ADHD would exhibit decreased functional connectivity (FC) between the cortex and striatum compared to adults with ADHD, who may show increased FC in these regions. Seventy-six patients with ADHD (26 children, 26 adolescents, and 24 adults) and 74 healthy controls (25 children, 24 adolescents, and 25 adults) participated in the study. Resting state magnetic resonance images were acquired using a 3.0 T Philips Achieva scanner. The results indicated a gradual decrease in the number of subcategories representing intelligence quotient deficits in the ADHD group with age. In adulthood, the ADHD group exhibited lower working memory compared to the healthy control group. The number of regions showing decreased FC from the cortex to striatum between the ADHD and control groups reduced with age, while regions with increased FC from the default mode network and attention network in the ADHD group increased with age. In adolescents and adults, working memory was positively associated with brain activity in the postcentral gyrus and negatively correlated with ADHD clinical symptoms. In conclusion, the findings suggest that intelligence deficits in certain IQ subcategories may diminish as individuals with ADHD age. Additionally, the study indicates an increasing anticorrelation between cortical and subcortical regions with age in individuals with ADHD.

Development of a self-report screening instrument for emotional dysregulation: the Reactivity, Intensity, Polarity and Stability questionnaire, screening version (RIPoSt-SV).

BACKGROUND: Emotional dysregulation (ED) refers to the inability to manage emotional experiences or expressions hindering goal-oriented behavior. Moderate impairment on at least two domains among temper control, affective lability, and emotional over-reactivity has been proposed to identify ED in adults with attention-deficit/hyperactivity disorder (ADHD). No screening measure designed for use in diverse psychiatric samples exists. We aimed to develop a self-report screening tool for ED based on the 40-item version of the Reactivity, Intensity, Polarity, and Stability questionnaire (RIPoSt-40). METHODS: 150 adult outpatients with non-psychotic conditions were enrolled between February and July 2023 at the Second Psychiatry Unit of Pisa University Hospital. Clinically significant ED (CSED) was defined based on the previously suggested approach for ADHD. Differences between patients with and without CSED were tested. To develop our screening instrument, a decision tree algorithm was trained by hyperparameter tuning through 5-fold cross-validation in 120 subjects and tested on the remaining 30. RESULTS: 75 subjects met criteria for CSED (50 %). CSED was associated with lower age and higher prevalence of psychiatric conditions, including minor mood disorders, ADHD, cannabis use disorders, and eating disorders. We identified a decision tree consisting of six items from RIPoSt-40 that effectively detected CSED, with accuracy, sensitivity, specificity, positive and negative predictive values of 80 % or higher in both the training and testing sets. LIMITATIONS: Tertiary-level; no consensus on criteria; sample size. CONCLUSION: The screening version of the Reactivity, Intensity, Polarity, and Stability questionnaire (RIPoSt-SV) demonstrates promise as a valuable tool for ED screening in clinical settings.

Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis.

BACKGROUND: The aim of this study was to investigate the diagnostic value of ML techniques based on sMRI or/and fMRI for ADHD. METHODS: We conducted a comprehensive search (from database creation date to March 2024) for relevant English articles on sMRI or/and fMRI-based ML techniques for diagnosing ADHD. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve and area under the curve (AUC) were calculated to assess the diagnostic value of sMRI or/and fMRI-based ML techniques. The I2 test was used to assess heterogeneity and the source of heterogeneity was investigated by performing a meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. RESULTS: Forty-three studies were included in the systematic review, 27 of which were included in our meta-analysis. The pooled sensitivity and specificity of sMRI or/and fMRI-based ML techniques for the diagnosis of ADHD were 0.74 (95 % CI 0.65-0.81) and 0.75 (95 % CI 0.67-0.81), respectively. SROC curve showed that AUC was 0.81 (95 % CI 0.77-0.84). Based on these findings, the sMRI or/and fMRI-based ML techniques have relatively good diagnostic value for ADHD. LIMITATIONS: Our meta-analysis specifically focused on ML techniques based on sMRI or/and fMRI studies. Since EEG-based ML techniques are also used for diagnosing ADHD, further systematic analyses are necessary to explore ML methods based on multimodal medical data. CONCLUSION: sMRI or/and fMRI-based ML technique is a promising objective diagnostic method for ADHD.

Attention-deficit Hyperactivity Disorder and Autism Spectrum Disorder: Towards Better Diagnosis and Management.

Background: Attention-deficit hyperactivity disorder (ADHA) is one of the most common comorbid disorders of autism spectrum disorder (ASD) that can accompany autism, triggered by it, or be a consequence of it. Objective: This review explored the prevalence of the comorbidity of both disorders, neurobiological background, symptoms, latest assessment methods, and therapeutic approaches. Results and Discussion: It concluded that effective assessment, diagnosis and management of ADHD in ASD children and adults is essential for this group of patients to thrive and live a good quality of life. Further research is recommended to explore the most effective intervention for such important members of our society. Conclusion: More studies are needed to understand the mechanisms underlying these comorbidities, and to prevent the misdiagnosis and mismanagement of these disorders. Also, to develop up to date personalized therapeutic plans for such children.

Relationships of gaming disorder, ADHD, and academic performance in university students: A mediation analysis.

This study investigates the intersection of Gaming Disorder (GD) and Attention-Deficit/Hyperactivity Disorder (ADHD), and Grade Point Average (GPA), among university students, a critical demographic often overlooked in research on these disorders. A sample of 348 university students was analyzed using the IGD-20 Test for risk of GD, the Adult ADHD Self-Report Scale (ASRS-v1.1) for ADHD symptoms, and GPA as a metric of academic performance. The findings indicate that 4.3% of the surveyed sample scored within the range for GD. The prevalence was higher in males, with 5.3% of the male cohort affected, compared to 1.2% of the female cohort. Significantly, the prevalence of ADHD was substantially higher in the GD group (35.7%) than in the non-GD group (24.2%). Further, ADHD symptoms were found to be a stronger predictor of GD in females than in males. Incorporating the mediating role of Gaming Disorder, this study also probes into how GD may serve as an intermediary in the impact of ADHD on academic performance. By examining the intricate relationship between these disorders, our findings suggest that GD exacerbates the negative effects of ADHD on academic performance, thereby underscoring the potential for Gaming Disorder to act as a bridge in this dynamic. This mediation analysis clarifies how ADHD may indirectly impact academic performance through GD. The study reveals a positive correlation between ADHD symptoms and GD severity, which in turn correlates negatively with academic achievement. In addition, the findings underscore the need for gender-sensitive interventions and highlight the importance of considering the comorbidity of ADHD and GD in academic settings, advocating for systematic screening for GD among students with ADHD, and vice versa. The dual challenges posed by ADHD and GD should be addressed to prevent their escalation into pervasive academic and psychosocial adversities.

An updated review on animal models to study attention-deficit hyperactivity disorder.

Attention-deficit hyperactivity disorder (ADHD) is a neuropsychiatric disorder affecting both children and adolescents. Individuals with ADHD experience heterogeneous problems, such as difficulty in attention, behavioral hyperactivity, and impulsivity. Recent studies have shown that complex genetic factors play a role in attention-deficit hyperactivity disorders. Animal models with clear hereditary traits are crucial for studying the molecular, biological, and brain circuit mechanisms underlying ADHD. Owing to their well-managed genetic origins and the relative simplicity with which the function of neuronal circuits is clearly established, models of mice can help learn the mechanisms involved in ADHD. Therefore, in this review, we highlighting the important genetic animal models that can be used to study ADHD.

Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder.

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview.

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder commonly seen in childhood that leads to behavioural changes in social development and communication patterns, often continues into undiagnosed adulthood due to a global shortage of psychiatrists, resulting in delayed diagnoses with lasting consequences on individual's well-being and the societal impact. Recently, machine learning methodologies have been incorporated into healthcare systems to facilitate the diagnosis and enhance the potential prediction of treatment outcomes for mental health conditions. In ADHD detection, the previous research focused on utilizing functional magnetic resonance imaging (fMRI) or Electroencephalography (EEG) signals, which require costly equipment and trained personnel for data collection. In recent years, speech and text modalities have garnered increasing attention due to their cost-effectiveness and non-wearable sensing in data collection. In this research, conducted in collaboration with the Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust, we gathered audio data from both ADHD patients and normal controls based on the clinically popular Diagnostic Interview for ADHD in adults (DIVA). Subsequently, we transformed the speech data into text modalities through the utilization of the Google Cloud Speech API. We extracted both acoustic and text features from the data, encompassing traditional acoustic features (e.g., MFCC), specialized feature sets (e.g., eGeMAPS), as well as deep-learned linguistic and semantic features derived from pre-trained deep learning models. These features are employed in conjunction with a support vector machine for ADHD classification, yielding promising outcomes in the utilization of audio and text data for effective adult ADHD screening. Clinical impact: This research introduces a transformative approach in ADHD diagnosis, employing speech and text analysis to facilitate early and more accessible detection, particularly beneficial in areas with limited psychiatric resources. Clinical and Translational Impact Statement: The successful application of machine learning techniques in analyzing audio and text data for ADHD screening represents a significant advancement in mental health diagnostics, paving the way for its integration into clinical settings and potentially improving patient outcomes on a broader scale.