Introduction
Benzodiazepine (BDZP) and/or z‐hypnotic dispensing during pregnancy has increased globally, as have rates of autism spectrum disorder (ASD) and attention‐deficit hyperactivity disorder ...(ADHD). This systematic review and meta‐analysis aimed to estimate the association between gestational exposure to BDZP and/or z‐hypnotics and diagnosis of ASD or ADHD in offspring.
Methods
We searched MEDLINE, EMBASE, and SCOPUS from inception till December 2023 for relevant English‐language articles. Outcomes of interest were risk of ASD and ADHD, two independent primary outcomes, in children exposed anytime during pregnancy to BDZP and/or z‐hypnotics versus those unexposed. Secondary outcomes were trimester‐wise analyses. Using a random effects model, we pooled the overall and trimester‐wise hazard ratios (HRs), with 95% confidence intervals (CIs), separately for risk of ASD and ADHD.
Results
We found six eligible retrospective cohort studies and no case–control studies. There was no increased risk of ASD associated with anytime gestational BDZP and/or z‐hypnotic exposure (primary outcome, HR, 1.10; 95% CI, 0.81–1.50; 4 studies; n = 3,783,417; 80,270 exposed, 3,703,147 unexposed) nor after first trimester exposure (HR, 1.15; 95% CI, 0.83–1.58; 3 studies; n = 1,539,335; 70,737 exposed, 1,468,598 unexposed) or later trimester exposures. A very small but significantly increased risk of ADHD was noted with anytime gestational exposure to these drugs (primary outcome, HR, 1.07; 95% CI, 1.03–1.12; 4 studies; n = 2,000,777; 78,912 exposed, 1,921,865 unexposed) and also with (only) second trimester exposure (HR, 1.07; 95% CI, 1.03–1.12; 3 studies; n = 1,539,281; 33,355 exposed, 1,505,926 unexposed). Findings were consistent in sensitivity analyses.
Conclusion
Gestational exposure to benzodiazepines or z‐hypnotics was not associated with an increased risk of ASD and with only a marginally increased risk of ADHD in offspring. Given the likelihood of confounding by indication and by unmeasured variables in the original studies, our findings should reassure women who need these medications for severe anxiety or insomnia during pregnancy.
This study aimed to analyze the association between Attention Deficit/Hyperactivity Disorder (ADHD) and Internet addiction (IA).
A systematic literature search was performed in four online databases ...in total including CENTRAL, EMBASE, PubMed and PsychINFO. Observational studies (case-control, cross-sectional and cohort studies) measuring the correlation between IA and ADHD were screened for eligibility. Two independent reviewers screened each article according to the predetermined inclusion criteria. A total of 15 studies (2 cohort studies and 13 cross-sectional studies) met our inclusion criteria and were included in the quantitative synthesis. Meta-analysis was conducted using RevMan 5.3 software.
A moderate association between IA and ADHD was found. Individuals with IA were associated with more severe symptoms of ADHD, including the combined total symptom score, inattention score and hyperactivity/impulsivity score. Males were associated with IA, whereas there was no significant correlation between age and IA.
IA was positively associated with ADHD among adolescents and young adults. Clinicians and parents should pay more attention to the symptoms of ADHD in individuals with IA, and the monitoring of Internet use of patients suffering from ADHD is also necessary. Longitudinal studies controlling for baseline mental health are needed.
Introduction
A lack of knowledge about attention‐deficit/hyperactivity disorder (ADHD) can contribute to feelings of distress and difficulty in seeking and accepting an ADHD diagnosis. The present ...study uses a Delphi consensus design to investigate the psychoeducational needs of adults with ADHD and the information about ADHD they would like included in digital health interventions for adults with ADHD. Inclusion of perspectives of service users in developing such interventions ensures that they are evidence based and addresses the risks of engagement barriers.
Methods
The expert panel consisted of 43 adults with ADHD (age range: 23–67 years). Panel members were asked to rate the importance of the proposed topics and provide additional suggestions. Suggested topics and topics that did not achieve consensus were included for ranking in the second round.
Results
Interquartile ratings were used to determine consensus. A high consensus was achieved in both rounds, with an agreement on 94% of topics in the first round and 98% in the second round. Most topics were rated as important or essential.
Conclusions
The findings highlighted that adults with ADHD want to learn about many different aspects of ADHD and the importance of considering their perspectives when developing psychosocial interventions. Findings can be applied when creating psychoeducational content for adult ADHD.
Patient or Public Contribution
Adults with ADHD were recruited to the Delphi panel to use an experts‐by‐experience approach. In doing so, we are engaging service users in the development of a psychoeducational smartphone app. The evaluation of the app will involve interviews with app users. Additionally, the present study was developed and conducted with ADHD Ireland, a charity based in Ireland that advocates for people with ADHD.
Background
Attention‐deficit/hyperactivity disorder (ADHD) and lower cognitive ability have been linked with increased likelihood of exposure to adversity. We hypothesized that these associations may ...be partly due to genetic factors.
Methods
We calculated polygenic scores for ADHD and intelligence and assessed psychopathology and general cognitive ability in a sample of 297 youth aged 5–27 years enriched for offspring of parents with mood and psychotic disorders. We calculated an adversity score as a mean of 10 indicators, including socio‐economic disadvantage, childhood maltreatment and bullying. We tested the effects of polygenic scores, externalizing symptoms and IQ on adversity scores using mixed‐effects linear regression.
Results
Externalizing symptoms and general cognitive ability showed expected positive and negative relationships with adversity, respectively. Polygenic scores for intelligence were unrelated to adversity, but polygenic scores for ADHD were associated with adversity (β = 0.23, 95% CI 0.13 to 0.34, p < .0001). ADHD polygenic scores uniquely explained 4.0% of variance in adversity score. The relationship between polygenic scores for ADHD and adversity was independently significant among individuals with (β = 0.49, 95% CI 0.25 to 0.75, p < .0001) and without (β = 0.14, 95% CI 0.02 to 0.26, p = .022) ADHD.
Conclusions
A genetic score indexing liability to ADHD was associated with exposure to adversity in early life. Previously observed associations between externalizing symptoms, lower cognitive ability and adversity may be partially attributed to genetic liability to ADHD.
Background
Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what ...distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review.
Scope and methodology
We first propose a neuroeconomic model of the decision‐making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self‐referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes.
Findings and conclusion
Based on clinical insights and considering each of the decision‐making stages in turn, we outline disorder‐specific hypotheses about impaired decision making in four childhood disorders: attention‐deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk‐averse, and self‐deprecating. A survey of current empirical indications related to these disorder‐specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research.
Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. In this review, we first propose a neuroeconomic model of the decision‐making process with four separate stages and suggest that the decision making is mediated by neuropsychological processes operating within three domains, with the processes underpinned by the interplay of multiple brain networks. Based on the clinical insights and considering each of the decision‐making stages in turn, we outline disorder‐specific hypotheses about impaired decision making in four childhood disorders. We hypothesize that decision making is inefficient, impulsive, and inconsistent in ADHD; reckless and insensitive to negative outcomes in CD; disengaged/perseverative/pessimistic in depression; and hesitant/risk‐aversive/self‐deprecating in anxiety. We conclude that the limited and fragmentary nature of the evidence base illustrates the need for a major research initiative in decision making in childhood disorders and highlight a number of themes to be considered in this future research.
Read the Commentary on this article at doi: 10.1111/jcpp.12531
Children of women treated with antidepressants during pregnancy are more likely to develop neurodevelopmental problems than are unexposed children. Associations between prenatal antidepressant ...exposure and neurodevelopmental problems could reflect a causal effect or could be partially or fully explained by other factors that differ between exposed and unexposed offspring, including having mothers with conditions requiring antidepressant treatment (e.g. depression), environmental risk factors, and/or genetic risk factors shared across disorders. This translational review aims to provide a brief overview of findings from rodent experiments and critically evaluate observational studies in humans to assess the extent to which associations between prenatal antidepressant exposure and neurodevelopmental problems are due to causal mechanisms versus other influences. We focus our review on two important neurodevelopmental outcomes – autism spectrum disorder (ASD) and attention‐deficit/hyperactivity disorder (ADHD). In general, rodent studies have reported adverse effects of perinatal antidepressant exposure on neurodevelopment. Between‐species differences raise questions about the generalizability of these findings to humans. Indeed, converging evidence from studies using multiple designs and approaches suggest that observed associations between prenatal antidepressant exposure and neurodevelopmental problems in humans are largely due to confounding factors. We also provide specific recommendations for future research. Animal research should explicitly evaluate the impact of timing of exposure and dosage of medications, as well as better map outcome measures in rodents to human neurodevelopmental problems. Observational studies should investigate specific confounding factors, specific antidepressant drugs and classes, the potential impact of timing of exposure, and a wider range of other potential offspring outcomes. The findings summarized in this review may help women and their doctors make informed decisions about antidepressant use during pregnancy by providing reassurance that use of these medications during pregnancy is unlikely to substantially increase the risk of ASD and ADHD.
Read the Commentary on this article at doi: 10.1111/jcpp.13036
Recent clinical studies, in both children/adolescents and adults, have shown the extreme neuropsychological heterogeneity of attention‐deficit hyperactivity disorder (ADHD): specific ...neuropsychological deficits have been found only in a minority of individuals, with no direct correlation between discrete cognitive performances and the trajectory of clinical symptoms. Deficits in specific neuropsychological functions may be common in ADHD, but nevertheless no cognitive or neuropsychological profile may fully explain the disorder. Sex differences in the ADHD presentation, both at a neuropsychological and clinical level, also contribute to this clinical and neuropsychological heterogeneity. At a neuropsychological level, females with ADHD may show greater working memory problems, poorer vocabulary skills and worse visual spatial reasoning. Structural and functional imaging study also show discrete differences across sex; however, the great majority of clinical studies mainly or exclusively include male participants with insufficient data to draw firm conclusions on sex differences within the disorder. Here, we report the recent literature data, discussing still open research questions about the clinical presentation, neuroimaging findings, and neuropsychological functioning in ADHD with a focus on the impact of sex differences—a deeper insight in these unresolved issues may have relevant clinical and therapeutic implications for tailored, effective, and long‐lasting interventions.
ADHD and autism symptoms in youth: a network analysis Farhat, Luis C.; Brentani, Helena; Toledo, Victor Hugo Calegari ...
Journal of child psychology and psychiatry,
February 2022, 2022-02-00, 20220201, Volume:
63, Issue:
2
Journal Article
Peer reviewed
Open access
Background
Previous research investigating the overlap between attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (henceforth, autism) symptoms in population samples have ...relied on latent variable modeling in which averaged scores representing dimensions were derived from observed symptoms. There are no studies evaluating how ADHD and autism symptoms interact at the level of individual symptom items.
Methods
We aimed to address this gap by performing a network analysis on data from a school survey of children aged 6–17 years old (N = 7,405). ADHD and autism symptoms were measured via parent‐report on the Swanson, Nolan, Pelham‐IV questionnaire and the Childhood Autism Spectrum test, respectively.
Results
A relatively low interconnectivity between ADHD and autism symptoms was found with only 10.06% of possible connections (edges) between one ADHD and one autism symptoms different than zero. Associations between ADHD and autism symptoms were significantly weaker than those between two symptoms pertaining to the same construct. Select ADHD symptoms, particularly those presenting in social contexts (e.g. ‘talks excessively’, ‘does not wait turn’), showed moderate‐to‐strong associations with autism symptoms, but some were considered redundant to autism symptoms.
Conclusions
The present findings indicate that individual ADHD and autism symptoms are largely segregated in accordance with diagnostic boundaries corresponding to these conditions in children and adolescents from the community. These findings could improve our clinical conceptualization of ADHD and autism and guide advancements in diagnosis and treatment.
Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI ...data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD.
High-resolution three-dimensional MR images were acquired from 55 ADHD subjects and 55 healthy controls. Multiple brain measures (cortical thickness, etc.) were calculated using a fully automated procedure in the FreeSurfer software package. In total, 340 cortical features were automatically extracted from 68 brain segments with 5 basic cortical features. F-score and SFS methods were adopted to select the optimal features for ADHD classification. Both ELM and SVM were evaluated for classification accuracy using leave-one-out cross-validation.
We achieved ADHD prediction accuracies of 90.18% for ELM using eleven combined features, 84.73% for SVM-Linear and 86.55% for SVM-RBF. Our results show that ELM has better computational efficiency and is more robust as sample size changes than is SVM for ADHD classification. The most pronounced differences between ADHD and healthy subjects were observed in the frontal lobe, temporal lobe, occipital lobe and insular.
Our ELM-based algorithm for ADHD diagnosis performs considerably better than the traditional SVM algorithm. This result suggests that ELM may be used for the clinical diagnosis of ADHD and the investigation of different brain diseases.
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