International Consensus on Standard Outcome Measures for Neurodevelopmental Disorders: A Consensus Statement.

Importance: The use of evidence-based standardized outcome measures is increasingly recognized as key to guiding clinical decision-making in mental health. Implementation of these measures into clinical practice has been hampered by lack of clarity on what to measure and how to do this in a reliable and standardized way. Objective: To develop a core set of outcome measures for specific neurodevelopmental disorders (NDDs), such as attention-deficit/hyperactivity disorder (ADHD), communication disorders, specific learning disorders, and motor disorders, that may be used across a range of geographic and cultural settings. Evidence Review: An international working group composed of clinical and research experts and service users (n = 27) was convened to develop a standard core set of accessible, valid, and reliable outcome measures for children and adolescents with NDDs. The working group participated in 9 video conference calls and 8 surveys between March 1, 2021, and June 30, 2022. A modified Delphi approach defined the scope, outcomes, included measures, case-mix variables, and measurement time points. After development, the NDD set was distributed to professionals and service users for open review, feedback, and external validation. Findings: The final set recommends measuring 12 outcomes across 3 key domains: (1) core symptoms related to the diagnosis; (2) impact, functioning, and quality of life; and (3) common coexisting problems. The following 14 measures should be administered at least every 6 months to monitor these outcomes: ADHD Rating Scale 5, Vanderbilt ADHD Diagnostic Rating Scale, or Swanson, Nolan, and Pelham Rating Scale IV; Affective Reactivity Index; Children's Communication Checklist 2; Colorado Learning Disabilities Questionnaire; Children's Sleep Habits Questionnaire; Developmental-Disability Children's Global Assessment Scale; Developmental Coordination Disorder Questionnaire; Family Strain Index; Intelligibility in Context Scale; Vineland Adaptive Behavior Scale or Repetitive Behavior Scale-Revised and Social Responsiveness Scale; Revised Child Anxiety and Depression Scales; and Yale Global Tic Severity Scale. The external review survey was completed by 32 professionals and 40 service users. The NDD set items were endorsed by more than 70% of professionals and service users in the open review survey. Conclusions and Relevance: The NDD set covers outcomes of most concern to patients and caregivers. Use of the NDD set has the potential to improve clinical practice and research.

Polygenic Resilience Scores are Associated with Lower Penetrance of Schizophrenia Risk Genes, Protection Against Psychiatric and Medical Disorders, and Enhanced Mental Well-Being and Cognition.

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. Recently, we discovered the first genomic resilience profile for SCZ, completely independent from the established risk loci for SCZ. We posited that these resilience loci protect against SCZ for those having a heighted genomic risk for SCZ. Nevertheless, our understanding of genetic resilience remains limited. It remains unclear whether resilience loci foster protection against adverse states associated with SCZ risk related to clinical, cognitive, and brain-structural phenotypes. To address this knowledge gap, we analyzed data from 487,409 participants from the UK Biobank, and found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and non-psychiatric medical disorders (such as asthma, cardiovascular disease, digestive disorders, metabolic disorders, and external causes of morbidity and mortality). Resilience loci also protected against self-harm behaviors, improved fluid intelligence, and larger whole-brain and brain-regional sizes. Overall, this study sheds light on the range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Our findings indicate that resilience loci may offer protection against serious psychiatric and medical outcomes, co-morbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.

Individualized prediction models in ADHD: a systematic review and meta-regression.

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (ß = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

Post-COVID-19 Mental Health Distress in 13 Million Youth: A Retrospective Cohort Study of Electronic Health Records.

OBJECTIVE: To investigate the impact of the SARS-CoV-2 infection on the rates of mental disorders in youth. METHOD: The study involved 7,519,465 children and 5,338,496 adolescents from the TriNetX Research Network, all without prior mental disorder histories. Among them, 290,145 children and 223,667 adolescents had SARS-CoV-2-positive tests or confirmed COVID-19 diagnoses. Kaplan-Meier survival analysis was used to evaluate the probability of developing new mental disorders (any codes in International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) F01-F99 category and suicidal behaviors) within 2 years post infection, compared to the propensity score-matched youth who were never infected. RESULTS: Within 2 years post SARS-CoV-2 infection, children had a probability of 0.15 in acquiring new psychiatric diagnoses, compared to 0.026 for matched non-infected children; adolescents had a 0.19 probability against 0.05 for their non-infected counterparts. The hazard ratio (HR) was 6.0 (95% CI = 5.8-6.3) for children and 4.2 for adolescents (95% CI = 4.1-4.4), with children vs adolescents HR of 1.4 (95% CI = 1.36-1.51). Elevated HRs were observed for almost all subcategories of mental disorders and suicidal behaviors, with variations based on sex, severity of SARS-CoV-2 infection, and viral variants. COVID-19 was similar to other respiratory infections in increasing the rate of mental disorders in adolescents, but had a significantly higher effect on children (HR = 1.57, 95% CI =1.53-1.61). CONCLUSION: This study revealed significant mental health distress following SARS-CoV-2 infection in youth, which was more pronounced in children than in adolescents. These findings underscore the urgent need to support at-risk youth, particularly those who contracted SARS-CoV-2 at younger ages and had more severe infections. DIVERSITY & INCLUSION STATEMENT: One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science.

Estimating heterogeneity of treatment effect in psychiatric clinical trials.

Currently, placebo-controlled clinical trials report mean change and effect sizes, which masks information about heterogeneity of treatment effects (HTE). Here, we present a method to estimate HTE and evaluate the null hypothesis (H0) that a drug has equal benefit for all participants (HTE=0). We developed measure termed 'estimated heterogeneity of treatment effect' or eHTE, which estimates variability in drug response by comparing distributions between study arms. This approach was tested across numerous large placebo-controlled clinical trials. In contrast with variance-based methods which have not identified heterogeneity in psychiatric trials, reproducible instances of treatment heterogeneity were found. For example, heterogeneous response was found in a trial of venlafaxine for depression (peHTE=0.034), and two trials of dasotraline for binge eating disorder (Phase 2, peHTE=0.002; Phase 3, 4mg peHTE=0.011; Phase 3, 6mg peHTE=0.003). Significant response heterogeneity was detected in other datasets as well, often despite no difference in variance between placebo and drug arms. The implications of eHTE as a clinical trial outcomes independent from central tendency of the group is considered and the important of the eHTE method and results for drug developers, providers, and patients is discussed.

From Consensus Statement to Pills to Pixels: New Innovations in Attention-Deficit/Hyperactivity Disorder Care.

Objectives: This review aims to present recent innovations and advancements in attention-deficit/hyperactivity disorder (ADHD) care, encompassing international consensus statement, new medication formulations, digital therapeutics, and neurostimulation devices. Methods: A comprehensive literature search of relevant articles published in the past five years was conducted, emphasizing the evidence base, efficacy, safety, and practical implications of these advancements. Results: The World Federation of ADHD Consensus Statement offers an updated diagnostic and treatment framework rooted in global scientific evidence. There are several newer ADHD medication formulations, including a nonstimulant (Viloxazine extended release) and the first transdermal amphetamine patch approved to treat ADHD. These options offer some unique benefits to personalize treatment based on symptom profile, lifestyle, preferences, and response. Digital tools offer additional means to restructure environments for individuals with ADHD, reducing impairment and reliance on others. In addition, digital therapeutics enhance access, affordability, personalization, and feasibility of ADHD care, complementing or augmenting existing interventions. Trigeminal nerve stimulation emerges as a well-tolerated nonpharmacological, device-based treatment for pediatric ADHD, with initial trials indicating effect sizes comparable to nonstimulant medications. Conclusions: These innovations in ADHD care represent clinically significant new treatment options and opportunities for personalized care. Health care professionals should integrate these developments into clinical practice, mindful of individual patient and family needs and preferences. Future research should assess long-term outcomes, cost-effectiveness, and acceptability of these innovations.

AACAP Endorses the Inclusion of Methylphenidate in the WHO Model Lists of Essential Medicines.

Despite decades of clinical use and a large body of evidence, the WHO continues to exclude methylphenidate for attention-deficit/hyperactivity disorder (ADHD) from its EML.1 The exclusion of methylphenidate has dire implications for millions of individuals with ADHD worldwide, especially those living in low and low-middle income countries (LMIC), where governmental decisions to make medicines available are contingent on EML listing.

Understanding Environmental Exposures and ADHD: a Pathway Forward.

This commentary addresses a series of articles in Prevention Science about environmental causes of attention deficit hyperactivity disorder (ADHD). It provides an overview of their key findings and places them in a broader context to facilitate their interpretation. Each of the articles included in the special issue is a meta-analysis assessing the association of ADHD with several environmental exposures. Each of the author teams systematically searched for articles and defined eligibility criteria. They assured that the measurement of risk factors preceded the measurement of ADHD. Most of the analyses are based on many studies with many participants in the constituent studies. As is typical of any observational epidemiologic study, the constituent studies could not correct for all possible confounds because some were not measured, and some are unknown. For this reason, these meta-analyses may have documented confounded associations, which calls for cautious interpretations. None of the constituent studies assessed what might be the most important type of confounding, familial, and genetic confounding, which occurs when the environmental exposure being studied is correlated with the genetic risk of the disorder being studied or other familial risk factors. Addressing familial/genetic confounding requires a genetically informed study. Because of these issues, the results presented here are intriguing but require further examination before one can conclude that the reported associations correspond to causal events for ADHD. A pathway forward is suggested by drawing parallels between genomic and exposure research.

Adult ADHD Symptoms in a Large Metropolitan Area From Brazil: Prevalence and Associations with Psychiatric Comorbidity, Bullying, Sexual Abuse, and Quality of Life.

OBJECTIVE: The aim of this study was to investigate the prevalence and psychiatric correlates of symptomatic ADHD in a large metropolitan area of a middle-income country. METHODS: An in-person household survey with randomly selected 2,297 adults aged 19 to 60 from Rio de Janeiro, Brazil, assessed by trained lay interviewers. The Adult Self-Rating Scale Screener (ASRS-6) was used. Chi-square and logistic regression were conducted. RESULTS: ADHD prevalence was 4.59 (95% CI [3.56, 5.44]). Those with ADHD were younger and more often unemployed; they displayed more psychiatric symptoms (depression, anxiety, and alcohol abuse) and a history of bullying and sexual abuse. They also had worse physical health indicators. Findings remained significant when controlling for socioeconomic variables. CONCLUSION: Adults with symptomatic ADHD from a large metropolitan area in Brazil show a pattern of findings consistent with what has been observed in higher-income countries.

Attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD; also known as hyperkinetic disorder) is a common neurodevelopmental condition that affects children and adults worldwide. ADHD has a predominantly genetic aetiology that involves common and rare genetic variants. Some environmental correlates of the disorder have been discovered but causation has been difficult to establish. The heterogeneity of the condition is evident in the diverse presentation of symptoms and levels of impairment, the numerous co-occurring mental and physical conditions, the various domains of neurocognitive impairment, and extensive minor structural and functional brain differences. The diagnosis of ADHD is reliable and valid when evaluated with standard diagnostic criteria. Curative treatments for ADHD do not exist but evidence-based treatments substantially reduce symptoms and/or functional impairment. Medications are effective for core symptoms and are usually well tolerated. Some non-pharmacological treatments are valuable, especially for improving adaptive functioning. Clinical and neurobiological research is ongoing and could lead to the creation of personalized diagnostic and therapeutic approaches for this disorder.

Effects of ADHD and ADHD treatment on glycemic management in type 1 diabetes: A systematic review and meta-analysis of observational studies.

AIMS: Studies suggested a higher prevalence of Attention-deficit/hyperactivity disorder (ADHD) in individuals with Type 1 Diabetes Mellitus (T1D). However, it is unclear how ADHD impacts glycemia and diabetes-related complications. This systematic review and meta-analysis aimed to investigate the effect of ADHD and ADHD medications on HbA1c and acute complications in T1D. METHODS: A literature search was conducted in PubMed, EMBASE, CINAHL, Scopus, PsycINFO, CENTRAL, and Web of Science collections up to November 22, 2023. Seventeen studies were selected for the systematic review by independent reviewers, with twelve included in the meta-analysis. RESULTS: Mean HbA1c levels were significantly higher in T1D individuals with ADHD compared to those without ADHD (MD = 0.60; 95 % CI: 0.41, 0.79; I2 = 90.1 %; p-value < 0.001). The rates of suboptimal HbA1c levels, hospitalization, diabetic ketoacidosis, and hypoglycemia were all substantially higher in T1D individuals with ADHD than those without ADHD. No difference was found in mean HbA1c between those who received ADHD treatment and those who did not (mean difference = -0.52; 95 % confidence interval: -1.16, 0.13; I2 = 78.6 %; p-value = 0.12). CONCLUSIONS: ADHD is associated with higher HbA1c and increased acute diabetes-related complications. More research is needed to assess the effects of ADHD treatments on T1D management.

ADHD medicine consumption in Europe after COVID-19: catch-up or trend change?

BACKGROUND: Although the COVID-19 pandemic and its implications have been associated with mental health services utilization and medication consumption, there is no longitudinal study on the long-term impact on ADHD medication use trends. METHODS: This study examines the European ADHD medication consumption in 2020 to 2022 compared to the predicted consumption assuming the persistence of pre-pandemic trends. Predictions are calculated using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. RESULTS: While European ADHD medication sales recorded a drop in 2020, they returned to the predicted level in 2021, even slightly exceeding it. In 2022, we found a clear exceedance of the predicted level by 16.4% on average at country level. Furthermore, the increase in consumption growth in the post-pandemic period (2021-2022) compared to the pre-pandemic period (2014-2019) was significant in 26 of the 28 European countries under consideration. CONCLUSION: There is strong evidence of a trend change in the ADHD medicine consumption growth throughout Europe after the COVID-19 pandemic.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

Differences in Primary Care Management of Patients With Adult Attention Deficit Hyperactivity Disorder (ADHD) Based on Race and Ethnicity.

OBJECTIVE: Examine differences in care patterns around adult ADHD between race (White/Non-White) and ethnic (Hispanic/Non-Hispanic) groups utilizing existing quality measures (QMs), concerning diagnosis, treatment, and medication prescribing. METHODS: The AAFP National Research Network in partnership with SUNY Upstate Medical used an EHR dataset to evaluate achievement of 10 ADHD QMs. The dataset was obtained from DARTNet Institute and includes 4 million patients of 873 behavioral and primary care practices with at least 100 patients from 2010 to 2020. Patients 18-years or older with adult ADHD were included in this analysis. RESULTS: White patients and Non-Hispanic/Latinx patients were more likely to achieve these QMs than Non-White patients and Hispanic/Latinx patients, respectively. Differences between groups concerning medication and monitoring demonstrate a disparity for Non-White and Hispanic/Latinx populations. CONCLUSIONS: Using QMs in EHR data can help identify gaps in ADHD research. There is a need to continue investigating disparities of quality adult ADHD care.

ADHD in Adults: Does Age at Diagnosis Matter?

OBJECTIVE: To provide additional information about clinical features associated with adult ADHD in patients diagnosed in childhood compared to those first diagnosed in adulthood. METHOD: We stratified a sample of adults with ADHD into patients diagnosed in childhood versus adulthood and compared demographic and clinical characteristics. RESULTS: We found similar clinical features in adults diagnosed in childhood and adults diagnosed in adulthood. Among those diagnosed in adulthood, 95% reported symptom onset in youth. Our results do not support the hypothesis that ADHD diagnosed in adulthood is due to misinterpreting symptoms of other disorders as ADHD. They also suggest incorporating behavioral signs of executive dysfunction into diagnostic criteria for ADHD in adults may increase diagnostic sensitivity. CONCLUSION: These results support the validity of ADHD diagnoses in adulthood, as these adults show similar clinical profiles to those diagnosed in youth. Our results also suggest that if adult-onset ADHD exists, it is rare.

The Association Between Repeated Measured Febrile Episodes During Early Childhood and Attention Deficit Hyperactivity Disorder: A Large-Scale Population-Based Study.

OBJECTIVE: We examined the association between the number, magnitude, and frequency of febrile episodes during the 0 to 4 years of life and subsequent diagnosis of ADHD. METHODS: This population-based case-control study in an Israeli HMO, Leumit Health Services (LHS), uses a database for all LHS members aged 5 to 18 years between 1/1/2002 and 1/30/2022. The number and magnitude of measured fever episodes during the 0 to 4 years were recorded in individuals with ADHD (N = 18,558) and individually matched non-ADHD controls in a 1:2 ratio (N = 37,116). RESULTS: A significant, independent association was found between the number and magnitude of febrile episodes during the 0 to 4 years and the probability of a later diagnosis of ADHD. Children who never had a measured temperature >37.5°C had a significantly lower rate of ADHD (OR = 0.834, 95% CI [0.802, 0.866], p < .0001). CONCLUSIONS: Febrile episodes during 0 to 4 years are associated with a significantly increased rate of a later diagnosis of ADHD in a doseresponse relationship.