ReviewJournal of child psychology and psychiatry, and allied disciplines2016
Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders--promises and limitations.
Review in Journal of child psychology and psychiatry, and allied disciplines, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Barriers to seeing a health care provider among rural adolescents with poorly controlled asthma.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2025Article
- From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care.Biomedicines · 2025Review
- Neural correlates of negative life events and their relationships with alcohol and cannabis use initiation.Dialogues in clinical neuroscience · 2023Article
- Statistical Learning Methods for Neuroimaging Data Analysis with Applications.Annual review of biomedical data science · 2023Review
- Association between Sexual Activity during Pregnancy, Pre- and Early-Term Birth, and Vaginal Cytokine Inflammation: A Prospective Study of Black Women.Healthcare (Basel, Switzerland) · 2023Article
- An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Neurite Orientation Dispersion and Density Imaging in Psychiatric Disorders: A Systematic Literature Review and a Technical Note.Biological psychiatry global open science · 2023Review
- Understanding the nature of face processing in early autism: A prospective study.Journal of psychopathology and clinical science · 2022Article
- Seeing the forest for the trees: Predicting attendance in trials for co-occurring PTSD and substance use disorders with a machine learning approach.Journal of consulting and clinical psychology · 2021Article
- Cognitive Dimensions of Learning in Children With Problems in Attention, Learning, and Memory.Journal of educational psychology · 2021Article
- All for one and one for all: heterogeneity of genetic etiologies in neurodevelopmental psychiatric disorders.Current opinion in genetics & development · 2021Review
- Cntn4, a risk gene for neuropsychiatric disorders, modulates hippocampal synaptic plasticity and behavior.Translational psychiatry · 2021Article
- Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.Journal of healthcare engineering · 2021Article
- Beyond the Core-Deficit Hypothesis in Developmental Disorders.Current directions in psychological science · 2020Article
- Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements.Seminars in pediatric neurology · 2020Review
- Transdiagnostic Brain Mapping in Developmental Disorders.Current biology : CB · 2020Article
- Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey.Frontiers in neuroinformatics · 2020Review
- Transdiagnostic associations across communication, cognitive, and behavioural problems in a developmentally at-risk population: a network approach.BMC pediatrics · 2019Article
- Brain age prediction: Cortical and subcortical shape covariation in the developing human brain.NeuroImage · 2019Article
- Big data approaches to decomposing heterogeneity across the autism spectrum.Molecular psychiatry · 2019Review
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Authors and funding
2 authors.
Funding
Abstract
backgroundPsychiatric science remains descriptive, with a categorical nosology intended to enhance interobserver reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles.
findingsA paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality, and heterogeneity of neuropsychiatric data collected from multiple sources ('broad' data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits, and behaviors ('deep' data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders.
conclusionsWe highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.