Prenatal Exposure And Child brain and mental Health (PEACH) study: protocol for a cohort study of children and youth with prenatal alcohol exposure
Bibliographic record
Abstract
INTRODUCTION: Fetal alcohol spectrum disorder (FASD), which is caused by prenatal alcohol exposure (PAE), affects an estimated 4% of North Americans, and is the most common preventable cause of intellectual disability. Mental health problems, including anxiety and depression, are experienced by nearly all individuals with FASD. However, there is very limited knowledge about effective mental health treatments for individuals with FASD; effective treatments are hindered in part due to a lack of understanding of the basic neurobiology underlying internalising disorders in youth with FASD. METHODS AND ANALYSIS: The Prenatal Exposure And Child brain and mental Health (PEACH) study includes children aged 7-18 years. We will use longitudinal neuroimaging (anatomical T1-weighted, diffusion and passive viewing function MRI) and mental health assessments (Behaviour Assessment Scale for Children, Multi-dimensional Anxiety Scale for Children, Children's Depression Inventory (CDI-2), Kiddie Scale of Affective Disorders) to: (1) characterise brain development trajectories in youth with FASD, (2) determine whether brain alterations mediate increased anxiety and depression in youth with FASD and (3) identify baseline brain features that predict changes of anxiety and depression symptoms over the next 2 years. All of this will be done while considering sex and adverse postnatal experiences, which can significantly impact mental health and brain outcomes. This project will forge new understanding of FASD and mental health from a neurobiological perspective, highlighting key time periods (ie, sensitive windows) and brain regions (ie, that may be susceptible to neurostimulation), while identifying factors that predict individual trajectories of anxiety and depression symptoms. ETHICS AND DISSEMINATION: This study was approved by the University of Calgary Conjoint Health Research Ethics Board and the University of Alberta Health Research Ethics Board. Study results will be disseminated in peer-reviewed journals, at relevant conferences and in conjunction with our knowledge mobilisation partners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".