The Maternal Adversity, Vulnerability and Neurodevelopment Project: Theory and Methodology
Bibliographic record
Abstract
OBJECTIVE: To describe the theory and methodology of the multi-wave, prospective Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) study. The goal of MAVAN is to examine the pre- and postnatal influences, and their interaction, in determining individual differences in mental health. METHOD: MAVAN is a community-based, birth cohort study of pregnant Canadian mothers and their offspring. Dyads are assessed longitudinally, with multiple assessments of both mother and child in home and laboratory across the child's development. Study measures, including assessments of cognitive and emotional function, are described. The study uses a candidate gene approach to examine gene-environment interdependence in specific developmental outcomes. Finally, the study includes measures of both brain-based phenotypes and metabolism to explore comorbidities associated with child obesity. One of the unique features of the MAVAN protocol is the extensive measures of the mother-child interaction. The relation between these measures will be discussed. RESULTS: Evidence from the MAVAN project shows interesting results about maternal care, families, and child outcomes. In our review, preliminary analyses showing the correlations between measures of maternal care are reported. As predicted, early evidence suggests that maternal care measures are positively correlated, over time. CONCLUSIONS: This review provides evidence for the feasibility and value of laboratory-based measures embedded within a longitudinal birth cohort study. Though retention of the samples has been a challenge of MAVAN, they are within a comparable range to other studies of this nature. Indeed, the trade-off of somewhat greater participant burden has allowed for a rich database. The results yielded from the MAVAN project will not only describe typical development but also possible targets for intervention. Understanding certain endophenotypes will shed light on the pathogenesis of various mental and physical disorders, as well as their interrelation.
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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 | 0.067 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".