Just DO(HaD) It! Testing the clinical potential of the DOHaD hypothesis to prevent mental disorders using experimental study designs
Bibliographic record
Abstract
Optimal early cognitive and emotional development are vital to reaching one's full potential and represent our best chance to improve the mental health of the population. The developmental origins of health and disease (DOHaD) hypothesis posits that adverse perinatal exposures can alter physiology and increase disease risk. As physiological plasticity decreases with age, interventions applied during gestation may hold the most promise for reducing the impact of mental disorders across the lifespan. However, this vast clinical potential remains largely unrealized as the majority of human DOHaD research is observational in nature. The application of more rigorous experimental designs [e.g. Randomized Controlled Trials (RCTs)] not only represents a major step toward unlocking this potential, but are required to fully test the scientific validity of the DOHaD hypothesis as it pertains to mental illness. Here, we argue that the optimization of maternal diet and exercise during pregnancy represents our best chance to improve offspring neurodevelopment and reduce the burden of mental disorders. Follow-up studies of the offspring of pregnant women enrolled in new and existing RCTs of maternal gestational nutrition+exercise interventions are required to determine if acting during pregnancy can prevent and/or meaningfully reduce the prevalence and severity of mental disorders in the population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".