Developmental origins of disruptive behaviour problems: the ‘original sin’ hypothesis, epigenetics and their consequences for prevention
Bibliographic record
Abstract
This paper reviews publications on developmental trajectories of disruptive behaviour (DB) problems (aggression, opposition-defiance, rule breaking, and stealing-vandalism) over the past decade. Prior to these studies two theoretical models had strongly influenced research on DB: social learning and disease onset. According to these developmental perspectives, children learn DB from their environment and onset of the disease is triggered by accumulated exposition to disruptive models in the environment, including the media. Most of the evidence came from studies of school age children and adolescents. Longitudinal studies tracing developmental trajectories of DB from early childhood onwards suggest an inversed developmental process. DB are universal during early childhood. With age, children learn socially acceptable behaviours from interactions with their environment. A 'disease' status is given to children who fail to learn the socially acceptable behaviours. The mechanisms that lead to deficits in using socially accepted behaviours are strongly intergenerational, based on complex genetic and environmental contributions, including epigenetic mechanisms. Prevention of these deficits requires early, intensive and long-term support to parents and child. Newly discovered epigenetic mechanisms suggest that intensive perinatal interventions will have impacts on numerous aspects of physical and mental health, including DB. This review also concludes that: a) subtypes of disruptive behaviours should not be aggregated because they have different developmental trajectories and require specific corrective interventions; b) the overt-covert and destructive-nondestructive dimensions appear the most useful to create DB subtypes; c) overt DB onset before covert DB because the latter require more brain maturation; d) DB subtype taxonomies are more useful for clinicians than developmental taxonomies because the latter are post mortem diagnoses and clinicians' retrospective information is unreliable; e) we need large-scale collaborative preventive experimental interventions starting during early pregnancy to advance knowledge on causes and prevention of DB problems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".