Development of Aggression Subtypes from Childhood to Adolescence: a Group-Based Multi-Trajectory Modelling Perspective
Bibliographic record
Abstract
The persistence of elevated subtypes of aggression beginning in childhood have been associated with long-term maladaptive outcomes. Yet it remains unclear to what extent there are clusters of individuals following similar developmental trajectories across forms (i.e., physical and indirect) and functions (i.e., proactive and reactive) of aggression. We aimed to identify groups of children with distinct profiles of the joint development of forms and functions of aggression and to identify risk factors for group membership. A sample of 787 children was followed from birth to adolescence. Parent and teacher reports, and standardised assessments were used to measure two forms and two functions of aggressive behaviour, between six and 13 years of age along with preceding child, maternal, and family-level risk-factors. Analyses were conducted using a group-based multi-trajectory modelling approach. Five trajectory groups emerged: non-aggressors, low-stable, moderate-engagers, high-desisting, and high-chronic. Coercive parenting increased membership risk in the moderate-engagers and high-chronic groups. Lower maternal IQ increased membership risk in both high-desisting and high-chronic groups, whereas maternal depression increased membership risk in the high-desisting group only. Never being breastfed increased membership risk in the moderate-engagers group. Boys were at greater risk for belonging to groups displaying elevated aggression. Individuals with chronic aggression problems use all subtypes of aggression. Risk factors suggest that prevention programs should start early in life and target mothers with lower IQ. Strategies to deal with maternal depression and enhance positive parenting while replacing coercive parenting tactics should be highlighted in programming efforts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".