Temperament, Bullying, and Dating Aggression: Longitudinal Associations for Adolescents in a Romantic Relationship
Bibliographic record
Abstract
Adolescent bullying perpetration has previously been associated with dating benefits and costs in the short- and long-term, yet it is unclear how early temperament traits facilitate these associations. Therefore, the developmental pathways from temperament in early adolescence to bullying perpetration in middle adolescence and to dating outcomes in late adolescence were examined. Participants included 463 individuals who completed self-report measures on temperament traits at age 12, bullying perpetration at age 14, dating outcomes at age 19, and were in a romantic relationship at age 19. Findings from a path analysis revealed that an early adolescent temperament trait reflecting difficulty with self-regulation (i.e., lower inhibitory control) was associated with middle adolescent bullying perpetration and bullying perpetration was associated with late adolescent dating benefits (i.e., more dating partners) and costs (i.e., higher dating aggression perpetration). Lower inhibitory control also had significant indirect associations to the late adolescent dating outcomes through middle adolescent bullying perpetration. Findings suggest that although a temperament trait can facilitate adaptive dating outcomes through bullying, it can also come at a cost for romantic relationships. Results highlight the importance of early tailoring of bullying interventions to the self-regulatory difficulties of youth to prevent adverse long-term outcomes and to also recognize the challenges of developing interventions for behavior that can result in benefits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".