Can Emotion Dysregulation Explain the Association Between Attachment Insecurities and Teen Dating Violence Perpetration?
Bibliographic record
Abstract
Attachment theory provides important insight regarding the etiology of teen dating violence perpetration (TDV-P). Attachment insecurities have been associated with TDV-P, but the mechanisms underlying this association remain unclear. Furthermore, as of now, studies have failed to explore whether the relation between attachment insecurities and TDV-P varied according to its forms (i.e., psychological, physical or sexual) or to the perpetrator’s gender. This study aimed to investigate if emotion dysregulation mediates the association between attachment insecurities and different forms of TDV-P among girls and boys. Adolescents ( M age = 16 years; n = 3,214; 60% girls) were recruited from a one-stage stratified cluster sample of 34 high schools in Quebec, Canada. Path analyses with probit regression models were conducted separately for girls and boys. Attachment anxiety and avoidance were associated with more emotion dysregulation. Emotion dysregulation was, in turn, associated with higher probabilities of physical TDV-P in girls and psychological TDV-P in girls and boys. Surprisingly, emotion dysregulation was not associated with sexual TDV-P. Attachment anxiety remained directly related to higher probabilities of perpetrating all forms of TDV. These findings support the hypotheses set forth by attachment theory and highlight the utility of this theory to understand and potentially prevent TDV-P. Practitioners should more specifically address adolescents’ attachment anxiety, as it seems more related to TDV-P. Finally, this study underscores the necessity of considering gender and specific forms of TDV-P to understand the association between attachment insecurities, emotion dysregulation, and TDV-P.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".