The Interplay of Perceptions and Conflict Behaviors during Disagreements: A Daily Study of Physical Teen Dating Violence Perpetration
Bibliographic record
Abstract
Physical dating violence (DV) is a widespread problem among adolescents. A growing body of literature demonstrates that physical DV often occurs during disagreements when partners use destructive conflict management strategies, such as conflict engagement (e.g., losing control, criticizing) or withdrawal (e.g., acting cold, being distant). However, little is known regarding how the individual daily variability on the use of destructive conflict management strategies can influence the probability of perpetrating day-to-day physical DV, especially if the other partner is also perceived as using destructive behaviors. Using an intensive longitudinal approach, the current study first aimed to examine the daily associations between the use of various conflict management strategies and physical DV perpetration in adolescent dating relationships. A second objective was to investigate if perceived partner’s conflict behaviors moderated the relation between self-reported conflict management strategies and day-to-day physical DV perpetration. A sample of 216 adolescents ( M age = 17.03, SD = 1.49) involved in a dating relationship, completed a baseline assessment followed by 14 daily diaries. Results of multilevel logistic analyses revealed that using conflict engagement strategies significantly increased the probability of day-to-day physical DV perpetration. Furthermore, the probability of perpetrating physical DV was significantly higher on days in which teens reported using high levels of conflict engagement while also perceiving their partner as using high levels of conflict engagement or withdrawal. These findings yield new insights on the daily context in which disagreements might escalate into aggression. Evidence from this study further supports the conflict escalation pattern and the demand/withdraw communication pattern in the context of adolescent dating relationships. Preventive initiatives should address the interplay of perceptions and conflict behaviors concerning physical DV perpetration.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".