Associations Between Pornography Use Frequency and Intimate Partner Violence Perpetration Among Young Adult Couples: A 2-Year Longitudinal Study
Bibliographic record
Abstract
Pornography use is a common sexual activity for many individuals including those in a romantic relationship. Some studies have shown that violent content depicted in pornography is a risk factor for perpetration of violence in real life. Even if most of these studies examined perpetration of violent behaviors in general, not specifically toward the intimate partner, some studies have shown that pornography use frequency is related to a greater perpetration of intimate partner violence (IPV), while other studies have found that it is not significantly related. However, most previous studies were cross-sectional, sampled individuals rather than couples, and did not include separately forms of IPV (e.g., physical, psychological, and sexual). The present study examined the associations between pornography use frequency and the perpetration of physical and psychological IPV, and sexual coercion among young adult couples. A convenience sample of 113 couples aged between 16 and 29 years old completed self-reported online questionnaires two times over a 2-year period. The results of autoregressive cross-lagged models showed that a person's pornography use frequency at Time 1 was related to their own higher sexual coercion perpetration 2 years later and that a person's sexual coercion perpetration was related to their partner's lower pornography use frequency 2 years later. However, no significant association between pornography use frequency and physical and psychological IPV emerged. In line with previous studies, our results suggest that pornography use represents an important risk factor for the perpetration of sexual coercion. Findings support the need to include education around pornography use in sexual violence prevention programs to avoid that young adults reproduce pornographic scripts in their sexuality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".