Motives for pornography use and women's sexual wellbeing: Insights from a 42-country study
Bibliographic record
Abstract
Background and aims: Despite a growing body of research on pornography use among women, there is a lack of understanding of the problematic versus non-problematic nature. The current study aimed to investigate the relationship between women's motivations for pornography use and sexual wellbeing using a cross-sectional, self-report survey design among participants from 42 countries. Methods: The total sample included 82,243 participants, of whom 46,874 (57.0%) identified as women and were analyzed. The participants' age averaged at M = 29.67 years, with a standard deviation of SD = 10.11. Participants were asked to complete a questionnaire assessing their motivations for pornography use, as well as measures of sexual functioning, sexual desire, and sexual satisfaction. Results: Study results suggest that across cultures, women's motivations for pornography use are associated with their sexual wellbeing. Specifically, when women reported using pornography for their own pleasure or sexual curiosity, it was associated with fewer sexual functioning problems and higher sexual desire. Conversely, when women reported using pornography due to a lack of sexual satisfaction in their relationships, it was associated with more sexual functioning problems. Discussion and conclusions: These findings highlight the need to consider the multifaceted nature of pornography use among women, including the usage motives, to fully understand associations with sexual wellbeing. Additionally, the study emphasizes the importance of conducting further research utilizing longitudinal designs, to establish the directionality between pornography use motivations and sexual wellbeing among women.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".