Are sexual functioning problems associated with frequent pornography use and/or problematic pornography use? Results from a large community survey including males and females
Why this work is in the frame
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Bibliographic record
Abstract
There is much debate regarding whether pornography use has positive or negative associations with sexuality-related measures such as sexual functioning problems. The present study aimed to examine differential correlates between quantity (frequency of pornography use–FPU) and severity (problematic pornography use–PPU) of pornography use with respect to sexual functioning problems among both males and females. Multi-group structural equation modeling was conducted to investigate hypothesized associations between PPU, FPU, and sexual functioning problems among males and females (N = 14,581 participants; females = 4,352; 29.8%; Mage=33.6 years, SDage=11.0), controlling for age, sexual orientation, relationship status, and masturbation frequency. The hypothesized model had excellent fit to the data (CFI = 0.962, TLI = 0.961, RMSEA = 0.057 [95% CI = 0.056-0.057]). Similar associations were identified in both genders, with all pathways being statistically significant (p < .001). PPU had positive, moderate associations (βmales=0.37, βfemales=0.38), while FPU had negative, weak associations with sexual functioning problems (βmales=-0.17, βfemales=-0.17). Although FPU and PPU had a positive, moderate association, they should be assessed and discussed separately when examining potential associations with sexuality-related outcomes. Given that PPU was positively and moderately and FPU negatively and weakly associated with problems in sexual functioning, it is important to consider both PPU and FPU in relation to sexual functioning problems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it