Visual Attention and Sexual Function in Women
Bibliographic record
Abstract
Abstract Purpose of Review Theoretical models situate attention as integral to the onset and regulation of sexual response and propose that problems with sexual response and subsequent sexual dysfunction result from insufficient attentional processing of sexual stimuli. The goal of this paper is to review literature examining the link between attentional processing of sexual stimuli and sexual function in women. Specifically, we sought to understand whether women with and without sexual dysfunction differ in their visual attention to sexual stimuli and examined the link with sexual response, which would support attention as a mechanism underlying sexual dysfunction. Recent Findings Across women with and without sexual concerns, sexual stimuli are preferentially attended to relative to nonsexual stimuli, suggesting that sexual stimuli are more salient than nonsexual stimuli. Differences between women with and without sexual dysfunction emerge when examining visual attention toward the most salient features of sexual stimuli (e.g., genital regions depicting sexual activity). Consistent with theoretical models, visual attention and sexual response are related, such that increasing attention to sexual cues facilitates sexual arousal, whereas reduced attention to sexual stimuli appears to suppress sexual arousal, which may contribute to sexual difficulties in women. Summary Taken together, the research supports the role of visual attention in sexual response and sexual function. These findings provide empirical support for interventions that target attentional processing of sexual stimuli. Future research is required to further delineate the specific attentional mechanisms involved in sexual response and investigate whether these are modifiable. This knowledge may be beneficial for developing novel psychological interventions targeting attentional processes in the treatment of sexual dysfunctions.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".