Hormones and visual attention to sexual stimuli in older men: an exploratory investigation
Bibliographic record
Abstract
Background Testosterone is associated with sexual desire and performance in men, but little is known about cognitive mechanisms underlying this relationship. Even less is known about the influence of estradiol, despite its production from testosterone, and high receptor density in brain regions related to male sexual behavior.Method We used eye-tracking to compare men’s visual attention to images of fully clothed (i.e. neutral) and minimally clothed (i.e. sexy) models in three groups: androgen-deprived (n = 6) and not androgen-deprived with prostate cancer (n = 11), and healthy controls (n = 7). We also assessed effects of serum testosterone, estradiol, and sex hormone-binding globulin levels.Results We found no group effect for fixations to sexy compared to neutral images, and no influence of testosterone on either total fixations, or proportion of fixations to sexy images. In contrast, we found that sex hormone binding globulin positively predicted total fixations, and estradiol positively predicted proportion of total fixations on sexy images--regardless of androgen treatment status.Conclusion Our results suggest that visual attention to sexual stimuli in men may be significantly affected by hormones. This has potential implications for clinical populations that experience sexual side effects, such as prostate cancer patients on androgen deprivation therapy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".