Using eye-tracking to quantify the impact of prostate cancer treatments on male libido: A pilot study.
Bibliographic record
Abstract
231 Background: Eye-tracking research has demonstrated that heterosexual men with normal testosterone levels attend visually to features of women associated with fertility, notably their breast size and waist to hip ratio. As such, eye-tracking data can serve as an implicit measure of a man’s libido. Many treatments for prostate cancer (PCa)—in particular androgen deprivation therapy (ADT)—depress sexual interest in men, but there is no objective measure of the intensity of this effect. Here we explore whether eye-tracking can be used to quantify the impact of PCa treatments on men’s libido. Methods: We used an IRB-approved deception protocol to explore the validity of eye-tracking technology for assessing the level of sexual interest of PCa patients and normal controls. Three age-matched groups of heterosexual men aged 50 years and older were recruited. They were: PCa patients using ADT, PCa patients not using ADT, and healthy controls. Unaware that their eye movements were being tracked, all were exposed to photographs of female models, either fully clothed (neutral) or minimally clothed (sexy). Number and duration of eye fixations on target areas of the female models’ bodies were recorded. Results: Trends observed in our preliminary data suggest that men on ADT exhibit differential patterns of visual attention to sexual stimuli compared to men in the other two groups. Although confirmation with a larger sample size is required, such shifts in attention may provide an objective measure of the influence of cancer treatments on the libido of PCa patients. Conclusions: Eye-tracking technology may provide a reliable and objective technique for measuring the libido of cancer patients. Such data could help patients be better informed about psychological side effects when making treatment decisions. They could also lead to ways to both study and reduce the impact of PCa treatments on men’s sexual interest.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".