Effects of Ginger on Disgust, Sexual Arousal, and Sexual Engagement: A Placebo-Controlled Experiment
Bibliographic record
Abstract
Sexual problems are common complaints across countries and cultures, and behavioral immune system theory suggests disgust plays an essential role in sexual functioning. The current study investigated 1) if disgust induced by sexual body fluids would reduce sexual arousal, reduce the likelihood of sexual engagement, and enhance disgust toward subsequent erotic stimuli, and 2) if the administration of ginger would affect these reactions. We administered either ginger or placebo pills to a sample of 247 participants (Mage = 21.59, SD = 2.52; 122 women) and asked them to complete either behavioral approach tasks with sexual body fluids or with neutral fluids. Next, participants viewed and responded to questions concerning erotic stimuli (nude and seminude pictures of opposite-sex models). As expected, the sexual body fluids tasks induced disgust. The elevated disgust induced by sexual body fluids tasks resulted in lower sexual arousal in women, whereas ginger consumption counteracted this inhibiting effect of disgust on sexual arousal. Disgust elicited by sexual body fluids also increased disgust toward the subsequent erotic stimuli. Ginger increased sexual arousal toward the erotic stimuli in both men and women who had completed the neutral fluids tasks. Findings provide further evidence of the role of disgust in sexual problems, and, importantly, that ginger may improve the sexual function of individuals via its sexual arousal-enhancing effect.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".