Anxiety induction and sexual arousal in men and women
Bibliographic record
Abstract
Anxiety can sometimes inhibit and sometimes potentiate sexual arousal. We examined whether an anxiety manipulation in a classical fear-conditioning paradigm impacts self-reported sexual arousal in men and women. University students (62 men, 61 women) underwent differential fear conditioning to erotic images; half the images were sometimes (60%) paired with a shock (CS+) and half were never paired with a shock (CS–). For each trial, participants rated their sexual arousal and anxiety in response to the image; skin conductance response (SCR) and zygomatic and corrugator activity were recorded. During acquisition, self-reported sexual arousal was lower to CS+ than CS− (inhibiting effect), but in men only. During extinction, self-reported sexual arousal was lower to CS+ than CS− for both genders. Some differences produced by CS+ and CS− were observed for SCR and zygomatic and corrugator activation at different points during acquisition and extinction, but the effects were unrelated to ratings of anxiety or sexual arousal. The negative impact of anxiety on sexual arousal appears to be resistant to extinction, and small gender differences were observed. Future studies should include direct measures of physiological sexual arousal. The relationship between sexual arousal and anxiety appears to be complex and should be further investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.002 | 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".