Ready or Not: Exploring Sexual Arousal with Women who Report Sexual Arousal Difficulties
Bibliographic record
Abstract
The purpose of this study is to examine possible differences in genital and subjective components of sexual arousal between women with and without sexual arousal/desire difficulties (SADD). Previous research has focused on physiological differences with women who have SADD, in particular, genital response to erotic stimuli. The pattern of results in the literature indicates that women with SADD exhibit similar genital responses to controls (Meston, Rellini, & McCall, 2010), yet women with SADD typically report a decrease in intensity of genital sensation in sexual situations (Laan, van Driel, & van Lunsen, 2008; Giraldi, Rellini, Pfaus, & Laan, 2013), calling into question the method of measurement employed to assess genitalresponse. In the current study, genital and subjective arousal, along with genital-subjective agreement (i.e., sexual concordance), will be investigated to determine if there is a difference between women with SADD and controls. Participants will include 30 self-identified heterosexual women who will complete a validated self-report measure of sexual function and a session in which they rate their subjective sexual arousal while their genital blood flow is measured in response to various films. Laser Doppler Imaging will be used to measure genital blood flow for the first time in this population. This study could lead to a better understanding of sexual arousal in women with SADD, which will assist with diagnosis, as well as identify areas to focus on when trying to develop treatments for sexual dysfunction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".