A review of experimental research on anxiety and sexual arousal: Implications for the treatment of sexual dysfunction using cognitive behavioral therapy
Bibliographic record
Abstract
Clinical models of sexual response link anxiety to the etiology of sexual dysfunction. Furthermore, some cognitive behavioral therapies (CBTs) for sexual dysfunction have included strategies targeting anxiety reduction. This review examines the experimental literature on the effects of manipulating aspects of the anxiety response (e.g., anxious sensations, thoughts, attentional focus) on genital and self-reported sexual arousal. An additional aim was to use this literature to elucidate potential mechanisms that may be useful for CBT for sexual dysfunction. Our review suggested that anxiety sometimes facilitates, inhibits, or has no effect on sexual arousal. These findings suggest that caution is warranted incorporating anxiety-focused interventions in the treatment of sexual dysfunctions. Importantly, little experimental research has utilized precise manipulations of anxiety (e.g., manipulating fear of penetration) that are related to current CBT interventions. To better understand the relationship between anxiety and sexual dysfunction, future research should explore the question of why and how anxiety exerts a variable effect on sexual arousal rather than simply if anxiety exerts an effect on sexual arousal. Importantly, experimental research examining individual differences in beliefs about anxiety and sex may be helpful in answering this important question and help advance and improve CBT interventions for sexual dysfunctions.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".