Female Sexual Arousal Disorders
Bibliographic record
Abstract
INTRODUCTION: Definitions and terminology for female sexual arousal disorder (FSAD) are currently being debated. While some authors have suggested that FSAD is more a subjective response rather than a genital response, others have suggested that desire and arousal disorders should be combined in one entity. Persistent genital arousal disorder (PGAD) is a new entity which is suggested to be defined as Restless Genital Syndrome. Aims. The aims of this brief review are to give definitions of the different types of FSAD, describe their aetiology, prevalence and comorbidity with somatic and psychological disorders, as well as to discuss different medical and psychological assessment and treatment modalities. METHODS: The experts of the International Society for Sexual Medicine's Standard Committee convened to provide a survey using relevant databases, journal articles, and own clinical experience. RESULTS: Female Arousal Disorders have been defined in several ways with focus on the genital or subjective response or a combination of both. The prevalence varies and increases with increasing age, especially at the time of menopause, while distress decreases with age. Arousal disorders are often comorbid with other sexual problems and are of biopsychosocial etiology. In the assessment, a thorough sexological history as well as medical and gynecological history and examination are recommended. Treatment should be based on of the symptoms, clinical findings and, if possibly, on underlying etiology. CONCLUSION: Recommendations are given for assessment and treatment of FSAD and PGAD.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".