Etiological Factors Affecting Female Sexuality: A Systematic Review
Bibliographic record
Abstract
Introduction: Evidence suggests that masturbation, genital stimulation, body awareness and movement, pelvic floor exercises, depression, anxiety, positive and negative feelings, personality type, emotional and overall well-being and emotional intelligence have been studied in association with female orgasm through the years. Additionally, healthcare providers of sexual health and most women lack information regarding sexual satisfaction and reaching orgasm. Few studies have addressed this issue.Aim: To systematically study the effect of social, behavioral, and psychological factors on female orgasm. Methods: An extensive search was conducted in PubMed, CINAHL, Google Scholar and Scopus, according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Statement (PRISMA) guidelines, for relevant articles published between June 2002 and June 2022. Studies in languages other than English were excluded. The following Medical Subject Headings (MeSH) terms were used: female, orgasm, psychological, behavioral, social, sexual. Inclusion criteria concerned studies that sampled adult healthy women, used quantitative methodology and explored factors influencing sexual satisfaction. Results: Out of 531 studies, forty-five were further screened. A total of twenty-one studies were reviewed, most of which were conducted in the USA, Portugal and the United Kingdom. They were followed by Switzerland, Iran, Brazil, Sweden, Canada, Hungary and the Netherlands. Four major themes influencing female sexual satisfaction emerged from the synthesis: psychological disorders, psychological background, genital stimulation, body awareness and movement.Conclusions: The female orgasm was influenced by a number of factors, some of which adversely affected it
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".