Female and Male Myths about Sexuality: A Systematic Review
Bibliographic record
Abstract
Background and Purpose: Individuals’ beliefs about sexuality are, at times, founded on exaggerated, invalid, and unscientific concepts. Such false notions influence current sexual attitudes and behaviors in female and male populations. From this perspective, the present study reviewed the most common myths around sexuality among women and men. Materials and Methods: This systematic review was conducted on various databases, including PubMed, Google Scholar, Magiran, Scopus, PsycINFO, IranDoc, Ovid, ProQuest, Scientific Information Database (SID) and the Cochrane Library. For this purpose, the relevant studies published from 1990 to 2022 were retrieved. After screening the given studies with reference to their abstracts, 7 cross-sectional and comparative studies were included in this systematic review. Results: Based on the search, 281 articles were obtained. The quality of the studies was assessed using the newcastle-ottawa scale (NOS). So, based on these studies, the female and male myths about sexuality could be divided into 5 main domains: Sexual functioning, practice and behavior, body image and sexual identity, first sexual intercourse and sexuality in special situations. Conclusion: The review of the selected articles revealed that female and male populations had multiple myths behind their beliefs about sexuality, depending on numerous factors. Moreover, it was suggested to provide sex education to the general population by healthcare providers (HCPs), particularly through incorporating it into school curricula.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".