Evaluating the Relationship Between Structural Determinants of Health and Quality of Sexual Life in Women: A Systematic Review
Bibliographic record
Abstract
Objectives: Quality of sexual life can be influenced by cultural and social contexts. This study aimed to investigate the relationship between structural determinants of health (such as education, income level, job, culture, and ethnicity) and quality of sexual life in women. Methods: In this systematic review, we searched six databases, including Web of Science, Scopus, ProQuest, PubMed/Medline (NLM), Cochrane, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) to obtain all the related observational studies (cross-sectional, cohort, and case-control). Results: Nine studies met the inclusion criteria. Based on the Newcastle-Ottawa Scale (NOS), the risk of bias in most of the included studies was fair. According to the results, the relationship between education level and quality of sexual life among women was significant in four studies. Also, in one study, job and income level were significantly correlated with women’s quality of sexual life. Conclusions: Based on the results, structural determinants of health, including education, job, and income level were significantly related with women’s quality of sexual life.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".