Female sexual function before and during the severe acute respiratory syndrome coronavirus-2 pandemic: a systematic review and Meta-analysis of longitudinal studies
Bibliographic record
Abstract
PurposeTo compare the female sexual function before and during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic using the Female Sexual Function Index (FSFI).MethodsRelevant studies were retrieved by online databases and manual searching reporting FSFI scores before and during the SARS-CoV-2 pandemic. The methodological quality of reviewed articles was evaluated using the Newcastle-Ottawa Scale, and heterogeneity with the I2 statistic. The standardized mean differences (SMDs) with their 95% confidence intervals (CIs) were calculated by random-effect meta-analyses.ResultsFour studies met the inclusion criteria reporting 1002 sexually active non-pregnant women comparing results of the 19-item FSFI. The meta-analysis of the overall FSFI score showed an SMD (95% CI) of −1.16 (−1.97 to −0.35), comparing the pandemic with the pre-pandemic scores. In addition, SMD scores for the FSFI domains were also significantly lower during the pandemic for arousal −0.80 (−1.13 to −0.48), orgasm −0.66 (−1.07 to −0.25), satisfaction −0.59 (−0.97 to −0.22), and pain −0.35 (−0.54 to −0.16), whereas there were not significant differences for desire and lubrication domains. There was a low risk of bias and the sensitivity analysis suggests that results are robust.ConclusionThe available studies showed a lower overall FSFI score during the pandemic, suggesting an increased risk of female sexual dysfunction compared to prepandemic results. Also, there were increased risks of sexual arousal, orgasm, satisfaction, and pain disorders. However, there were no alterations in the desire and the lubrication domains. Limitations are related to the heterogeneity populations, and pandemic confounding and aggravating factors.
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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 | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.041 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".