Sexual Activity and Impairment in Women with Systemic Sclerosis Compared to Women from a General Population Sample
Bibliographic record
Abstract
OBJECTIVE: Reports of low sexual activity rates and high impairment rates among women with chronic diseases have not included comparisons to general population data. The objective of this study was to compare sexual activity and impairment rates of women with systemic sclerosis (SSc) to general population data and to identify domains of sexual function driving impairment in SSc. METHODS: Canadian women with SSc were compared to women from a UK population sample. Sexual activity and, among sexually active women, sexual impairment were evaluated with a 9-item version of the Female Sexual Function Index (FSFI). RESULTS: Among women with SSc (mean age = 57.0 years), 296 of 730 (41%) were sexually active, 181 (61%) of whom were sexually impaired, resulting in 115 of 730 (16%) who were sexually active without impairment. In the UK population sample (mean age = 55.4 years), 956 of 1,498 women (64%) were sexually active, 420 (44%) of whom were impaired, with 536 of 1,498 (36%) sexually active without impairment. Adjusting for age and marital status, women with SSc were significantly less likely to be sexually active (OR = 0.34, 95%CI = 0.28-0.42) and, among sexually active women, significantly more likely to be sexually impaired (OR = 1.88, 95%CI = 1.42-2.49) than general population women. Controlling for total FSFI scores, women with SSc had significantly worse lubrication and pain scores than general population women. CONCLUSIONS: Sexual functioning is a problem for many women with scleroderma and is associated with pain and poor lubrication. Evidence-based interventions to support sexual activity and function in women with SSc are needed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".