Women Find It Easy and Prefer to Collect Their Own Vaginal Swabs to Diagnose Chlamydia trachomatis or Neisseria gonorrhoeae Infections
Bibliographic record
Abstract
BACKGROUND: Self-collected specimens can be used to screen asymptomatic women for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC). We surveyed women's opinions on ease and preferences as to sampling after collecting their own vaginal swab and urine and a physician collection of vaginal swab and cervical swab. METHODS: In 7 North American cities, a questionnaire was used for women after they participated in a clinical trial of nucleic acid amplification testing of various specimens. A total of 1,090 women consenting to gynecologic sampling for CT and GC (82% of those sampled) volunteered to complete the survey. We analyzed the data for ease of self-collection and preferences for a vaginal swab, urine, or cervical swab. RESULTS: The average age was 26.6 years; 59.6% were black, 25.5% white, 11% Hispanic, 1.9% Asian, and 2% unknown. Thirty-five percent had more than one sex partner in the past 6 months, 84.9% had been previously tested for a sexually transmitted infection (STI), and 49.2% had experienced an STI. A total of 90.4% found it very easy to self-collect a vaginal swab. This was not influenced by age, education, or study site. Seventy-six percent preferred a vaginal swab over a pelvic examination, 60% over a urine collection, and 94% indicated that they would be tested more often if a vaginal swab was available. CONCLUSION: Self-collected vaginal swabs were easy to collect and patients preferred them over urine and cervical swabs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".