Sexually Transmitted Disease Testing Misconceptions Threaten the Validity of Self‐Reported Testing History
Bibliographic record
Abstract
OBJECTIVE: Sexually transmitted disease (STD) testing is fundamental to STD prevention and control. We sought to comprehensively examine young women's beliefs about the STD testing process. DESIGN AND SAMPLE: Descriptive, cross-sectional, survey investigation. Women aged 18-24 (n = 302) drawn from four women's health clinics and one university classroom. MEASURES: Participants completed the RoTEST, which measures five domains of women's STD testing beliefs and a demographic survey. RESULTS: Many women believed they would be screened for all STDs when they receive STD testing (40%) and that visual inspection by a provider was a valid method of STD screening for gonorrhea (35%), chlamydia (32%) and HSV (77%). More than a quarter believed that a Pap test screens for gonorrhea (23%) and chlamydia (26%). Twenty-one percent reported that discussing STD testing with a provider is difficult and most reported feeling more comfortable seeking STD testing from an STD specialist rather than a family doctor (79%). CONCLUSIONS: Young women have numerous misconceptions about the STD testing process that may interfere with the validity of their self-reported STD testing history and subsequently undermine public health efforts to improve STD prevention and control. Innovative approaches to educating women about the testing process 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 | 0.016 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".