In search of optimal genital herpes management and standard of care (INSIGHTS): doctors' and patients' perceptions of genital herpes
Bibliographic record
Abstract
OBJECTIVE: To compare and contrast attitudes and behaviours of family doctors and patients with regard to genital herpes and its management. METHODS: Family doctors and infected patients were surveyed online to explore disease importance/seriousness, emotional impact, transmission and treatment. The study received ethics approval. RESULTS: 400 patients and 200 doctors participated. Doctors estimated the emotional impact of genital herpes to be higher than did patients. Patient distress increased with recurrences and more recent diagnosis. Doctors and patients underestimated the risk of transmission during periods of asymptomatic viral shedding, 45% and 51%, respectively. Doctors reported that 74% of their patients were taking medication, whereas only 29% of patients reported use of antivirals. Doctors reported discussing suppressive therapy with 59% of patients, whereas only 25% of patients recalled such a discussion. Only 40% of patients were aware that daily anti-viral therapy was available to reduce the risk of transmission. The most compelling reason for high interest in suppressive therapy was to reduce the frequency or severity of outbreaks (62%). CONCLUSIONS: Although doctor and patient attitudes and behaviours coincide in a number of areas, there are many areas of misalignment. This presents opportunities for education and improvement in the management of genital herpes.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".