The Emotional Experience of Intercourse and Sexually Transmitted Diseases
Bibliographic record
Abstract
BACKGROUND: Epidemiologic data document high risks for many sexually transmitted diseases (STDs) among US adolescents and young adults. GOAL: This case-control study used decision trees to investigate the relationship between STD incidence and emotional reactions to intercourse. STUDY DESIGN: For this study, 188 adolescents and young adults (mean age, 24.9 years [SD = 8.2]) at a regional public STD clinic completed a behavioral and psychological questionnaire and underwent a workup for STD. RESULTS: The prevalence of STD in this group was 44.8%. Decision-tree analysis identified emotional reactions to intercourse that were associated with STD diagnosis for some patients: feeling good about oneself after sex half the time or less (OR = 3.21; 95% CI = 1.73-5.95), feeling comfortable during sex half the time or less (OR = 2.17; 95% CI = 1.07-4.40), and feeling angry after sex (OR = 1.90; 95% CI = 0.91-3.99). Findings of a logistic regression model of emotional reactions to intercourse were significant (chi-square = 24.6; df = 8; P < 0.002), but adding behavioral variables did not improve prediction. CONCLUSIONS: For some of these young adults at the time of life when they are at highest risk of STD, emotional factors have higher odds ratios for STD diagnosis than the traditionally assessed behavioral variables. This underscores the need for interventions targeted to specific subgroups and for readily available mental health services.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".