Sexual and Drug Use Risk Behaviors of Internal Long Distance Truck Drivers in Iran.
Bibliographic record
Abstract
BACKGROUND: Long Distance Truck Drivers (LDTDs) and their sexual health risk behaviors have been associated with greater prevalence of sexually transmitted Infections (STIs), HIV and hepatitis virus transmission. However, there is no information about Iranian LDTDs' high-risk behaviors. The aim of this investigation was to estimate the prevalence of high-risk behaviors in Iranian LDTDs. METHODS: This cross-sectional study was conducted in Jun 2014 with LDTDs from Tehran Province of Iran. LDTDs were recruited via convenience sampling and given a 43-item reliable and valid questionnaire to assess sexual health risk behaviors and demographic and background characteristics of study participants. RESULTS: A total of 349 LDTDs with the mean age of 36.91 yr (range, 19-65 yr) participated in the study. The average duration of staying away from home for participants was 5 d (SD=±1). Majority of the LDTDs were married (82.2 %) and had more than 5 yr (inclusive) of formal education (95.7%). Younger LDTDs reported more condom use with their partners (r=-0.170, P≤0.001), more extramarital sexual contacts (r=-0.157, P≤0.001), more pay for sex (r=-0.110, P≤0.005) and condom use in their extra-marital sex contacts (including with sex workers) (r=-0.176, P≤0.001). CONCLUSION: Iranian LDTDs have specific risk factors for unhealthy sexual behaviors. Prevention efforts must emphasize on specific high-risk groups.
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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 | 0.001 |
| 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 | 0.000 |
| 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".