STD/HIV PREVENTION KNOWLEDGE, STD AND HIV/AIDS INCIDENT AMONG GAY, TRANSVESTITE, AND TRANSGENDER IN JAKARTA AND SURROUNDING
Bibliographic record
Abstract
This study was conducted to determine the correlation of STDs/HIV prevention knowledge level with STD and HIV/AIDS incidences among gays, transvestites and transgender people in Jakarta and surrounding areas. This was a quantitative study with a cross-sectional design involving 114 people consist of gays, transvestites and transgender women aged over 17 years old and live in Jakarta and surrounding. Samples obtained with a snowball sampling technique. The study was conducted through Gaya Warna Lentera Indonesia Governmental Organization in May to June 2019. An online questionnaire was used in the form of demographic data to determine the respondents characteristic and STDs/HIV Prevention Knowledge questionnaire from Public Health Agency of Canada to measure the STDs/HIV prevention knowledge level. STDs/HIV prevention knowledge showed a significant relationship with STDs incidence in gay, transvestite and transgender people in Jakarta and surrounding (OR = 2.807; p = 0.017) and the relationship was found most significantly in gay (OR = 10.929 ; p = 0.000). While the STDs/HIV prevention knowledge were not associated with the incidence of HIV/AIDS (OR = 0.467; p = 0.144). Knowledge has a significant relationship with the incidence of STDs, but not with the incidence of HIV/AIDS. Therefore, health care providers need to socialize more in-depth about the signs, symptoms and preventions of STDs. Regular medical check-up need to be undertaken by gay, transvestite and transgender to find out their status of STDs and HIV/AIDS. It’s needed to reduce the growth rates of STDs and HIV/AIDS incidence among them
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".