The Current Level of HIV/AIDS Knowledge and Sexual Behaviors of Students in Southern China: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: The spread of HIV/AIDS in China is predominantly driven by sexual transmission and it is a fact that HIV transmission among students is quite common, e.g., 480 000 adolescents were infected from 2000 to 2018. Our study aimed to investigate knowledge of HIV/AIDS and sexual behaviors of young students in Southern China. METHODS: A cross-sectional study was conducted based on questionnaire. The information collected included socio-demographic characteristics, knowledge of HIV and risky sexual behaviors. RESULTS: 9027 students were invited and 8349 were eventually enrolled in the study. The following factors were found to be associated with lower level of HIV/AIDS knowledge: female (OR: 0.757, 95% CI 0.689–0.831), residence in rural areas (OR: 0.786, 95% CI: 0.713–0.866), studying in high school (OR = 0.598, CI =0.459–0.779) and secondary vocational school (OR =0.713, CI =0.545–0.933), major in pharmacy (OR = 0.453, CI = 0.331–0.621), medicine (OR = 0.592, CI = 0.402–0.872) and others (OR = 0.671, CI = 0.518–0.871), and little participation in programs for the prevention of AIDS (OR = 0.646, CI = 0.585–0.714). Kendall correlation test showed that students who had risky sexual behaviors all had lower level of HIV/AIDS Knowledge (P < 0.05). CONCLUSIONS: Students who have more knowledge of HIV/AIDS were generally less likely to have risky sexual behaviors. Female students and those who reside in rural areas had lower level of HIV/AIDS knowledge, indicating that we may need to pay more attention to deliver education for these cohorts. It is suggested to follow the strategies used by some developed countries to improve students’ knowledge for HIV/AIDS and prevent its transmission.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".