Knowledge, Attitude and Practice regarding HIV/AIDS among University students in Xinjiang
Bibliographic record
Abstract
Objective: The aim of this paper is to assess the level of knowledge on HIV/AIDS and its risk factors, attitude towards HIV/AIDS and AIDS patients and its transmission and to identify high risk behaviors associated with HIV/AIDS among university students in Xinjiang. Methodology: A cross–sectional survey was conducted among students enrolled in two universities, the Xingjiang University (XU) and Xinjiang Medical University (XMU). Data was collected using self-administered standardized questionnaire on attitude and practice regarding HIV/AIDS among 200 students randomly selected students from XU and 200 students from XMU Result: Among the 400 students who participated in the study Overall, the mean knowledge score was 19.3 +5.5. Their knowledge score ranges from 2 to 30. Mean knowledge scores is significantly different by ethnicity, sex, subject major, and year of study in university. Only 33.3% of the respondents had positive attitude towards HIV/AIDS patient. With regards high risk behavior associated with HIV transmission, 15.8% had at least 1 risk behavior related to unprotected sexual exposure Conclusion: HIV/AIDS health education efforts should be intensified in non-medical universities, among female students, first year students and Uyghur and other minorities. About two-thirds of the university students in Xinjiang had negative attitude towards HIV/AIDS and HIV/AIDS patients. At the same time about 15% of these students reported having at least 1 high risk behavior related to sex and unprotected sex.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".