HIV/AIDS-knowledge and attitudes in the Arabian Peninsula: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: HIV/AIDS prevention has been widely adopted worldwide, but little is known about HIV/AIDS knowledge and attitudes in the Arabian Peninsula. AIM: To summarize the level of knowledge and attitude about HIV/AIDS in seven Arabian Peninsula countries (Saudi Arabia, Oman, Kuwait, Qatar, Bahrain, Yemen, and the United Arab Emirates (UAE)). METHODS: A systematic literature search was performed using combined keywords in four scientific databases of peer-reviewed publications from January 2010 to June 2019. Twenty-five articles were included in the systematic review, and twenty studies in the meta-analysis. The data was analyzed using a random-effect model due to the heterogeneity between the studies. RESULTS: Seventeen studies reported on the level of knowledge and overall knowledge about HIV/AIDS in this region: 74.4% (95% confidence interval (CI): 66.8%-82.0%, p<0.001) and the attitude was 52.8% (95% CI: 36.9%-68.6%, p<0.001). A study from Oman reported higher knowledge levels (95.5%, 95% CI: 94.2%-96.8%) while less than a quarter of the Bahrain population had positive attitudes 22.5% (95% CI: 20.5%-24.5%). Medical doctors showed higher knowledge (94.1%, 95% CI: 92.9%-95.3%), but a positive attitude was only observed in 32.5% (95% CI: 28.8%-36.2%) of the dentists toward HIV/AIDS. CONCLUSION: The overall knowledge about HIV/AIDS was found to be satisfactory (74.4%), but about half (52.8%) of those displayed negative attitudes toward HIV/AIDS. Regular training courses as well as reviewing and reinforcing HIV/AIDS prevention guidelines can be useful to update knowledge and improve attitudes in this region.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".