Preventing HIV transmission among Iranian prisoners: Initial support for providing education on the benefits of harm reduction practices
Bibliographic record
Abstract
BACKGROUND: Harm reduction is a health-centred approach that seeks to reduce the health and social harms associated with high-risk behaviors, such as illicit drug use. The objective of this study is to determine the association between the beliefs of a group of adult, male prisoners in Iran about the transmission of HIV and their high-risk practices while in prison. METHODS: A cross-sectional study was conducted in 2004. The study population was a random selection of 100 men incarcerated at Rajaei-Shahr prison. The data were collected through a self-administered questionnaire. Focus group discussions were held at the prison to guide the design of the questionnaire. The relationship between components of the Health Belief Model (HBM) and prisoners' risky HIV-related behaviors was examined. RESULTS: Calculating Pearson's correlation coefficient, a significant, positive association was found between the benefit component of the HBM and prisoners not engaging in HIV high-risk behaviors. CONCLUSION: Educational harm reduction initiatives that promote the effectiveness of strategies designed to reduce the risk of HIV transmission may decrease prisoners' high-risk behaviors. This finding provides initial support for the Iran prison system's current offering of HIV/AIDS harm reduction programming and suggests the need to offer increased education about the effectiveness of HIV prevention practices.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".