Drug-related harm among people who inject drugs in Thailand: summary findings from the Mitsampan Community Research Project
Bibliographic record
Abstract
BACKGROUND: For decades, Thailand has experienced high rates of illicit drug use and related harms. In response, the Thai government has relied on drug law enforcement to address this problem. Despite these efforts, high rates of drug use persist, and Thailand has been contending with an enduring epidemic of human immunodeficiency virus (HIV) among people who inject drugs (IDU). METHODS: In response to concerns regarding drug-related harm in Thailand and a lack of research focused on the experiences and needs of Thai IDU, the Mitsampan Community Research Project was launched in 2008. The project involved administering surveys capturing a range of behavioral and other data to community-recruited IDU in Bangkok in 2008 and 2009. RESULTS: In total, 468 IDU in Bangkok were enrolled in the project. Results revealed high rates of midazolam injection, non-fatal overdose and incarceration. Syringe sharing remained widespread among this population, driven primarily by problems with access to syringes and methamphetamine injection. As well, reports of police abuse were common and found to be associated with high-risk behavior. Problems with access to evidence-based drug treatment and HIV prevention programs were also documented. Although compulsory drug detention centers are widely used in Thailand, data suggested that these centers have little impact on drug use behaviors among IDU in Bangkok. CONCLUSIONS: The findings from this project highlight many ongoing health and social problems related to illicit drug use and drug policies in Bangkok. They also suggest that the emphasis on criminal justice approaches has resulted in human rights violations at the hands of police, and harms associated with compulsory drug detention and incarceration. Collectively, the findings indicate the urgent need for the implementation of evidence-based policies and programs in this setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".