Changes in quality of life and its associated factors among illicit drug users in Vietnamese mountainous provinces: a 12-month follow-up study
Bibliographic record
Abstract
BACKGROUND: Sustainability of methadone maintenance treatment (MMT) program involves regularly assessing its impact on health and social outcomes of drug users in different settings, particularly in disadvantaged areas. In this study, we evaluated the change in quality of life (QoL), and identified associated factors amongst drug users over the course of 12-month MMT in Vietnamese mountainous provinces. METHODS: We conducted a longitudinal study among patients from 6 MMT clinics in three mountainous provinces of Vietnam. At baseline, we screened 300 participants and after a 12-month treatment, 244 participants remained to involve in the study. World Health Organization Quality of Life short form instrument (WHOQOL-BREF) was used to measure the QoL of patients. The magnitude of the changes was extrapolated. RESULTS: There were significant changes in all four dimensions of quality of life measured by WHOQoL-BREF between baseline and 12 months with the effect size ranged from 0.21 to 0.24. Increased age, being workers compared to unemployment and having health problems or comorbidities were positively related to reduced scores of QoL. CONCLUSIONS: To conclude, we observed a significant increase in the QoL level regarding physical, psychological, social relationships and environmental aspects among people who used drug after 12 months of MMT. Findings from this study emphasize the role of continuously receiving MMT treatment among people using drugs to enhance their QoL.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".