The epidemiology of substance use among street children in resource‐constrained settings: a systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: To compile and analyze critically the literature published on street children and substance use in resource-constrained settings. METHODS: We searched the literature systematically and used meta-analytical procedures to synthesize literature that met the review's inclusion criteria. Pooled-prevalence estimates and 95% confidence intervals (CI) were calculated using the random-effects model for life-time substance use by geographical region as well as by type of substance used. RESULTS: Fifty studies from 22 countries were included into the review. Meta-analysis of combined life-time substance use from 27 studies yielded an overall drug use pooled-prevalence estimate of 60% (95% CI = 51-69%). Studies from 14 countries contributed to an overall pooled prevalence for street children's reported inhalant use of 47% (95% CI = 36-58%). This review reveals significant gaps in the literature, including a dearth of data on physical and mental health outcomes, HIV and mortality in association with street children's substance use. CONCLUSIONS: Street children from resource-constrained settings reported high life-time substance use. Inhalants are the predominant substances used, followed by tobacco, alcohol and marijuana.
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".