Primary Substance Use Prevention Programs for Children and Youth: A Systematic Review
Bibliographic record
Abstract
CONTEXT: An updated synthesis of research on substance abuse prevention programs can promote enhanced uptake of programs with proven effectiveness, particularly when paired with information relevant to practitioners and policy makers. OBJECTIVE: To assess the strength of the scientific evidence for psychoactive substance abuse prevention programs for school-aged children and youth. DATA SOURCES: A systematic review was conducted of studies published up until March 31, 2020. STUDY SELECTION: Articles on substance abuse prevention programs for school-aged children and youth were independently screened and included if they met eligibility criteria: (1) the program was designed for a general population of children and youth (ie, not designed for particular target groups), (2) the program was delivered to a general population, (3) the program only targeted children and youth, and (4) the study included a control group. DATA EXTRACTION: Two reviewers independently evaluated study quality and extracted outcome data. RESULTS: Ninety studies met eligibility criteria, representing 16 programs. Programs evaluated with the largest combined sample sizes were Drug Abuse Resistance Education, Project Adolescent Learning Experiences Resistance Training, Life Skills Training (LST), the Adolescent Alcohol Prevention Trial, and Project Choice. LIMITATIONS: Given the heterogeneity of outcomes measured in the included studies, it was not possible to conduct a statistical meta-analysis of program effectiveness. CONCLUSIONS: The most research has been conducted on the LST program. However, as with other programs included in this review, studies of LST effectiveness varied in quality. With this review, we provide an updated summary of evidence for primary prevention program effectiveness.
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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 | 0.017 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".