Psychoactive Substance Use and School Performance among Adolescents in Public Secondary Schools in Uganda
Bibliographic record
Abstract
Introduction: Psychoactive substance use among adolescents influences behavioral and cognitive processes and is associated with adolescents’ performance in school. We therefore sought to investigate association of PASU with adolescents’ school performance. Methods: We employed quantitative methods of data collection and analysis. To test the substance use-school performance association, we specified and estimated fixed effects hierarchical linear models (HLMs). We nested the data in their respective four regions of Uganda. Results: Model estimates show that only alcohol use had significant t-values in association with school performance (b = 1.15, SE =.32, t = 3.83, p = .029 for beer use; b = .82, SE = .18, t = 4.49, p < .001 for wines; and b = .89, SE = .19, t = 4.53, p< .001 for spirits). Conclusions: Alcohol use significantly contributed to the model estimating association between PASU and adolescents’ school performance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".