Investigating the association between school substance programs and student substance use: accounting for informative cluster size
Why this work is in the frame
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Bibliographic record
Abstract
Objectives: The use of substances in adolescents is an increasing public health problem. Many high schools in Canada have implemented school-based programs to mitigate student substance use, but their utility is not conclusive. Polysubstance use data collected on students from multiple schools may be subject to informative cluster size (ICS). The objective of this study was to investigate whether a multivariate analysis approach that addresses ICS provides different conclusions from univariate analyses and methods that do not account for ICS. Methods: We used data from the 2018/2019 cycle of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary Behaviour (COMPASS) study, an ongoing prospective cohort study that annually collects data from Canadian high schools and students. We compared results from four analytical approaches that estimate marginal associations between each school substance program and the four substance use behaviours (binge drinking, cannabis, e-cigarette, and cigarette): univariate generalized estimating equations (GEE), univariate cluster-weighted GEE (CWGEE), multivariate GEE, and multivariate CWGEE. Results: We observed that the proportion of students who engage in each of the four behaviours was higher in small schools and lower in large schools. In general, the univariate and multivariate analyses produced comparable results. Some differences existed between multivariate CWGEE and GEE. CWGEE indicated that the school program on cannabis had an odds ratio (OR) and 95 % confidence interval (CI) of 0.83 (0.73, 0.95) on all substance use, but GEE produced a null association with an OR (95 % CI) of 0.92 (0.79, 1.07). Conclusions: When ICS is present in clustered school data, weighted and unweighted analyses may produce different results. Care is needed to investigate the relationship between cluster size and the outcome, and use appropriate methods for analysis. Certain substance programs may influence student behaviour in other substances, highlighting the need for a multivariate analytical approach when studying the use of substances by adolescents.
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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 | 0.023 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it