Negative Affect and Drinking among Indigenous Youth: Disaggregating Within- and Between-Person Effects
Bibliographic record
Abstract
Abstract Negative affect (depression/anxiety) and alcohol use among Indigenous youth in Canada remain a concern for many communities. Disparate rates of these struggles are understood to be a potential outcome of colonization and subsequent intergenerational trauma experienced by individuals, families, and communities. Using a longitudinal design, we examined change in alcohol use and negative affect, and reciprocal associations, among a group of Indigenous adolescents. Indigenous youth ( N = 117; 50% male; M age =12.46–16.28; grades 6–10) from a remote First Nation in northern Quebec completed annual self-reported assessments on negative affect (depression/anxiety) and alcohol use. A Latent Curve Model with Structured Residuals (LCM-SR) was used to distinguish between- and within-person associations of negative affect and alcohol use. Growth models did not support change in depression/anxiety, but reports of drinking increased linearly. At the between-person level, girls reported higher initial levels of depression/anxiety and drinking; depression/anxiety were not associated with drinking. At the within-person level, drinking prospectively predicted increases in depression/anxiety but depression/anxiety did not prospectively predict drinking. When Indigenous adolescents reported drinking more alcohol than usual at one wave of assessment, they reported higher levels of negative affect than expected (given their average levels of depression/anxiety) at the following assessment. Our findings suggest that when Indigenous youth present for treatment reporting alcohol use, they should also be screened for negative affect (depression/anxiety). Conversely, if an Indigenous adolescent presents for treatment reporting negative affect, they should also be screened for alcohol use.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".