Internalizing symptoms are indirectly associated with simultaneous alcohol and cannabis use through specific motives for simultaneous use: A longitudinal study of young adults
Bibliographic record
Abstract
BACKGROUND: This study examined motivational pathways between internalizing symptoms (i.e., depression, anxiety, stress) and simultaneous alcohol and cannabis use among young adults. METHODS: Participants (N = 151; 64% female, Mean age = 22.07) completed baseline questionnaires assessing internalizing symptoms and simultaneous use motives, and then reported their alcohol and cannabis use each day for 21 days. Participants repeated these procedures again 6 months and 12 months postbaseline. Daily survey responses were used to calculate the number of simultaneous use days involving heavy drinking (4 or more drinks for females; 5 or more drinks for males) and light drinking at each wave for each participant. The total number of negative consequences reported across all simultaneous use days was also calculated for each participant at each wave. RESULTS: Multilevel mediation analyses revealed that within-person increases in internalizing symptoms (a latent factor consisting of depression, anxiety, and stress indicators) at a given wave were indirectly associated with (a) a greater number of heavy drinking simultaneous use days (controlling for number of cannabis-only days and heavy drinking alcohol-only days) and (b) greater negative consequences on simultaneous use days (controlling for negative consequences on cannabis-only and alcohol-only days). These within-person associations were mediated by increases in positive (i.e., reward/enhancement) motives for simultaneous use. At the between-person level, greater average internalizing symptoms (aggregated across waves) were indirectly associated with more light drinking simultaneous use days via coping motives, and with fewer heavy drinking simultaneous use days via conformity motives (controlling for frequency of single substance use). CONCLUSIONS: Young adults may combine cannabis with heavy episodic drinking more frequently during periods when they experience elevations in internalizing symptoms, mediated by a desire to achieve the positive/enhancing effects of simultaneous use. Findings may inform alcohol and cannabis harm reduction interventions tailored for young adults with internalizing symptoms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".