Emotion Regulation, Motives and Personality Risk for Cannibis Use Problems in Emerging Adulthood: A Person-centred Approach
Bibliographic record
Abstract
Legalization of cannabis in Canada and parts of the United States has created a need for additional research on factors that contribute to cannabis problems among vulnerable populations, including emerging adults (ages 18 to 29 years of age). There is substantial evidence pointing to cannabis use motives, personality, and emotion regulation difficulties as important correlates of cannabis-related problems, however, there is little research integrating these factors. This study sought to examine the combined effect of cannabis use motives, personality, and emotion dysregulation in a North American sample. Participants were 126 emerging adults (ages 19-29, 38.1 % women). Using latent profile analysis, a four-group solution was extracted. Two high risk groups were identified, suggesting that different patterns of motives for use, emotion dysregulation, and neuroticism might have greater combined risk than in isolation, and may be useful targets for future approaches to preventing or treating cannabis use problems in emerging adulthood.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".