Indirect Associations Between PTSD Symptoms and Cannabis Problems in Young Adults: The Unique Roles of Cannabis Coping Motives and Medicinal Use Orientation
Bibliographic record
Abstract
Background: Cannabis use in young adulthood has been associated with exposure to traumatic events and posttraumatic stress disorder (PTSD). Coping motives for cannabis use represent one mechanism linking PTSD with cannabis problems, yet some individuals with PTSD consider their cannabis use to be medicinal in nature. While a medicinal orientation to cannabis overlaps conceptually with coping motives, it could be associated with unique cannabis outcomes. Objectives: This study examined trauma-related coping motives and medicinal cannabis orientation as mediators of the association between PTSD symptoms and cannabis outcomes in young adults. Method: Data came from an online survey of 212 university students (M age = 19.41; 70.3% Women; 43.4% White) who used cannabis in the past month and endorsed a traumatic life event. Path analyses examined associations of PTSD symptoms with past month cannabis frequency and problems through medicinal cannabis orientation (i.e., number of mental health symptoms that cannabis is used to manage) and trauma-related coping motives. Results: PTSD symptoms were associated with trauma-related coping motives but not with medicinal cannabis orientation. Both trauma-related coping motives and medicinal cannabis orientation were uniquely associated with greater cannabis use frequency, but only trauma-related coping motives were associated with greater cannabis problems. There were significant indirect relationships from PTSD symptoms to cannabis use frequency and problems through trauma-related coping motives but not through medicinal cannabis orientation. Conclusions: Results support unique contributions of trauma-related coping motives and medicinal cannabis orientation to cannabis outcomes and suggest that trauma-related coping motives are specifically implicated in the link between PTSD and cannabis problems.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".