Do Cannabis Use Motives Mediate the Relationship between PTSD Symptoms and Cannabis Craving to Trauma Cues?
Bibliographic record
Abstract
Cannabis use is common in individuals with posttraumatic stress disorder (PTSD). The PTSD-cannabis relationship is important as cannabis use can worsen PTSD outcomes. Cannabis use motives are a useful construct for understanding the PTSD-cannabis relationship. Frequent pairing of a trauma cue with substance use to cope can lead to conditioned substance craving. The extant research has not yet examined potential mechanisms to explain this effect. We recruited 51 cannabis users with a trauma history for a cannabis cue-reactivity study to examine coping motives as a potential mediator of the hypothesized relationship between PTSD symptoms and cannabis craving to trauma cues. Participants first completed a validated cannabis use motives measure. They were then exposed to a personalized audio and visual cue based on their trauma experience and reported on their cannabis craving immediately following using a standardized measure. Coping motives were contrasted with enhancement motives as the mediator. Results supported our first hypothesis: PTSD symptoms were associated with increased cannabis craving following personal trauma cue exposure. However, our second hypothesis of an indirect effect through coping motives was not supported. We did find an independent main effect of coping motives on cannabis craving triggered by trauma cue exposure. The lack of an interaction between PTSD symptoms and coping motives on trauma-cue induced craving is potentially due to other factors we did not examine that help strengthen the relationship (e.g., sleep). These findings have important clinical implications for targeting both PTSD symptoms and coping motives to prevent the development of conditioned cannabis craving to trauma reminders.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".