Investigating Sex and Gender Influences on the Use and Effects of Cannabis
Bibliographic record
Abstract
Sex and gender differences have been demonstrated in the use, harms, and effects of cannabis and in cannabis use disorder. However, research investigating these differences is limited, particularly as the cannabis landscape continues to rapidly shift and grow following the legalization of non-medical cannabis. Study 1 examined sex differences in the acute pharmacological effects of an intoxicating dose of alcohol combined with a moderate dose of cannabis (12.5%/94 mg ∆9-tetrahydrocannabinol; THC) smoked ad libitum in 28 adults (12 females, 16 males) who used cannabis at least once per week. Limited sex differences were found across all outcomes; however, in the alcohol-cannabis combined condition, females smoked significantly less cannabis, though no sex differences were uncovered in any acute effects. Study 2 investigated sex differences in the acute pharmacological effects of a range of cannabis doses (0%/0 mg, 6.25%/47 mg, 12.5%94 mg, 22.0%/165 mg THC) smoked ad libitum in 35 adults (18 females, 17 males) who used cannabis 1-5 days per week. Minimal sex differences were revealed in smoking topography, blood cannabinoid concentrations, vitals, subjective effects, pharmacokinetic-pharmacodynamic relationships, mood, and cognition. Study 3 explored gender influences on cannabis use and treatment trajectories through qualitative interviews with 23 adults (10 cisgender women, 12 cisgender men, 1 non-binary person) who had received treatment for cannabis-related problems. Four major themes were identified including: 1) a lack of perceived relationship between gender and cannabis use trajectories; 2) influences of masculinity and recreational motivations for cannabis use among men; 3) influences of social factors, stigma, and coping with mental health symptoms on cannabis use trajectories among women; and 4) influences of concurrent substance use and a lack of awareness of cannabis harms and treatment options on cannabis use trajectories, regardless of gender. Additionally, Study 3 unexpectedly uncovered fraudulent and deceptive practices in some virtual participants, providing the opportunity to generate awareness of this growing issue in online studies and offer potential strategies to detect and prevent fraud and deception in future research. These findings provide insights into the influences of sex on the acute effects of cannabis and the influences of gender on cannabis use and treatment trajectories, highlighting the importance of considering sex and gender when examining the use, harms, and effects of cannabis to better inform education, prevention, and treatment.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".