Evaluating expectancies: Do community-recruited adults believe that cannabis is an effective stress reliever?
Bibliographic record
Abstract
There is growing interest in using cannabis or specific cannabinoids (e.g., THC, CBD) as therapeutic agents for various stress-related psychiatric disorders (e.g., PTSD, anxiety). While beliefs about a drug, such as expecting to feel a certain way, have strong influences over the actual effects experienced by individuals, they are rarely evaluated in clinical research. In the present exploratory report, we sought to (1) evaluate the extent to which individuals believe that cannabis relieves stress, and (2) examine whether individual characteristics (i.e., age, sex, psychiatric illness, cannabis use frequency) are related to these beliefs. A sample of 234 adults (54.7% female; Mean age=31.37, SD=11.03, 19-69 years old) from the Halifax Regional Municipality community took part in a brief telephone screening interview to assess their eligibility for a larger study (in progress). Information was gathered about the frequency of current (i.e., past month) cannabis use (days per week), the presence of current psychiatric disorder(s) ("yes"/"no"), and the extent to which they believed that cannabis was an effective stress reliever (rating scale from 1 (“not at all”) to 10 (“extremely”)). Subjects reported a mean belief rating of 6.39 (SD=2.26). A multiple regression analysis was run to evaluate whether the belief that cannabis relieves stress was related to age, sex, psychiatric illness, and frequency of current cannabis use. Overall, the model significantly predicted cannabis belief ratings (p<.001, adjusted R2=.17). Among all variables, only frequency of cannabis use contributed significantly to this prediction (B=.544, 95% CI: [.387, .701], p<.001). In general, the present sample of community-recruited adults believed that cannabis was somewhat effective at relieving stress. Additionally, cannabis use frequency was the only variable that predicted the strength of this belief, such that more frequent use was associated with higher belief ratings. This is consistent with prior research indicating that heavier cannabis use is linked to positive cannabis expectancies. Given that stimulus expectancies influence substance-related responses, such findings would further the case for evaluating and controlling for these expectancies in clinical work with cannabis for stress-related conditions. Indeed, clinical cannabis research evaluating samples of heavy or frequent cannabis users may be subject to bias due to higher positive expectancies.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".