Short-term effects of cannabis consumption on cognitive performance in medical cannabis patients
Bibliographic record
Abstract
This observational study examined the acute cognitive effects of cannabis. We hypothesized that cognitive performance would be negatively affected by acute cannabis intoxication. Twenty-two medical cannabis patients from Southwestern Ontario completed the study. The majority (n = 13) were male. Mean age was 36.0 years, and mean level of education was 13.7 years. Participants were administered the same brief neurocognitive battery three times during a six-hour period: at baseline (“Baseline”), once after they consumed a 20% THC cannabis product (“THC”), and once again several hours later (“Recovery”). The average self-reported level of cannabis intoxication prior to the second assessment (i.e., during THC) was 5.1 out of 10. Contrary to expectations, performance on neuropsychological tests remained stable or even improved during the acute intoxication stage (THC; d: .49−.65, medium effect), and continued to increase during Recovery (d: .45−.77, medium-large effect). Interestingly, the failure rate on performance validity indicators increased during THC. Contrary to our hypothesis, there was no psychometric evidence for a decline in cognitive ability following THC intoxication. There are several possible explanations for this finding but, in the absence of a control group, no definitive conclusion can be reached at this time.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".