Comparative study between effect of Cannabis and Synthetic Cannabinoids on cognitive functions
Bibliographic record
Abstract
Background: Synthetic cannabinoid usage is on the rise around the world, and it has become a huge global health issue. Previous studies showed a relationship between synthetic cannabinoids and cognitive function decline either after acute or chronic usage. Aim of the study: The present study aims at comparing between natural and synthetic cannabinoids effect on cognitive functions in a sample of Egyptian patients. Subjects and methods: Thirty patients using synthetic cannabinoids with or without cannabis and 30 patients using cannabis were included in the study. Montreal Cognitive Assessment was used to test cognitive functions. Results: Impairments in attention, language, orientation, abstract thinking, visuospatial and executive functions were observed in patients using synthetic cannabinoids with or without cannabis and were significantly higher than in patients using cannabis alone. Conclusion: Synthetic cannabinoids and cannabis both cause cognitive dysfunction and when cannabis abusers add synthetic cannabinoids to cannabis, it causes more cognitive dysfunction. According to the findings of this study, future research should focus on evaluating each cognitive domain with more extensive test batteries and supporting these assessments with brain imaging studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".