Cannabis use is both independently associated with and mediates worse psychosocial health in patients with epilepsy
Bibliographic record
Abstract
OBJECTIVE: To examine whether cannabis use is associated with or mediates psychosocial health in people with epilepsy. METHODS: Consecutive adult epilepsy patients visiting the Calgary Comprehensive Epilepsy Programme clinic were administered validated patient-reported outcome measures (PROMs) including the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), Quality of Life in Epilepsy (QOLIE-10-P), EuroQOL five dimensions five level scale (EQ-5D-5L), Global Assessment of Severity of Epilepsy Scale, Global Assessment of Disability Associated with Seizures Scale and the Treatment Satisfaction Questionnaire for Medication scale. We used multiple regression analyses to investigate associations between cannabis use and PROMs. Mediation analyses were performed to determine the degree to which cannabis modulated the associations between current or past psychiatric disorders, monthly seizure frequency, and 1-year seizure freedom on psychosocial health. RESULTS: Of 337 consecutive patients, 71 (21%) reported cannabis use. Cannabis use was independently associated with depression (NDDI-E score≥14; OR 3.90; 95% CI 2.01 to 7.59; p<0.001), lower quality of life (β=-16.73, 95% CI - 26.26 to - 7.20; p=0.001), worse epilepsy-related disability (OR 2.23, 95% CI 1.19 to 4.17; p=0.01) and lower satisfaction with antiepileptic medication (OR 0.41, 95% CI 0.23 to 0.72; p=0.002). Cannabis use mediates 7%-12% of the effect of a psychiatric history on depression, worse quality of life and worse health valuation. CONCLUSIONS: There is a strong and independent association between cannabis use and poor psychosocial health, and it partially mediates the deleterious effect of a psychiatric history on these same outcomes. Inclusion of PROMs in future cannabis trials is warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".