Cannabis for the Treatment of Attention Deficit Hyperactivity Disorder: A Report of 3 Cases
Bibliographic record
Abstract
Attention deficit hyperactivity disorder (ADHD) is a chronic neurobehavioral disorder that is highly prevalent in children and adults. An increasing number of patients with ADHD are self-medicating with cannabis, despite a lack of evidence on efficacy and safety. This case report describes 3 males (ages 18, 22, and 23) who have integrated cannabis into their treatment regimen with positive results. Semistructured interviews conducted with the patients describe subjective improvements in symptoms and on quality of life. Improvements on validated rating scales conducted post-cannabis initiation, compared to pre-cannabis initiation obtained from the medical chart, corroborated their personal accounts. Scores on the PHQ-9 (measuring depression) improved by 8-22 points (30-81%), and the SCARED (measuring anxiety) ranged from 0 to 27 points (up to 33%). Improvements on the CEER-9 scale (measuring regulation) ranged from 2 to 7 points (22-78%), and the 9-item SNAP scale (measuring inattention) showed improvements of 2-8 points (7-30%). Mild adverse events including short-term memory problems, dry mouth, and sleepiness were reported. Blood samples were also collected from the patients to determine the plasma concentrations of the cannabinoids and relevant metabolites before and after a cannabis administration. After cannabis use, the plasma levels for CBD and THC ranged from 0 to 15.29 ng/mL and 1.32 to 13.76 ng/mL, respectively. Cannabinoids, however, were not detected prior to dosing, suggesting that cannabis played a complimentary role in the therapeutic regimen of these 3 patients. Clinical trials are recommended to confirm the efficacy of cannabis in the treatment of ADHD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".