Cannabidiol effects on cognition in individuals with cocaine use disorder: Exploratory results from a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Cocaine use disorder (CUD) is associated with various cognitive deficits that impede patients' functionality, prognosis and therapeutic outcomes. New pharmacological treatments for CUD that could improve cognition are needed. OBJECTIVE: To explore whether cannabidiol (CBD) is superior to placebo to improve cognitive functioning in individuals with CUD. METHODS: We conducted an exploratory analysis of a single site, randomized, double-blind, placebo-controlled trial evaluating CBD's efficacy in reducing craving, cocaine use and relapse in individuals with CUD. Seventy-eight individuals diagnosed with CUD were randomized to receive either CBD (800 mg) or placebo for 92 days. We used the Cambridge Neuropsychological Test Automated Battery (CANTAB) to assess inhibition (Stop Signal Task; SST), risky decision making (Cambridge Gambling Task; CGT) and visual memory (Pattern Recognition Memory; PRM). This assessment was made on day 1, day 7 and at week 6. We controlled for sex, severity of dependence and baseline cognitive scores in our generalized estimating equation models. RESULTS: Both groups performed similarly on the PRM (correct answers: p = 0.080), SST (stop signal reaction time: p = 0.644) and CGT (quality of decision making: p = 0.994; deliberation time: p = 0.507; delay aversion: p = 0.968; risk taking: p = 0.914) tests. CONCLUSIONS: We found no evidence for 800 mg of CBD to be more efficacious than placebo for improving cognitive outcomes. Clinical trials evaluating pharmacological treatments for CUD should continue to be a research priority.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".