Cannabis Use Characteristics Associated with Self-Reported Cognitive Function in a Nationally Representative U.S. sample
Bibliographic record
Abstract
BACKGROUND: With increases in cannabis use and potency, there is a need to improve our understanding of the impact of use on cognitive function. Previous research indicates long-term cannabis use may have a negative effect on executive function. Few studies have examined persistence of it in protracted abstinence, and there is limited evidence of predictors of worse cognitive function in current and former users. In this study, we aim to evaluate the associations between cannabis use status (current, former, and never use) and self-report cognition. Further, we investigate if cannabis use characteristics predict self-report cognitive function. METHODS: = 36,309) conducted in the USA between 2012 and 2013 were used alongside the Executive Function Index scales. The data were analyzed by using Ordinary Least Squares regression. RESULTS: = 24,956, Female = 56.6%). Self-reported cognition of former users was in-between that of current and never users. Several cannabis use characteristics were associated with self-reported cognition in current and former users. CONCLUSION: While prospective studies are required to confirm, findings suggest cannabis use is linked to worse cognition. There may be some limited recovery of cognition in former users and some cannabis use characteristics predict impairment. These findings add to our understanding of the cognitive impact of cannabis use. As worse cognitive function may impact relapse, findings have implications for personalization of cannabis use disorder treatment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".