Mechanisms Underlying the Link between Cannabis Use and Prospective Memory
Bibliographic record
Abstract
While the effects of cannabis use on retrospective memory have been extensively examined, only a limited number of studies have focused on the links between cannabis use and prospective memory. We conducted two studies to examine the links between cannabis use and both time-based and event-based prospective memory as well as potential mechanisms underlying these links. For the first study, 805 students completed an online survey designed to assess cannabis consumption, problems with cannabis use indicative of a disorder, and frequency of experiencing prospective memory failures. The results showed small to moderate sized correlations between cannabis consumption, problems with cannabis use, and prospective memory. However, a series of mediation analyses revealed that correlations between problems with cannabis use and prospective memory were driven by self-reported problems with retrospective memory. For the second study, 48 non-users (who had never used cannabis), 48 experimenters (who had used cannabis five or fewer times in their lives), and 48 chronic users (who had used cannabis at least three times a week for one year) were administered three objective prospective memory tests and three self-report measures of prospective memory. The results revealed no objective deficits in prospective memory associated with chronic cannabis use. In contrast, chronic cannabis users reported experiencing more internally-cued prospective memory failures. Subsequent analyses revealed that this effect was driven by self-reported problems with retrospective memory as well as by use of alcohol and other drugs. Although our samples were not fully characterized with respect to variables such as neurological disorders and family history of substance use disorders, leaving open the possibility that these variables may play a role in the detected relationships, the present findings indicate that cannabis use has a modest effect on self-reported problems with prospective memory, with a primary problem with retrospective memory appearing to underlie this relationship.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".