Reduced memory and attention performance in a population-based sample of young adults with a moderate lifetime use of cannabis, ecstasy and alcohol
Bibliographic record
Abstract
Regular use of illegal drugs is suspected to cause cognitive impairments. Two substances have received heightened attention: 3,4-methylenedioxymethamphetamine (MDMA or 'ecstasy') and delta-9-tetrahydrocannabinol (THC or 'cannabis'). Preclinical evidence, as well as human studies examining regular ecstasy consumers, indicated that ecstasy use may have negative effects on learning, verbal memory and complex attentional functions. Cannabis has also been linked to symptoms of inattention and deficits in learning and memory. Most of the published studies in this field of research recruited participants by means of newspaper advertisements or by using word-of-mouth strategies. Because participants were usually aware that their drug use was critical to the research design, this awareness may have caused selection bias or created expectation effects. Focussing on attention and memory, this study aimed to assess cognitive functioning in a community-based representative sample that was derived from a large-scale epidemiological study. Available data concerning drug use history allowed sampling of subjects with varying degrees of lifetime drug experiences. Cognitive functioning was examined in 284 young participants, between 22 and 34 years. In general, their lifetime drug experience was moderate. Participants completed a neuropsychological test battery, including measures for verbal learning, memory and various attentional functions. Linear regression analysis was performed to investigate the relationship between cognitive functioning and lifetime experience of drug use. Ecstasy and cannabis use were significantly related to poorer episodic memory function in a dose-related manner. For attentional measures, decrements of small effect sizes were found. Error measures in tonic and phasic alertness tasks, selective attention task and vigilance showed small but significant effects, suggesting a stronger tendency to experience lapses of attention. No indication for differences in reaction time was found. The results are consistent with decrements of memory and attentional performance described in previous studies. These effects are relatively small; however, it must be kept in mind that this study focussed on assessing young adults with moderate drug use from a population-based study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".