Temporal changes in cognitive functions and associated factors among stimulant users: a 12-month, prospective study
Bibliographic record
Abstract
Cognitive impairments are commonly observed in individuals who use stimulants, yet few studies have tracked these individuals longitudinally. This prospective, 12-month longitudinal study investigated changes in cognitive functioning among active stimulant users and explored the associated factors. Adults with recent stimulant use were recruited from substance misuse treatment clinics and the community. Their demographics, history of drug use, and stimulant use disorder severity were assessed with structured clinical interviews. Global cognitive function and frontal executive function were measured every three months using the Montreal Cognitive Assessment (MoCA) and the Frontal Assessment Battery (FAB) over one year. Linear mixed-effects models evaluated temporal trajectories and associated factors related to the Changes in cognitive functions. Among 76 analysed participants, their frequency of stimulant uses were active and stable over 12 months. The MoCA scores averaged below the clinical cut-off at baseline, although no further persistent decline was observed. In contrast, FAB scores presented no systematic temporal changes. Being female and being of older ages were found to be associated with lower MoCA and FAB. None of severity, education, recent stimulant use, and lifetime duration of use, were found to be associated with cognition. While stimulant users exhibited some modest cognitive declines at baseline, no further substantial cognitive deterioration was observed over the one-year study period. Cognitive outcomes were more strongly associated with demographic factors than SUD severity or stimulant use patterns. These findings highlight the need for more sensitive tools to detect subtle cognitive changes associated with stimulant uses.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".