Multiple Substance Use Disorders and Self-Reported Cognitive Function in U.S. Adults: Associations and Sex-Differences in a Nationally Representative Sample
Bibliographic record
Abstract
Polysubstance use is a growing public health concern that has been associated with poor clinical outcomes. Compared to single-drug users, this population suffers greater deficits in cognitive function, which hinder treatment success and recovery. Despite its high prevalence and poor prognosis, epidemiological research on polysubstance use and accompanying cognitive profile is lacking. We investigated associations between numbers of past-year co-occurring substance use disorders (SUDs) and self-reported cognitive function using data from the National Epidemiologic Survey for Alcohol and Related Conditions III (NESARC-III). Regression analyses revealed a significant negative association between cognitive scores and numbers of past-year SUDs, which was moderated by sex. After adjusting for confounding variables, greater numbers of SUDs were associated with declining self-reported cognitive function, and this relationship was stronger among females. Our findings expand on current literature on cognitive impairments among polysubstance users and provide a novel, nuanced description of this relationship among the general population. We highlight the need for targeted and individualized treatment approaches in order to improve outcomes in this population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".