1003 Non-Medical Use of Prescription Stimulants for Daytime Sleepiness in University Students
Bibliographic record
Abstract
University students may use off-label prescription stimulants to prolong alertness or manage the daytime effects of poor sleep. Stimulant use has been associated with sleep disturbance, anxiety, increased heart rate, nausea, and dependence. The objective of this study was to determine the prevalence of, and factors associated with, non-medical use of prescription stimulants among university students. We surveyed 3,699 university students aged 18–35 attending Memorial University in Newfoundland, Canada. Participants indicated whether or not they had used prescription stimulants (e.g., Adderall) for the specific non-medical purpose of helping them stay awake in the past month. Univariate and multivariate logistic regression were used to examine the demographic and clinical factors associated with stimulant use. Covariates included sociodemographics and the following standardized measures: Hospital Anxiety and Depression Scale, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Prescription Drug Attitudes Questionnaire. Of the participants, 73% were female, with 49% aged between 18–21 years. One hundred eleven (3%) students reported the non-medical use of prescription stimulants to help them stay awake. Male sex (p=.02), poor sleep quality (p<.001), higher anxiety (p=.001), more depressive symptoms (p<.001), daytime sleepiness (p=.04), and permissive attitudes towards drug use (p<.001) were all independent predictors of non-medical use of prescription stimulants; however, when entered into a multivariate model the only clinical factors that remained significant were poor sleep quality (AOR=5.82; 95%Cl, 1.36 to 24.84; p=0.017) and more positive attitudes to non-medical use of prescription medication (AOR=2.52; 95%Cl, 1.06 to 5.99; p=0.037; AOR=10.41; 95%Cl, 4.57 to 23.72; p<0.001). The prevalence of stimulant use in this sample was lower than previously reported in other university samples. Those with poor sleep quality and/or more positive attitudes towards the non-medical use of prescription medication were more likely to use stimulants to reduce daytime sleepiness. Prevention or intervention programs should target beliefs that support stimulant taking behavior. N/A.
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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 | 0.000 |
| 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".