0235 Cannabis Use as a Moderator Between Sleep and Academic Performance in Canadian University Students
Bibliographic record
Abstract
Abstract Introduction Good sleep quality plays a crucial role in optimal cognitive functioning and well-being, making it a key factor in academic performance. However, university students are particularly vulnerable to sleep disturbances that may be influenced by lifestyle factors such as substance use. Cannabis, a commonly used substance among young adults, is known to disturb sleep and impair cognitive performance. Hence, we investigated the moderating effect of cannabis use on the relationship between sleep disturbances and academic performance of Canadian university students. Methods A total of 778 Canadian university students (M=22.5 ±4.6 years; 71.4% females) participated in a 20-minutes anonymous online survey. The survey included, among others, the Pittsburgh Sleep Quality Index (PSQI) and a homemade lifestyle habits questionnaire. A moderation analysis was performed using PROCESS 4.2 to examine the moderating effect of cannabis use (average weekly usage) on the relationship between sleep disturbances (subscale #5 of the PSQI) and academic performance (self-reported satisfaction with school performance). Results The moderation model was significant (F[3,774] = 4.32, p =.005), explaining 1.7% of the variance. Cannabis use had a significant main effect on school performance (b = -0.04, p =.015), and the interaction was significant (b = -0.07, p =.005). Sleep disturbances were associated with school performance when cannabis use was at one SD below the mean (b = -0.15, p =.027) but not at the mean (b = -0.09, p =.118) or above the mean (b = 0.04, p =.537). A simple slope analysis showed that among students with minimal or no cannabis use, fewer sleep disturbances was associated with better academic performance, while more sleep disturbances predicted poorer performance. However, for students with moderate or high cannabis use, fewer sleep disturbances were not associated with better academic performance. Conclusion This study highlights how cannabis use may mitigate the beneficial effect of undisturbed sleep on academic performance. Given the modest explained variance, it is essential to consider additional factors. Further research on the influence of lifestyle habits on the relationship between sleep and academic performance among Canadian university students is needed to help students achieve their full academic potential. Support (if any)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".