Substance Abuse and Stress Levels in Canadian University Students
Bibliographic record
Abstract
Background: University students often report feeling intense stress, high anxiety, depressive feelings, low selfesteem, suicidal ideation, and substance abuse.This study examined correlations of student stress levels to their abuse of alcohol and non-prescription drugs. Materials and Method:A total of 100 Canadian university students (mean age 20.2 years, SD=2.5, 33 males, 67 females) participated in an internet survey.They all completed a 30-item questionnaire dealing with their use of alcohol or non-prescribed drugs "to cope" with the stress of studying and exams, and with symptoms such as nightmares, depression, feelings of "being better off dead," and low self-esteem.The questionnaire also assessed the extent of positive attitude to professors and the pride in or contentment with the social status as a university student.Results: High proportions of students reported use of alcohol (76%) or of non-prescribed drugs (83%) to cope with the stress of university life.Only 6% of the students indicated that they used neither alcohol nor nonprescribed drugs.Total scores on the Student Stress Questionnaire were significantly correlated with reports of substance abuse: higher level of stress was reported by students using alcohol (r=.51) or non-prescribed drugs (r=.50).The substance abusing students more often reported feeling depressed, worthless, useless, and being better off dead, and they had more often nightmares about exams or about uncompleted assignments (Pearson rs from .26 to .40).Discussion: The high prevalence of the use of alcohol and non-prescribed drugs among university students is worrisome, but it also seems consistent with glorification of alcohol consumption both in contemporary films and in novels.Conclusions: University students who abuse alcohol and/or non-prescription drugs report higher levels of academic stress in their lives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".