The Association Between Secondhand Harms From Alcohol and Mental Health Outcomes Among Postsecondary Students
Bibliographic record
Abstract
OBJECTIVE: There is a paucity of research on the prevalence and consequences of secondhand harms from alcohol. The current study (a) investigated whether secondhand harms can be clustered into latent factors that reflect distinct but related types of harms and (b) examined the associations between experiencing secondhand harms and mental health outcomes, including anxiety, depression, and subjective mental well-being, among first-year Canadian postsecondary students. The moderating effect of living arrangement (i.e., living on campus or not) on the associations was also tested. METHOD: The sample included 1,885 first-year undergraduate students (49.8% female; mean age = 18.31 years) from three Canadian universities. Exploratory and confirmatory factor analyses were used to determine the factor structure of the harms measure. Path analysis was used to assess the association between harms and mental health outcomes. Models accounted for age, sex, and frequency of heavy drinking. RESULTS: Seventy-one percent of the sample reported experiencing at least one type of secondhand harm. The harms examined clustered into two distinct but related factors: strains (e.g., interrupted sleep) and threats (e.g., being harassed or insulted). Both threats and strains were associated with higher levels of anxiety and depression and poorer subjective well-being. Associations were stronger for threats and did not differ by living arrangement. CONCLUSIONS: Experiencing secondhand harms from alcohol, particularly threats, may have negative implications for student mental health over and above students' own drinking. Programs and policies on university campuses targeting both alcohol use and mental health should consider how to reduce both the prevalence and impact of secondhand harms from alcohol on students.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".