Longitudinal Associations between Life Satisfaction and Cannabis Use Initiation, Cessation, and Disorder Symptom Severity in a Cohort of Young Swiss Men
Bibliographic record
Abstract
Motivations for cannabis use may include coping with negative well-being. Life satisfaction, a hallmark of subjective well-being, could play a role in cannabis use among young adults. This study aims to assess whether life satisfaction (SWLS) at age 21 is associated with cannabis initiation and cessation between the ages of 21 and 25, and with cannabis use severity (CUDIT) at age 25. Data were drawn from a cohort of young Swiss males. Associations of life satisfaction with initiation, cessation, and severity were assessed with logistic and zero-truncated negative binomial regressions. Age, family income, education, alcohol, and tobacco use at age 21 were used as adjustment variables. From a sample of 4778 males, 1477 (30.9%) reported cannabis use at age 21, 456 (9.5%) initiated use between age 21 and 25, and 515 (10.8%) ceased by age 25. Mean (SD) SWLS was significantly higher among non-users at age 21: 27.22 (5.35) vs. 26.28 (5.80), p < 0.001. Negative associations between life satisfaction at age 21 and cannabis use initiation (OR = 0.98, p = 0.029) and severity at age 25 (IRR = 0.97, p < 0.001) were no more significant in adjusted analyses (OR = 0.98, p = 0.059 and IRR = 0.99, p = 0.090). Life satisfaction at age 21 was not associated with cannabis cessation (OR = 0.99, p = 0.296). Results suggest that the predictive value of life satisfaction in cannabis use is questionable and may be accounted for by other behaviors, such as tobacco and alcohol use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".